essay about future of computer

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Essay on the Future of Computer Technology

1. introduction.

The introduction section of "The Future of Computer Technology" serves as a gateway into the exploration of the advancements, challenges, and potential impact of computer technology in our society. As we delve into the future of computer technology, it is essential to understand the rapid evolution and transformation that has taken place over the past few decades. From the advent of the first programmable computers to the emergence of artificial intelligence and quantum computing, the landscape of technology has significantly evolved, reshaping industries, communication, and daily life. In this section, we will examine the driving forces behind the development of computer technology and the crucial role it plays in shaping the future of various sectors, including healthcare, finance, education, and transportation. Additionally, we will consider the ethical and societal implications of these advancements, as well as the potential risks and challenges that come with the rapid progression of technology. By understanding the roots of computer technology and its current state, we can better comprehend the trajectory it is heading towards, laying the groundwork for the in-depth exploration of its future developments and impacts in the subsequent sections of this essay.

2. Advancements in Hardware

In recent years, significant advancements have been made in the field of computer hardware, particularly in the areas of quantum computing and neuromorphic chips. Quantum computing, a revolutionary approach to data processing, has the potential to solve complex problems at an unprecedented speed by harnessing the power of quantum mechanics. This technology leverages quantum bits, or qubits, which can exist in multiple states simultaneously, allowing for the parallel processing of vast amounts of data. As a result, quantum computers have the capability to outperform traditional binary-based systems in tasks such as cryptography, optimization, and simulation. On the other hand, neuromorphic chips are designed to mimic the structure and function of the human brain, offering a new paradigm for computing. Inspired by the brain's neural networks, these chips are equipped with artificial synapses and neurons, enabling them to process and interpret information in a manner akin to human cognition. This neuromorphic approach holds promise for applications in artificial intelligence, robotics, and pattern recognition, as it can potentially deliver higher efficiency and lower power consumption compared to conventional computing architectures. The advancements in hardware, particularly in the realms of quantum computing and neuromorphic chips, signal a transformative shift in the future of computer technology. These innovations have the potential to revolutionize the way we process and analyze data, opening up new possibilities for addressing complex challenges across various domains. As we continue to explore and harness the capabilities of these cutting-edge technologies, the landscape of computing is poised to undergo profound and impactful changes, paving the way for a future that is both exciting and transformative.

2.1. Quantum Computing

Quantum computing is a revolutionary field that has the potential to greatly impact the future of computer technology. Unlike traditional computers that use bits to process information, quantum computers use quantum bits or qubits, which can exist in multiple states at once due to the principles of quantum mechanics. This allows them to perform complex calculations at incredible speeds, making them ideal for solving problems that are currently infeasible for classical computers. One of the key concepts in quantum computing is superposition, where a qubit can exist in both 0 and 1 states simultaneously, and entanglement, where the state of one qubit is dependent on the state of another, regardless of the distance between them. These properties enable quantum computers to process and analyze vast amounts of data in parallel, leading to significant advancements in fields such as cryptography, drug discovery, and optimization problems. However, quantum computing also presents unique challenges, such as the need for sophisticated error correction due to the inherent fragility of qubits. Additionally, the technology is still in its infancy and requires further research and development to become commercially viable. Nevertheless, the potential applications of quantum computing are vast, and as the technology continues to advance, it has the power to revolutionize the future of computer technology.

2.2. Neuromorphic Chips

Neuromorphic chips, also known as brain-inspired chips, are a type of hardware that mimics the structure and function of the human brain. These chips are designed to process information in a way that is similar to how neurons in the brain process signals. By using parallel processing and interconnected nodes, neuromorphic chips are capable of performing tasks such as pattern recognition, sensor processing, and data analysis with greater efficiency and flexibility than traditional computer hardware. One of the key advantages of neuromorphic chips is their ability to adapt and learn from new information, similar to the plasticity of the human brain. This means that they can continuously improve their performance and efficiency over time, making them ideal for applications such as artificial intelligence, robotics, and autonomous systems. Additionally, neuromorphic chips have the potential to significantly reduce power consumption and increase processing speeds, which is essential for the development of future computer technology. Overall, neuromorphic chips represent a promising advancement in hardware technology, offering new opportunities for the development of intelligent and adaptive computing systems. As researchers and engineers continue to explore the potential of these brain-inspired chips, it is likely that we will see significant advancements in the field of computer technology in the coming years, with implications for a wide range of industries and applications.

3. Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and machine learning (ML) are two of the most rapidly advancing fields in computer technology. AI refers to the ability of a machine to replicate human cognitive functions, such as learning, reasoning, and problem-solving. ML, on the other hand, is a subset of AI that involves algorithms allowing machines to learn from data and improve their performance over time without being explicitly programmed. These technologies have the potential to revolutionize various industries, including healthcare, finance, transportation, and more. One of the key aspects of AI and ML is their ability to analyze large datasets and extract valuable insights, leading to more informed decision-making. In healthcare, for example, AI and ML can be used to diagnose diseases, personalize treatment plans, and predict patient outcomes. In finance, these technologies can be utilized for fraud detection, risk assessment, and portfolio management. Additionally, AI-powered autonomous vehicles are poised to transform the transportation industry, making roads safer and transportation more efficient. Furthermore, AI and ML are also driving innovation in natural language processing, computer vision, and robotics. With advancements in natural language processing, machines can understand and respond to human language, leading to the development of virtual assistants and chatbots. Computer vision enables machines to interpret and understand visual information, powering applications such as facial recognition and autonomous drones. Robotics, combined with AI and ML, has the potential to automate tasks in manufacturing, logistics, and other industries, leading to increased efficiency and productivity. In summary, AI and ML are revolutionizing the future of computer technology by enabling machines to learn, analyze data, and perform tasks that were once the exclusive domain of humans. With their wide-ranging applications and potential to drive innovation across industries, AI and ML are poised to shape the future of technology in profound ways.

4. Cybersecurity Challenges and Solutions

As technology continues to advance, cybersecurity has become a critical concern for individuals, businesses, and governments alike. The increasing frequency and sophistication of cyber attacks pose significant challenges to the security of computer technology. Some of the key cybersecurity challenges include data breaches, ransomware attacks, phishing scams, and malware infections. These threats can result in financial losses, reputational damage, and the compromise of sensitive information. In response to these challenges, various cybersecurity solutions have been developed to protect against potential threats. These solutions include the implementation of robust firewalls, encryption technologies, and multi-factor authentication systems. Additionally, the use of artificial intelligence and machine learning algorithms has enabled proactive threat detection and rapid response to cyber attacks. Moreover, ongoing efforts to educate individuals and organizations on the best cybersecurity practices are essential in mitigating potential risks and strengthening overall security measures. As computer technology continues to evolve, it is imperative to remain vigilant and proactive in addressing cybersecurity challenges to safeguard against potential threats and vulnerabilities.

5. Ethical and Social Implications of Future Technologies

The future of computer technology brings to the forefront various ethical and social implications that need to be addressed. As technology continues to advance, there is a growing concern about issues such as data privacy, cybersecurity, and the impact of automation on employment. One of the key ethical considerations is the collection and use of personal data. With the increasing amount of information being gathered by technology companies, there is a need for ethical guidelines to ensure that individuals' privacy is respected and their data is used responsibly. Additionally, the rise of artificial intelligence and automation raises questions about the future of work and the potential displacement of jobs. Ethical considerations in this area include ensuring that the benefits of technological advancements are shared equitably and that measures are in place to support those affected by job displacement. From a social perspective, future technologies have the potential to exacerbate existing inequalities. Access to technology and digital skills can create a divide between those who have access to opportunities and those who do not. It is essential to address these disparities to ensure that the benefits of technology are accessible to all members of society. In conclusion, as we look towards the future of computer technology, it is crucial to consider the ethical and social implications of these advancements. By proactively addressing these issues, we can work towards creating a future where technology benefits society as a whole.

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Envisioning the future of computing

MIT students share ideas, aspirations, and vision for how advances in computing stand to transform society in a competition hosted by the Social and Ethical Responsibilities of Computing.

How will advances in computing transform human society?

MIT students contemplated this impending question as part of the Envisioning the Future of Computing Prize — an essay contest in which they were challenged to imagine ways that computing technologies could improve our lives, as well as the pitfalls and dangers associated with them.

Offered for the first time this year, the Institute-wide competition invited MIT undergraduate and graduate students to share their ideas, aspirations, and vision for what they think a future propelled by advancements in computing holds. Nearly 60 students put pen to paper, including those majoring in mathematics, philosophy, electrical engineering and computer science, brain and cognitive sciences, chemical engineering, urban studies and planning, and management, and entered their submissions.

Students dreamed up highly inventive scenarios for how the technologies of today and tomorrow could impact society, for better or worse. Some recurring themes emerged, such as tackling issues in climate change and health care. Others proposed ideas for particular technologies that ranged from digital twins as a tool for navigating the deluge of information online to a cutting-edge platform powered by artificial intelligence, machine learning, and biosensors to create personalized storytelling films that help individuals understand themselves and others.

Conceived of by the Social and Ethical Responsibilities of Computing (SERC), a cross-cutting initiative of the MIT Schwarzman College of Computing in collaboration with the School of Humanities, Arts, and Social Sciences (SHASS), the intent of the competition was “to create a space for students to think in a creative, informed, and rigorous way about the societal benefits and costs of the technologies they are or will be developing,” says Caspar Hare, professor of philosophy, co-associate dean of SERC, and the lead organizer of the Envisioning the Future of Computing Prize. “We also wanted to convey that MIT values such thinking.”

Prize winners

The contest implemented a two-stage evaluation process wherein all essays were reviewed anonymously by a panel of MIT faculty members from the college and SHASS for the initial round. Three qualifiers were then invited to present their entries at an awards ceremony on May 8, followed by a Q&A with a judging panel and live in-person audience for the final round.

The winning entry was awarded to Robert Cunningham ’23, a recent graduate in math and physics, for his paper on the implications of a personalized language model that is fine-tuned to predict an individual’s writing based on their past texts and emails. Told from the perspective of three fictional characters: Laura, founder of the tech startup ScribeAI, and Margaret and Vincent, a couple in college who are frequent users of the platform, readers gained insights into the societal shifts that take place and the unforeseen repercussions of the technology.

Cunningham, who took home the grand prize of $10,000, says he came up with the concept for his essay in late January while thinking about the upcoming release of GPT-4 and how it might be applied. Created by the developers of ChatGPT — an AI chatbot that has managed to capture popular imagination for its capacity to imitate human-like text, images, audio, and code — GPT-4, which was unveiled in March, is the newest version of OpenAI’s language model systems.

“GPT-4 is wild in reality, but some rumors before it launched were even wilder, and I had a few long plane rides to think about them! I enjoyed this opportunity to solidify a vague notion into a piece of writing, and since some of my favorite works of science fiction are short stories, I figured I’d take the chance to write one,” Cunningham says.

The other two finalists , awarded $5,000 each, included Gabrielle Kaili-May Liu ’23, a recent graduate in mathematics with computer science, and brain and cognitive sciences, for her entry on using the reinforcement learning with human feedback technique as a tool for transforming human interactions with AI; and Abigail Thwaites and Eliot Matthew Watkins, graduate students in the Department of Philosophy and Linguistics, for their joint submission on automatic fact checkers, an AI-driven software that they argue could potentially help mitigate the spread of misinformation and be a profound social good.

“We were so excited to see the amazing response to this contest. It made clear how much students at MIT, contrary to stereotype, really care about the wider implications of technology, says Daniel Jackson, professor of computer science and one of the final-round judges. “So many of the essays were incredibly thoughtful and creative. Robert’s story was a chilling, but entirely plausible take on our AI future; Abigail and Eliot’s analysis brought new clarity to what harms misinformation actually causes; and Gabrielle’s piece gave a lucid overview of a prominent new technology. I hope we’ll be able to run this contest every year, and that it will encourage all our students to broaden their perspectives even further.”

Fellow judge Graham Jones, professor of anthropology, adds: “The winning entries reflected the incredible breadth of our students’ engagement with socially responsible computing. They challenge us to think differently about how to design computational technologies, conceptualize social impacts, and imagine future scenarios. Working with a cross-disciplinary panel of judges catalyzed lots of new conversations. As a sci-fi fan, I was thrilled that the top prize went to a such a stunning piece of speculative fiction!”

Other judges on the panel for the final round included:

Dan Huttenlocher, dean of the MIT Schwarzman College of Computing;
Aleksander Madry, Cadence Design Systems Professor of Computer Science;
Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science;
Georgia Perakis, co-associate dean of SERC and the William F. Pounds Professor of Management; and
Agustin Rayo, dean of the MIT School of Humanities, Arts, and Social Sciences.

Honorable mentions

In addition to the grand prize winner and runners up, 12 students were recognized with honorable mentions for their entries, with each receiving $500.

The honorees and the title of their essays include:

Alexa Reese Canaan, Technology and Policy Program, “A New Way Forward: The Internet & Data Economy”;
Fernanda De La Torre Romo, Department of Brain and Cognitive Sciences, “The Empathic Revolution Using AI to Foster Greater Understanding and Connection”;
Samuel Florin, Mathematics, “Modeling International Solutions for the Climate Crisis;”
Claire Gorman, Department of Urban Studies and Planning (DUSP), “Grounding AI- Envisioning Inclusive Computing for Soil Carbon Applications”;
Kevin Hansom, MIT Sloan School of Management, “Quantum Powered Personalized Pharmacogenetic Development and Distribution Model”;
Sharon Jiang, Department of Electrical Engineering and Computer Science (EECS), “Machine Learning Driven Transformation of Electronic Health Records”;
Cassandra Lee, Media Lab, “Considering an Anti-convenience Funding Body”;
Martin Nisser, EECS, “Towards Personalized On-Demand Manufacturing;
Andi Qu, EECS, “Revolutionizing Online Learning with Digital Twins”;
David Bradford Ramsay, Media Lab, “The Perils and Promises of Closed Loop Engagement”;
Shuvom Sadhuka, EECS, “Overcoming the False Trade-off in Genomics: Privacy and Collaboration”; and
Leonard Schrage, DUSP, “Embodied-Carbon-Computing.”

The Envisioning the Future of Computing Prize was supported by MAC3 Impact Philanthropies.

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How will advances in computing transform human society?

Prize winners

The winning entry was awarded to Robert Cunningham '23, a recent graduate in math and physics, for his paper on the implications of a personalized language model that is fine-tuned to predict an individual’s writing based on their past texts and emails. Told from the perspective of three fictional characters: Laura, founder of the tech startup ScribeAI, and Margaret and Vincent, a couple in college who are frequent users of the platform, readers gained insights into the societal shifts that take place and the unforeseen repercussions of the technology.

“GPT-4 is wild in reality, but some rumors before it launched were even wilder, and I had a few long plane rides to think about them! I enjoyed this opportunity to solidify a vague notion into a piece of writing, and since some of my favorite works of science fiction are short stories, I figured I'd take the chance to write one,” Cunningham says.

The other two finalists, awarded $5,000 each, included Gabrielle Kaili-May Liu '23, a recent graduate in mathematics with computer science, and brain and cognitive sciences, for her entry on using the reinforcement learning with human feedback technique as a tool for transforming human interactions with AI; and Abigail Thwaites and Eliot Matthew Watkins, graduate students in the Department of Philosophy and Linguistics, for their joint submission on automatic fact checkers, an AI-driven software that they argue could potentially help mitigate the spread of misinformation and be a profound social good.

Other judges on the panel for the final round included:

Dan Huttenlocher, dean of the MIT Schwarzman College of Computing;
Aleksander Madry, Cadence Design Systems Professor of Computer Science;
Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science;
Georgia Perakis, co-associate dean of SERC and the William F. Pounds Professor of Management; and
Agustin Rayo, dean of the MIT School of Humanities, Arts, and Social Sciences.

Honorable mentions

In addition to the grand prize winner and runners up, 12 students were recognized with honorable mentions for their entries, with each receiving $500.

The honorees and the title of their essays include:

Alexa Reese Canaan, Technology and Policy Program, “A New Way Forward: The Internet & Data Economy”;
Fernanda De La Torre Romo, Department of Brain and Cognitive Sciences, “The Empathic Revolution Using AI to Foster Greater Understanding and Connection”;
Samuel Florin, Department of Mathematics, "Modeling International Solutions for the Climate Crisis";
Claire Gorman, Department of Urban Studies and Planning (DUSP), “Grounding AI — Envisioning Inclusive Computing for Soil Carbon Applications”;
Kevin Hansom, MIT Sloan School of Management, “Quantum Powered Personalized Pharmacogenetic Development and Distribution Model”;
Sharon Jiang, Department of Electrical Engineering and Computer Science (EECS), “Machine Learning Driven Transformation of Electronic Health Records”;
Cassandra Lee, Media Lab, “Considering an Anti-convenience Funding Body”;
Martin Nisser, EECS, "Towards Personalized On-Demand Manufacturing";
Andi Qu, EECS, "Revolutionizing Online Learning with Digital Twins";
David Bradford Ramsay, Media Lab, “The Perils and Promises of Closed Loop Engagement”;
Shuvom Sadhuka, EECS, “Overcoming the False Trade-off in Genomics: Privacy and Collaboration”; and
Leonard Schrage, DUSP, “Embodied-Carbon-Computing.”

The Envisioning the Future of Computing Prize was supported by MAC3 Impact Philanthropies.

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The present and future of AI

Finale doshi-velez on how ai is shaping our lives and how we can shape ai.

image of Finale Doshi-Velez, the John L. Loeb Professor of Engineering and Applied Sciences

Finale Doshi-Velez, the John L. Loeb Professor of Engineering and Applied Sciences. (Photo courtesy of Eliza Grinnell/Harvard SEAS)

How has artificial intelligence changed and shaped our world over the last five years? How will AI continue to impact our lives in the coming years? Those were the questions addressed in the most recent report from the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted at Stanford University, that will study the status of AI technology and its impacts on the world over the next 100 years.

The 2021 report is the second in a series that will be released every five years until 2116. Titled “Gathering Strength, Gathering Storms,” the report explores the various ways AI is increasingly touching people’s lives in settings that range from movie recommendations and voice assistants to autonomous driving and automated medical diagnoses .

Barbara Grosz , the Higgins Research Professor of Natural Sciences at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) is a member of the standing committee overseeing the AI100 project and Finale Doshi-Velez , Gordon McKay Professor of Computer Science, is part of the panel of interdisciplinary researchers who wrote this year’s report.

We spoke with Doshi-Velez about the report, what it says about the role AI is currently playing in our lives, and how it will change in the future.

Q: Let's start with a snapshot: What is the current state of AI and its potential?

Doshi-Velez: Some of the biggest changes in the last five years have been how well AIs now perform in large data regimes on specific types of tasks. We've seen [DeepMind’s] AlphaZero become the best Go player entirely through self-play, and everyday uses of AI such as grammar checks and autocomplete, automatic personal photo organization and search, and speech recognition become commonplace for large numbers of people.

In terms of potential, I'm most excited about AIs that might augment and assist people. They can be used to drive insights in drug discovery, help with decision making such as identifying a menu of likely treatment options for patients, and provide basic assistance, such as lane keeping while driving or text-to-speech based on images from a phone for the visually impaired. In many situations, people and AIs have complementary strengths. I think we're getting closer to unlocking the potential of people and AI teams.

There's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: Over the course of 100 years, these reports will tell the story of AI and its evolving role in society. Even though there have only been two reports, what's the story so far?

There's actually a lot of change even in five years. The first report is fairly rosy. For example, it mentions how algorithmic risk assessments may mitigate the human biases of judges. The second has a much more mixed view. I think this comes from the fact that as AI tools have come into the mainstream — both in higher stakes and everyday settings — we are appropriately much less willing to tolerate flaws, especially discriminatory ones. There's also been questions of information and disinformation control as people get their news, social media, and entertainment via searches and rankings personalized to them. So, there's a much greater recognition that we should not be waiting for AI tools to become mainstream before making sure they are ethical.

Q: What is the responsibility of institutes of higher education in preparing students and the next generation of computer scientists for the future of AI and its impact on society?

First, I'll say that the need to understand the basics of AI and data science starts much earlier than higher education! Children are being exposed to AIs as soon as they click on videos on YouTube or browse photo albums. They need to understand aspects of AI such as how their actions affect future recommendations.

But for computer science students in college, I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc. I'm really excited that Harvard has the Embedded EthiCS program to provide some of this education. Of course, this is an addition to standard good engineering practices like building robust models, validating them, and so forth, which is all a bit harder with AI.

I think a key thing that future engineers need to realize is when to demand input and how to talk across disciplinary boundaries to get at often difficult-to-quantify notions of safety, equity, fairness, etc.

Q: Your work focuses on machine learning with applications to healthcare, which is also an area of focus of this report. What is the state of AI in healthcare?

A lot of AI in healthcare has been on the business end, used for optimizing billing, scheduling surgeries, that sort of thing. When it comes to AI for better patient care, which is what we usually think about, there are few legal, regulatory, and financial incentives to do so, and many disincentives. Still, there's been slow but steady integration of AI-based tools, often in the form of risk scoring and alert systems.

In the near future, two applications that I'm really excited about are triage in low-resource settings — having AIs do initial reads of pathology slides, for example, if there are not enough pathologists, or get an initial check of whether a mole looks suspicious — and ways in which AIs can help identify promising treatment options for discussion with a clinician team and patient.

Q: Any predictions for the next report?

I'll be keen to see where currently nascent AI regulation initiatives have gotten to. Accountability is such a difficult question in AI, it's tricky to nurture both innovation and basic protections. Perhaps the most important innovation will be in approaches for AI accountability.

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What’s next for quantum computing

Companies are moving away from setting qubit records in favor of practical hardware and long-term goals.

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This story is a part of MIT Technology Review’s What’s Next series , where we look across industries, trends, and technologies to give you a first look at the future

In 2023, progress in quantum computing will be defined less by big hardware announcements than by researchers consolidating years of hard work, getting chips to talk to one another, and shifting away from trying to make do with noise as the field gets ever more international in scope.

For years, quantum computing’s news cycle was dominated by headlines about record-setting systems. Researchers at Google and IBM have had spats over who achieved what—and whether it was worth the effort. But the time for arguing over who’s got the biggest processor seems to have passed: firms are heads-down and preparing for life in the real world. Suddenly, everyone is behaving like grown-ups.

As if to emphasize how much researchers want to get off the hype train, IBM is expected to announce a processor in 2023 that bucks the trend of putting ever more quantum bits, or “qubits,” into play. Qubits, the processing units of quantum computers, can be built from a variety of technologies, including superconducting circuitry, trapped ions, and photons, the quantum particles of light.

IBM has long pursued superconducting qubits, and over the years the company has been making steady progress in increasing the number it can pack on a chip. In 2021, for example, IBM unveiled one with a record-breaking 127 of them. In November, it debuted its 433-qubit Osprey processor , and the company aims to release a 1,121-qubit processor called Condor in 2023.

But this year IBM is also expected to debut its Heron processor, which will have just 133 qubits. It might look like a backwards step, but as the company is keen to point out, Heron’s qubits will be of the highest quality. And, crucially, each chip will be able to connect directly to other Heron processors, heralding a shift from single quantum computing chips toward “modular” quantum computers built from multiple processors connected together—a move that is expected to help quantum computers scale up significantly.

Heron is a signal of larger shifts in the quantum computing industry. Thanks to some recent breakthroughs, aggressive roadmapping, and high levels of funding, we may see general-purpose quantum computers earlier than many would have anticipated just a few years ago, some experts suggest. “Overall, things are certainly progressing at a rapid pace,” says Michele Mosca, deputy director of the Institute for Quantum Computing at the University of Waterloo.

Here are a few areas where experts expect to see progress.

Stringing quantum computers together

IBM’s Heron project is just a first step into the world of modular quantum computing. The chips will be connected with conventional electronics, so they will not be able to maintain the “quantumness” of information as it moves from processor to processor. But the hope is that such chips, ultimately linked together with quantum-friendly fiber-optic or microwave connections, will open the path toward distributed, large-scale quantum computers with as many as a million connected qubits. That may be how many are needed to run useful, error-corrected quantum algorithms. “We need technologies that scale both in size and in cost, so modularity is key,” says Jerry Chow, director at IBM Quantum Hardware System Development.

Other companies are beginning similar experiments. “Connecting stuff together is suddenly a big theme,” says Peter Shadbolt, chief scientific officer of PsiQuantum , which uses photons as its qubits. PsiQuantum is putting the finishing touches on a silicon-based modular chip. Shadbolt says the last piece it requires—an extremely fast, low-loss optical switch—will be fully demonstrated by the end of 2023. “That gives us a feature-complete chip,” he says. Then warehouse-scale construction can begin: “We’ll take all of the silicon chips that we’re making and assemble them together in what is going to be a building-scale, high-performance computer-like system.”

The desire to shuttle qubits among processors means that a somewhat neglected quantum technology will come to the fore now, according to Jack Hidary , CEO of SandboxAQ, a quantum technology company that was spun out of Alphabet last year . Quantum communications, where coherent qubits are transferred over distances as large as hundreds of kilometers, will be an essential part of the quantum computing story in 2023, he says.

“The only pathway to scale quantum computing is to create modules of a few thousand qubits and start linking them to get coherent linkage,” Hidary told MIT Technology Review. “That could be in the same room, but it could also be across campus, or across cities. We know the power of distributed computing from the classical world, but for quantum, we have to have coherent links: either a fiber-optic network with quantum repeaters, or some fiber that goes to a ground station and a satellite network.”

Many of these communication components have been demonstrated in recent years. In 2017, for example, China’s Micius satellite showed that coherent quantum communications could be accomplished between nodes separated by 1,200 kilometers. And in March 2022, an international group of academic and industrial researchers demonstrated a quantum repeater that effectively relayed quantum information over 600 kilometers of fiber optics.

Taking on the noise

At the same time that the industry is linking up qubits, it is also moving away from an idea that came into vogue in the last five years—that chips with just a few hundred qubits might be able to do useful computing, even though noise easily disrupts their operations.

This notion, called “noisy intermediate-scale quantum” (NISQ), would have been a way to see some short-term benefits from quantum computing, potentially years before reaching the ideal of large-scale quantum computers with many hundreds of thousands of qubits devoted to correcting errors. But optimism about NISQ seems to be fading. “The hope was that these computers could be used well before you did any error correction, but the emphasis is shifting away from that,” says Joe Fitzsimons, CEO of Singapore-based Horizon Quantum Computing.

Some companies are taking aim at the classic form of error correction, using some qubits to correct errors in others. Last year, both Google Quantum AI and Quantinuum , a new company formed by Honeywell and Cambridge Quantum Computing, issued papers demonstrating that qubits can be assembled into error-correcting ensembles that outperform the underlying physical qubits.

Other teams are trying to see if they can find a way to make quantum computers “fault tolerant” without as much overhead. IBM, for example, has been exploring characterizing the error-inducing noise in its machines and then programming in a way to subtract it (similar to what noise-canceling headphones do). It’s far from a perfect system—the algorithm works from a prediction of the noise that is likely to occur, not what actually shows up. But it does a decent job, Chow says: “We can build an error-correcting code, with a much lower resource cost, that makes error correction approachable in the near term.”

Maryland-based IonQ , which is building trapped-ion quantum computers, is doing something similar. “The majority of our errors are imposed by us as we poke at the ions and run programs,” says Chris Monroe, chief scientist at IonQ. “That noise is knowable, and different types of mitigation have allowed us to really push our numbers."

Getting serious about software

For all the hardware progress, many researchers feel that more attention needs to be given to programming. “Our toolbox is definitely limited, compared to what we need to have 10 years down the road,” says Michal Stechly of Zapata Computing , a quantum software company based in Boston.

The way code runs on a cloud-accessible quantum computer is generally “circuit-based,” which means the data is put through a specific, predefined series of quantum operations before a final quantum measurement is made, giving the output. That’s problematic for algorithm designers, Fitzsimons says. Conventional programming routines tend to involve looping some steps until a desired output is reached, and then moving into another subroutine. In circuit-based quantum computing, getting an output generally ends the computation: there is no option for going round again.

Horizon Quantum Computing is one of the companies that have been building programming tools to allow these flexible computation routines. “That gets you to a different regime in terms of the kinds of things you’re able to run, and we’ll start rolling out early access in the coming year,” Fitzsimons says.

Helsinki-based Algorithmiq is also innovating in the programming space. “We need nonstandard frameworks to program current quantum devices,” says CEO Sabrina Maniscalco. Algorithmiq’s newly launched drug discovery platform, Aurora, combines the results of a quantum computation with classical algorithms. Such “hybrid” quantum computing is a growing area, and it’s widely acknowledged as the way the field is likely to function in the long term. The company says it expects to achieve a useful quantum advantage—a demonstration that a quantum system can outperform a classical computer on real-world, relevant calculations—in 2023.

Competition around the world

Change is likely coming on the policy front as well. Government representatives including Alan Estevez, US undersecretary of commerce for industry and security, have hinted that trade restrictions surrounding quantum technologies are coming.

Tony Uttley, COO of Quantinuum, says that he is in active dialogue with the US government about making sure this doesn’t adversely affect what is still a young industry. “About 80% of our system is components or subsystems that we buy from outside the US,” he says. “Putting a control on them doesn’t help, and we don’t want to put ourselves at a disadvantage when competing with other companies in other countries around the world.”

And there are plenty of competitors. Last year, the Chinese search company Baidu opened access to a 10-superconducting-qubit processor that it hopes will help researchers make forays into applying quantum computing to fields such as materials design and pharmaceutical development. The company says it has recently completed the design of a 36-qubit superconducting quantum chip. “Baidu will continue to make breakthroughs in integrating quantum software and hardware and facilitate the industrialization of quantum computing,” a spokesman for the company told MIT Technology Review. The tech giant Alibaba also has researchers working on quantum computing with superconducting qubits.

In Japan, Fujitsu is working with the Riken research institute to offer companies access to the country’s first home-grown quantum computer in the fiscal year starting April 2023. It will have 64 superconducting qubits. “The initial focus will be on applications for materials development, drug discovery, and finance,” says Shintaro Sato, head of the quantum laboratory at Fujitsu Research.

Not everyone is following the well-trodden superconducting path, however. In 2020, the Indian government pledged to spend 80 billion rupees ($1.12 billion when the announcement was made) on quantum technologies. A good chunk will go to photonics technologies—for satellite-based quantum communications, and for innovative “qudit” photonics computing.

Qudits expand the data encoding scope of qubits—they offer three, four, or more dimensions, as opposed to just the traditional binary 0 and 1, without necessarily increasing the scope for errors to arise. “This is the kind of work that will allow us to create a niche, rather than competing with what has already been going on for several decades elsewhere,” says Urbasi Sinha, who heads the quantum information and computing laboratory at the Raman Research Institute in Bangalore, India.

Though things are getting serious and internationally competitive, quantum technology remains largely collaborative—for now. “The nice thing about this field is that competition is fierce, but we all recognize that it’s necessary,” Monroe says. “We don’t have a zero-sum-game mentality: there are different technologies out there, at different levels of maturity, and we all play together right now. At some point there’s going to be some kind of consolidation, but not yet.”

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Computer Science Essay Examples

Explore 15+ Brilliant Computer Science Essay Examples: Tips Included

Published on: May 5, 2023

Last updated on: Jan 30, 2024

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Do you struggle with writing computer science essays that get you the grades you deserve?

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Crafting a top-notch essay can be a daunting task, but it's crucial to your success in the field of computer science.

For that, CollegeEssay.org has a solution for you!

In this comprehensive guide, we'll provide you with inspiring examples of computer science essays. You'll learn everything you need to know to write effective and compelling essays that impress your professors and get you the grades you deserve.

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Computer Science Essays: Understanding the Basics

A computer science essay is a piece of writing that explores a topic related to computer science. It may take different forms, such as an argumentative essay, a research paper, a case study, or a reflection paper.

Just like any other essay, it should be well-researched, clear, concise, and effectively communicate the writer's ideas and arguments.

Computer essay examples encompass a wide range of topics and types, providing students with a diverse set of writing opportunities.

Here, we will explore some common types of computer science essays:

Middle School Computer Science Essay Example

College Essay Example Computer Science

University Computer Science Essay Example

Computer Science Extended Essay Example

Uiuc Computer Science Essay Example [

Computer Science Essay Examples For Different Fields

Computer science is a broad field that encompasses many different areas of study. For that, given below are some examples of computer science essays for some of the most popular fields within the discipline.

By exploring these examples, you can gain insight into the different types of essays within this field.

College Application Essay Examples Computer Science

The Future of Computers Technology

Historical Development of Computer Science

Young Children and Technology: Building Computer Literacy

Computer Science And Artificial Intelligence

Looking for more examples of computer science essays? Given below are some additional examples of computer science essays for readers to explore and gain further inspiration from.

Computer Science â My Choice for Future Career

My Motivation to Pursue Undergraduate Studies in Computer Engineering

Abstract Computer Science

Computer Science Personal Statement Example

Sop For Computer Science

Computer Science Essay Topics

There are countless computer science essay topics to choose from, so it can be challenging to narrow down your options.

However, the key is to choose a topic that you are passionate about and that aligns with your assignment requirements.

Here are ten examples of computer science essay topics to get you started:

The impact of artificial intelligence on society: benefits and drawbacks
Cybersecurity measures in cloud computing systems
The Ethics of big data: privacy, bias, and Transparency
The future of quantum computing: possibilities and challenges
The Role of computer hardware in Healthcare: current applications and potential innovations
Programming languages: a comparative analysis of their strengths and weaknesses
The use of machine learning in predicting human behavior
The challenges and solutions for developing secure and reliable software
The Role of blockchain technology in improving supply chain management
The use of data analytics in business decision-making.

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Tips to Write an Effective Computer Science Essay

Writing an effective computer science essay requires a combination of technical expertise and strong writing skills. Here are some tips to help you craft a compelling and well-written essay:

Understand the Requirements: Make sure you understand the assignment requirements, including the essay type, format, and length.

Choose a Topic: Select a topic that you are passionate about and that aligns with your assignment requirements.
Create an Outline: Develop a clear and organized outline that highlights the main points and subtopics of your essay.
Use Appropriate Language and Tone: Use technical terms and language when appropriate. But ensure your writing is clear, concise, and accessible to your target audience.
Provide Evidence: Use relevant and credible evidence to support your claims, and ensure you cite your sources correctly.
Edit and Proofread Your Essay: Review your essay for clarity, coherence, and accuracy. Check for grammatical errors, spelling mistakes, and formatting issues.

By following these tips, you can improve the quality of your computer science essay and increase your chances of success.

In conclusion, writing a computer science essay can be a challenging yet rewarding experience.

It allows you to showcase your knowledge and skills within the field and develop your writing and critical thinking abilities. By following the examples provided in this blog, you can create an effective computer science essay, which will meet your requirements.

If you find yourself struggling with the writing process, consider seeking essay writing help online from CollegeEssay.org.

Our AI essay writer can provide guidance and support in crafting a top-notch computer science essay.

So, what are you waiting for? Hire our computer science essay writing service today!

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Home — Essay Samples — Information Science and Technology — Computer Science — The Future of Computers Technology

The Future of Computers Technology

Categories: Computer Science Impact of Technology

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Eric G. Swedin and David L. Computers: The Life Story Of Technology. Hardcover - Illustrated, 30 April 2005.
Ron White. How Computers Work: Que Pub; 9th edition (November 1, 2007).
New York Times; Sunday, 24 October 2010.
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Computer Technology: Evolution and Developments Essay

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Evolution of Computers and their Technology

Uses of computers, advantages of computers and their technology, disadvantages of computers and computer technology, trends in computer technology, works cited.

The development of computer technology is characterized by the change in the technology used in building the devices. The evolution of computer technology is divided into several generations, from mechanical devices, followed by analog devices, to the recent digital computers that now dominate the world. This paper examines the evolution of computers and their technology, their use in the early and modern periods, their merits and demerits, and future developments.

Mechanical Age (1800s -1920s)

The development of the computer characterized this period to facilitate mathematical calculations that could not be done manually by individuals. The first notable computing device was the “analytical engine” designed by Charles Babbage in 1834, which used electromechanical relays to function (Zakari 1). The mechanical era saw improvements made to the first design by Babbage until the first generation era.

First Generation (the 1930s-1950s)

The first generation era is characterized by the development of three electronic computers that used vacuum tubes, unlike the previous devices that used electromechanical relays to perform their tasks (Enzo 4). In this period, the machines were capable of storing data in the form of instructions written manually by the programmers and installed into the device (Zakari 1). The devices developed in this period were primarily used in applied science and engineering to facilitate solving evaluations.

Second Generation (Mid-1950s-Early 1960s)

The second-generation period saw the development of many design areas; there was development in the technology used and the programming language used to write the commands. Unlike in the previous generations, the operations in this era were performed in the hardware (McAfee 141). The period saw the development of the index registers used for numerous operations.

Third Generation (the Early 1960s – Early1970s)

The era saw improvement in the technology used in designing the devices; integrated circuits in computer devices were introduced. The period saw the introduction of the microprogramming technique and the development of the operation system (Zakari, 1). The speed of functioning of the devices designed in this period was faster than in the previous eras, and the computers could perform more functions.

Fourth Generation (The early 1970s – Mid 1980s)

This Generation saw the development in the use of large-scale integration in the computers developed. The size of the microchips was the information for the computers was stored was reduced to allow for data to be stored in the same microchip (Zakari 1). The devices were installed with semiconductors memories to replace the core memories of the previous era. The processors were designed with high speed to allow faster processing speed of operations in the devices (McAfee 141).

Fifth Generation (the Mid 1980s- Early 1990s)

The machines/ devices designed had many processors that worked simultaneously on a single program (Zakari1). The semiconductors in the computers were improved to increase the scale of operation with the development of chips (Enzo 2). In this period, the computer devices developed were capable of performing parallel processing of commands. Which improved their functionality?

Sixth Generation (1990 to Date)

The era is characterized by improvements in all the areas of designing computers. There is a reduction in the size of the devices developed with increased portability of the machines. The era has seen the development of computers to interact more with people and facilitate human functions in society, with an increase in connection due to improved network development linking computers (Zachari 1).

The early computers were mainly used to accomplish mathematical functions in applied science and engineering. These machines were primarily used to solve mathematical calculation problems (Zakari 1). The second-generation devices improved on their functionality and were capable of processing information stored in them by the programmer (Zakari 1). Today, individuals use computers to perform various functions, including facilitating communication, storing data, and processing information for individuals. The use of computer technology is now in every section of the world; people in different areas are using computers to perform numerous functions (McAfee 141). The technology is directly applied in agriculture, health and medicine, education and transport, communication, and other regions.

Computer technology has enabled the development of devices like mobile phones that are easy to use and effective, allowing individuals to keep in contact with one another even when at different locations (Golosova and Romanovs 3). Computer technology has improved manufacturing; producing goods is now better and more efficient due to the development of technology that enhances individuals’ performance. Computer technology enhances the development of better healthcare operations by facilitating functions in health. Computer technology also enhances learning as individuals can get the required learning material (Golosova and Romanovs 6). Computers and computer technology improve teacher-student interaction during education by providing a medium that can facilitate lessons.

Computers are hazardous to human health; when used excessively, individuals suffer from health issues like eye problems resulting from extreme exposure to the screen light. Also, sitting for an extended period affects an individual’s health (Golosova and Romanovs 14). Computers and computer technology are artificial, making them susceptible to human manipulation; humans are exposed to risks from those that can harm them by manipulating information (Suma 133). Computers also impact the environment negatively due to the carbon footprint left in the environment when they become obsolete because people can no longer use them.

There is an expected increase in the use of artificial intelligence among people with increased developments in computers and their technology (McAfee 141). Computer technology is expected to increase the automation of processes and functci0ons previously done by humans in society. Computer technology is expected to increase the virtual reality and augmented reality among individuals in society to improve the human experience.

Enzo, Albert, Charles O. Connors, and Walter Curtis. “The Evolution of Computer Science.” Computer Science, Murdoch University, Australia. Web.

McAfee, Andrew. “Mastering the Three Worlds of Information Technology.” Harvard Business Review. vol. 84, no. 11, 2006, p. 141. Web.

Suma. V. “Computer Vision for Humans-machines Interaction-review.” Journal of Trends in Computer Science and Smart Technology ( TCSST ), vol. 1, no. 2, 2019, pp. 131-139. Web.

Golosova, Julija, and Andrejs Romanovs. “The Advantages and Disadvantages of the Blockchain Technology.” 2018 IEEE 6th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) . Web.

Zakari, Ishaq “History of Computers and its Generations.” Umaru Musa Yar’adua University, Katsina State (2019). Web.

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Essay on Computer and its Uses for School Students and Children

500+ words essay on computer.

In this essay on computer, we are going to discuss some useful things about computers. The modern-day computer has become an important part of our daily life. Also, their usage has increased much fold during the last decade. Nowadays, they use the computer in every office whether private or government. Mankind is using computers for over many decades now. Also, they are used in many fields like agriculture, designing, machinery making, defense and many more. Above all, they have revolutionized the whole world.

History of Computers

It is very difficult to find the exact origin of computers. But according to some experts computer exists at the time of world war-II. Also, at that time they were used for keeping data. But, it was for only government use and not for public use. Above all, in the beginning, the computer was a very large and heavy machine.

Working of a Computer

The computer runs on a three-step cycle namely input, process, and output. Also, the computer follows this cycle in every process it was asked to do. In simple words, the process can be explained in this way. The data which we feed into the computer is input, the work CPU do is process and the result which the computer give is output.

Components and Types of Computer

The simple computer basically consists of CPU, monitor, mouse, and keyboard . Also, there are hundreds of other computer parts that can be attached to it. These other parts include a printer, laser pen, scanner , etc.

The computer is categorized into many different types like supercomputers, mainframes, personal computers (desktop), PDAs, laptop, etc. The mobile phone is also a type of computer because it fulfills all the criteria of being a computer.

Get the huge list of more than 500 Essay Topics and Ideas

Uses of Computer in Various Fields

As the usage of computer increased it became a necessity for almost every field to use computers for their operations. Also, they have made working and sorting things easier. Below we are mentioning some of the important fields that use a computer in their daily operation.

Medical Field

They use computers to diagnose diseases, run tests and for finding the cure for deadly diseases . Also, they are able to find a cure for many diseases because of computers.

Whether it’s scientific research, space research or any social research computers help in all of them. Also, due to them, we are able to keep a check on the environment , space, and society. Space research helped us to explore the galaxies. While scientific research has helped us to locate resources and various other useful resources from the earth.

For any country, his defence is most important for the safety and security of its people. Also, computer in this field helps the country’s security agencies to detect a threat which can be harmful in the future. Above all the defense industry use them to keep surveillance on our enemy.

Threats from a Computer

Computers have become a necessity also, they have become a threat too. This is due to hackers who steal your private data and leak them on internet. Also, anyone can access this data. Apart from that, there are other threats like viruses, spams, bug and many other problems.

The computer is a very important machine that has become a useful part of our life. Also, the computers have twin-faces on one side it’s a boon and on the other side, it’s a bane. Its uses completely depend upon you. Apart from that, a day in the future will come when human civilization won’t be able to survive without computers as we depend on them too much. Till now it is a great discovery of mankind that has helped in saving thousands and millions of lives.

Frequently Asked Questions on Computer

Q.1 What is a computer?

A.1 A computer is an electronic device or machine that makes our work easier. Also, they help us in many ways.

Q.2 Mention various fields where computers are used?

A.2 Computers are majorly used in defense, medicine, and for research purposes.

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How to Write the “Why Computer Science?” Essay

What’s covered:, what is the purpose of the “why computer science” essay, elements of a good computer science essay, computer science essay example, where to get your essay edited.

You will encounter many essay prompts as you start applying to schools, but if you are intent on majoring in computer science or a related field, you will come across the “ Why Computer Science? ” essay archetype. It’s important that you know the importance behind this prompt and what constitutes a good response in order to make your essay stand out.

For more information on writing essays, check out CollegeVine’s extensive essay guides that include everything from general tips, to essay examples, to essay breakdowns that will help you write the essays for over 100 schools.

Colleges ask you to write a “ Why Computer Science? ” essay so you may communicate your passion for computer science, and demonstrate how it aligns with your personal and professional goals. Admissions committees want to see that you have a deep interest and commitment to the field, and that you have a vision for how a degree in computer science will propel your future aspirations.

The essay provides an opportunity to distinguish yourself from other applicants. It’s your chance to showcase your understanding of the discipline, your experiences that sparked or deepened your interest in the field, and your ambitions for future study and career. You can detail how a computer science degree will equip you with the skills and knowledge you need to make a meaningful contribution in this rapidly evolving field.

A well-crafted “ Why Computer Science? ” essay not only convinces the admissions committee of your enthusiasm and commitment to computer science, but also provides a glimpse of your ability to think critically, solve problems, and communicate effectively—essential skills for a computer scientist.

The essay also gives you an opportunity to demonstrate your understanding of the specific computer science program at the college or university you are applying to. You can discuss how the program’s resources, faculty, curriculum, and culture align with your academic interests and career goals. A strong “ Why Computer Science? ” essay shows that you have done your research, and that you are applying to the program not just because you want to study computer science, but because you believe that this particular program is the best fit for you.

Writing an effective “ Why Computer Science ?” essay often requires a blend of two popular college essay archetypes: “ Why This Major? ” and “ Why This College? “.

Explain “Why This Major?”

The “ Why This Major? ” essay is an opportunity for you to dig deep into your motivations and passions for studying Computer Science. It’s about sharing your ‘origin story’ of how your interest in Computer Science took root and blossomed. This part of your essay could recount an early experience with coding, a compelling Computer Science class you took, or a personal project that sparked your fascination.

What was the journey that led you to this major? Was it a particular incident, or did your interest evolve over time? Did you participate in related activities, like coding clubs, online courses, hackathons, or internships?

Importantly, this essay should also shed light on your future aspirations. How does your interest in Computer Science connect to your career goals? What kind of problems do you hope to solve with your degree?

The key for a strong “ Why This Major? ” essay is to make the reader understand your connection to the subject. This is done through explaining your fascination and love for computer science. What emotions do you feel when you are coding? How does it make you feel when you figure out the solution after hours of trying? What aspects of your personality shine when you are coding?

By addressing these questions, you can effectively demonstrate a deep, personal, and genuine connection with the major.

Emphasize “Why This College?”

The “ Why This College? ” component of the essay demonstrates your understanding of the specific university and its Computer Science program. This is where you show that you’ve done your homework about the college, and you know what resources it has to support your academic journey.

What unique opportunities does the university offer for Computer Science students? Are there particular courses, professors, research opportunities, or clubs that align with your interests? Perhaps there’s a study abroad program or an industry partnership that could give you a unique learning experience. Maybe the university has a particular teaching methodology that resonates with you.

Also, think about the larger university community. What aspects of the campus culture, community, location, or extracurricular opportunities enhance your interest in this college? Remember, this is not about general praises but about specific features that align with your goals. How will these resources and opportunities help you explore your interests further and achieve your career goals? How does the university’s vision and mission resonate with your own values and career aspirations?

It’s important when discussing the school’s resources that you always draw a connection between the opportunity and yourself. For example, don’t tell us you want to work with X professor because of their work pioneering regenerative AI. Go a step further and say because of your goal to develop AI surgeons for remote communities, learning how to strengthen AI feedback loops from X professor would bring you one step closer to achieving your dream.

By articulating your thoughts on these aspects, you demonstrate a strong alignment between the college and your academic goals, enhancing your appeal as a prospective student.

Demonstrate a Deep Understanding of Computer Science

As with a traditional “ Why This Major? ” essay, you must exhibit a deep and clear understanding of computer science. Discuss specific areas within the field that pique your interest and why. This could range from artificial intelligence to software development, or from data science to cybersecurity.

What’s important is to not just boast and say “ I have a strong grasp on cybersecurity ”, but instead use your knowledge to show your readers your passion: “ After being bombarded with cyber attack after cyber attack, I explained to my grandparents the concept of end-to-end encryption and how phishing was not the same as a peaceful afternoon on a lake. ”

Make it Fun!

Students make the mistake of thinking their college essays have to be serious and hyper-professional. While you don’t want to be throwing around slang and want to present yourself in a positive light, you shouldn’t feel like you’re not allowed to have fun with your essay. Let your personality shine and crack a few jokes.

You can, and should, also get creative with your essay. A great way to do this in a computer science essay is to incorporate lines of code or write the essay like you are writing out code.

Now we will go over a real “ Why Computer Science? ” essay a student submitted and explore what the essay did well, and where there is room for improvement.

Please note: Looking at examples of real essays students have submitted to colleges can be very beneficial to get inspiration for your essays. You should never copy or plagiarize from these examples when writing your own essays. Colleges can tell when an essay isn’t genuine and will not view students favorably if they plagiarized.

I held my breath and hit RUN. Yes! A plump white cat jumped out and began to catch the falling pizzas. Although my Fat Cat project seems simple now, it was the beginning of an enthusiastic passion for computer science. Four years and thousands of hours of programming later, that passion has grown into an intense desire to explore how computer science can serve society. Every day, surrounded by technology that can recognize my face and recommend scarily-specific ads, I’m reminded of Uncle Ben’s advice to a young Spiderman: “with great power comes great responsibility”. Likewise, the need to ensure digital equality has skyrocketed with AI’s far-reaching presence in society; and I believe that digital fairness starts with equality in education.

The unique use of threads at the College of Computing perfectly matches my interests in AI and its potential use in education; the path of combined threads on Intelligence and People gives me the rare opportunity to delve deep into both areas. I’m particularly intrigued by the rich sets of both knowledge-based and data-driven intelligence courses, as I believe AI should not only show correlation of events, but also provide insight for why they occur.

In my four years as an enthusiastic online English tutor, I’ve worked hard to help students overcome both financial and technological obstacles in hopes of bringing quality education to people from diverse backgrounds. For this reason, I’m extremely excited by the many courses in the People thread that focus on education and human-centered technology. I’d love to explore how to integrate AI technology into the teaching process to make education more available, affordable, and effective for people everywhere. And with the innumerable opportunities that Georgia Tech has to offer, I know that I will be able to go further here than anywhere else.

What the Essay Did Well

This essay perfectly accomplishes the two key parts of a “ Why Computer Science? ” essay: answering “ Why This Major? ” and “ Why This College? ”. Not to mention, we get a lot of insight into this student and what they care about beyond computer science, and a fun hook at the beginning.

Starting with the “ Why This Major? ” aspect of the response, this essay demonstrates what got the student into computer science, why they are passionate about the subject, and what their goals are. They show us their introduction to the world of CS with an engaging hook: “I held my breath and hit RUN. Yes! A plump white cat jumped out and began to catch the falling pizzas. ” We then see this is a core passion because they spent “ Four years and thousands of hours ,” coding.

The student shows us why they care about AI with the sentence, “ Every day, surrounded by technology that can recognize my face and recommend scarily-specific ads ,” which makes the topic personal by demonstrating their fear at AI’s capabilities. But, rather than let panic overwhelm them, the student calls upon Spiderman and tells us their goal of establishing digital equality through education. This provides a great basis for the rest of the essay, as it thoroughly explains the students motivations and goals, and demonstrates their appreciation for interdisciplinary topics.

Then, the essay shifts into answering “ Why This College? ”, which it does very well by honing in on a unique facet of Georgia Tech’s College of Computing: threads. This is a great example of how to provide depth to the school resources you mention. The student describes the two threads and not only why the combination is important to them, but how their previous experiences (i.e. online English tutor) correlate to the values of the thread: “ For this reason, I’m extremely excited by the many courses in the People thread that focus on education and human-centered technology. ”

What Could Be Improved

This essay does a good job covering the basics of the prompt, but it could be elevated with more nuance and detail. The biggest thing missing from this essay is a strong core to tie everything together. What do we mean by that? We want to see a common theme, anecdote, or motivation that is weaved throughout the entire essay to connect everything. Take the Spiderman quote for example. If this was expanded, it could have been the perfect core for this essay.

Underlying this student’s interest in AI is a passion for social justice, so they could have used the quote about power and responsibility to talk about existing injustices with AI and how once they have the power to create AI they will act responsibly and help affected communities. They are clearly passionate about equality of education, but there is a disconnect between education and AI that comes from a lack of detail. To strengthen the core of the essay, this student needs to include real-world examples of how AI is fostering inequities in education. This takes their essay from theoretical to practical.

Whether you’re a seasoned writer or a novice trying your hand at college application essays, the review and editing process is crucial. A fresh set of eyes can provide valuable insights into the clarity, coherence, and impact of your writing. Our free Peer Essay Review tool offers a unique platform to get your essay reviewed by another student. Peer reviews can often uncover gaps, provide new insights or enhance the clarity of your essay, making your arguments more compelling. The best part? You can return the favor by reviewing other students’ essays, which is a great way to hone your own writing and critical thinking skills.

For a more professional touch, consider getting your essay reviewed by a college admissions expert . CollegeVine advisors have years of experience helping students refine their writing and successfully apply to top-tier schools. They can provide specific advice on how to showcase your strengths, address any weaknesses, and generally present yourself in the best possible light.

Kamala Harris & The Future of America: An Essay in Three Parts

By Caleb Maupin

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The Future of Design in Technology

How will technology continue to affect our role as designers? We interviewed two faculty in the College of Design to explore technology’s role as it relates to ideation, human-machine teaming and the impacts on our rights and resources.

Is AI here to take over our jobs? We asked two faculty in the College of Design to explore the future of design within the realm of technology, and delve into some of the pros and cons of redefining their work with this endlessly-transforming industry.

While the nature of design has always been to explore, question, ideate, iterate, prototype, test and test again, newly emerging technologies related to Artificial Intelligence (AI) have the potential to disrupt our current cycles of work and propose new roles for a future generation of students.

Helen Armstrong, a professor of graphic & experience design and director of graduate programs, has been researching in this space since 2015. One of the ways she’s preparing students at both the undergraduate and graduate level for this shift is to encourage students to continue to view their work as part of a larger system, rather than a one-off solution. “When you design, you’re not designing something that finishes the moment your work is done,” she says. “The interfaces we’re designing today have to be able to interact with a whole ecosystem of other products within a spectrum of environments. These interfaces also have to anticipate and respond to user needs—before humans make requests. We are entering an era of anticipatory design. For example, a few years ago our students worked with an auto parts company to integrate AI into their retail spaces. One of the solutions was an anticipatory maintenance application that identified customer vehicles and then enabled the sales team’s members to predict not only current maintenance needs but also near future and far future needs.

Exploring user interface (UI) and user experience (UX) design means students must consider the end user of a product and consider the ways in which that user might interact with a product – whether that’s the interface you use to access your mobile banking or the notification you receive from your fridge, reminding you to buy milk. Each of these elements can talk to one another and respond to human needs, and there’s an inherent agreement of trust that humans place in the systems.

“Our research has found that people tend to begin by over-trusting autonomous systems, but if they disagree with the system’s prediction, then that trust begins to erode very quickly,” Armstrong says. So how can designers design the system to create a bit of skepticism and teach users more about how the machine might be making its prediction?

Our research has found that people tend to begin by over-trusting autonomous systems, but if they disagree with the system’s prediction, then that trust begins to erode very quickly.

A lot of that connection boils down to an ever-increasing need to understand data and being able to consider the larger implications of working with tools with a vast resource of computing power.

Shawn Protz, a professor of architecture and digital technology, compares the addition of AI to that of the practice of hand-drafting before programs like AutoCAD took over. “I understand that shift in process affected the outcomes in how we make architecture – moving from hand-drafting to the computer,” he says. “The computer was always part of my education – we used hand-drafting to learn how to move from 2D to 3D, but I don’t think it’s changed anything. The advances in BIM (building information modeling) garnered a lot of hype in the beginning, but now it’s just normal expected use. It was hyped as something new, but it was really just an extension of what we’d always been doing in architecture. We’ve been using abstractions like plans and sections to understand the complex spatial design, but it gave us the superpower of coordinating the way we draw and the way we think in three dimensions. I certainly had to learn some new software features, but everything just feels like an extension of what we’ve been trying to do this whole time. Even AI – I don’t see it as radically changing we’ve already been doing for centuries.”

With the addition of AI, students and professionals will be able to redefine what it means to iterate on a design or a series of designs. Protz sees it as a way to augment work processes, rather than removing part of the role. During a recent lecture at the College of Design, David Benjamin, founding principal at The Living and associate professor at Columbia’s GSAPP, shared his workflow of using machine learning in Grasshopper 3D to refine ideas and further his creative practice. “Benjamin sets up parameters and generates preliminary floor plans and can then work with his client to explore possibilities. So the work isn’t designing for you, but it’s allowing you to see what’s unexpected, what’s missing, and is another voice or agent, rather than something that might be replacing you,” Protz says.

This use of AI as an early idea generator in which the designer refines the final product is just one option for enhancing our current workflows. While AI helps us grasp complexity and can augment the creative process, it has the potential for unwanted consequences as well. “We need to be considering what human skills we’re automating away vs. what skills we could be shoring up through these systems,” says Armstrong. “Think about the GPS system in your car – its goal is to help you navigate from point A to point B. Often, this is great, but, sometimes, you would prefer the system to teach you how to better navigate between spaces yourself. Recently I worked on a project with Dr. Matthew Peterson in which we were thinking about this concept in relation to human memory. We worked with the NC State Laboratory for Analytic Sciences to consider how generative AI might be used to help an intelligence analyst capture and remember vital information. We weren’t using AI to replace human memory but rather leveraging the technology to increase analysts’ natural memory capacities. Each time designers create an interface today, they make choices around automation that can either bypass certain human skills or team up with AI to expand those skills. That’s a very powerful position and a very heavy responsibility for designers right now,” she adds. While the question of automation and future human abilities is one of the concerns for AI, another deals with the larger unexpected ramifications of this technology. Issues of bias, misuse of data and even intense usage of the earth’s natural resources all have implications in this field.

Armstrong sees her role as encouraging students to question their influence on the future of society. “I always tell my grad students – this is such a great time to be a student. We’re in the midst of figuring out what roles these systems can play in our future, and determining how we can build systems that support the future we want to live in,” she says.

Both she and Protz point to guiding resources that are keeping a watchful eye on the future of this technology. Guiding principles such as the AI Bill of Rights and advocates such as the AI Now Institute continue to bring meaningful discourse and governance to this topic. President Biden has recognized the potential impact unchecked technology advances could have on civil rights and democratic values, foundational principles to the United States of America. Based on this charge, the White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. The Blueprint for an AI Bill of Rights is a guide for a society that protects all people from these threats—and uses technologies in ways that reinforce our highest values.” 1

Armstrong encourages each of her students to read this document, and to think of it as a design brief. “Every paragraph is something that designers could be thinking about and working on right now,” she says. She gives an example from the section on Notice and Explanation, which focuses on letting end users know that they may be impacted by the systems they use. It’s a design question – how do designers develop UX/UI designs that can meet the expectations outlined in the AI Bill of Rights?

Protz is also exploring the ethical implications of some of these technologies, especially taking into consideration those that wield the power behind these mighty datasets. While guiding principles such as the AI Bill of Rights encourage the Notice and Explanation of the ways in which your data can be used, advocates such as the AI Now Institute point to the failure of big tech corporations to adhere to these “data minimization” models of accountability. 2 “This brings up all kinds of issues around privacy and bias that students need to be critically engaging with,” adds Armstrong.

Exploring some of these larger societal problems may be beyond the scope of architects, but there is more the profession could be doing to consider the ethical implications and the use of these tools when it comes to professional practice. Similar to considering the ways in which the built environment affects our climate and landscape, we should also consider the intense energy usage and water consumption 3 that the data centers powering artificial intelligence need to churn out endless iterations for designs and visualizations.

Consistently pushing his students to be critical thinkers is part of Protz’ role as a professor. “I try to emphasize that all of these tools have a lineage and are part of a continuum of thinking,” he says.

“Think about what the tool allows you to do, what it limits you from doing, and what opportunities or frictions does that create?” He feels that a large part of his role in the college is embracing and questioning new digital tools, being willing to try every new thing that comes out, and “just play around with it.”

Armstrong feels that some of the shifts into more reliance on AI will be so subtle to become invisible. “These capabilities are being unbundled and put into existing technologies. So it’s not like you go pick a special generative tool to get the output you want – they are being seamlessly incorporated into products so that we barely even know it’s happening.”

Understanding that these systems are predictive and do not have a true sense of truth or meaning is something Armstrong underscores as important to this work. Having a healthy dose of skepticism as we continue to work with these tools encourages us to be aware of both their immense potential and their limitations.

That hearkens back to Protz’s goal to help students become critical thinkers. The College of Design is positioning its graduates to not only work with and explore the boundaries of new technologies such as AI, but to also step back and assess the roles in which these technologies have the power to shape our lives.

Both see AI as a huge shift in the means by which our work moves forward, with Armstrong likening the emergence of AI to the early days of the internet. The influence on the dissemination and processing of knowledge is profound, as is the ability to propagate false knowledge. Navigating that balance continues to be a space that designers can have influence on in the future.

“As long as humans are part of the equation, designers will be needed. Machines cannot truly understand the human experience. Moving forward, we need to be designing interfaces that enable humans and machines to work together to engage thoughtfully with the strengths of both,” says Armstrong. “This space is only going to be more important as we move forward.”

This article first appeared in the May 2024 issue of Designlife magazine. Explore other articles from this issue .

Student Predictions

What future challenges do you think will affect your generation of designers?

“I think that designers are going to have to think about bigger problems. We’ll have to do more design thinking around systems that we didn’t think of as traditional design.” – Ellis

Story Contributors

Helen Armstrong is the director of the master’s in graphic & experience design (MGXD) program and professor of graphic & experience design at NC State. Her research focuses on digital rights, human-machine teaming and accessible design. Her research partners have included IBM, Redhat, REI, Advance Auto Parts, SAS Analytics, Sealed Air and the Laboratory for Analytic Sciences.

Shawn Protz is an assistant professor of architecture and digital technology. He has explored a range of subjects spanning from structural and environmental systems to digital representation and fabrication; past classes have covered design communication, building information modeling, climatic design, housing, inflatable architecture and tectonics. At NC State, Protz focuses on building a vibrant digital culture and developing coursework and research projects that explore emerging digital systems and materials.

Author: Christine Klocke is the director of communications and marketing at NC State University’s College of Design. She is a graduate of the University of North Carolina at Chapel Hill’s Hussman School of Journalism and Media.

“ Blueprint for an AI Bill of Rights. ” The White House, Office of Science and Technology Policy n.d.
“ Data Minimization as a Tool for AI Accountability. ” AI Now Institute, 2023. April 11.
“ The Climate Costs of Big Tech .” AI Now Institute, 2023. April 11.
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Designlife Magazine 2024
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College of design students and faculty win awards at ncasla, madtech department head derek ham accepts new position as director of carnegie mellon university's entertainment technology center, freedom by design celebrates with custom-designed outdoor learning center.

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Best Tablets For Students To Study Long Into The Night

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While students need a wide variety of applications to complete their education, a tablet can bring an extra level of versatility to read ebooks, take notes and multitask during long study sessions. The best tablets for students can be a great supplementary piece to a companion laptop, or in the case of our top pick—the Apple iPad Pro M4 —it can be a computer all its own.

The best tablets for students can be used alongside a laptop or on their own.

But we’ve also got great options from Android, Chrome and Windows, too. The best Android tablet for students, the Samsung Galaxy Tab S9 Ultra , can keep you fully integrated into the Samsung ecosystem. For those that want a powerful machine with Copilot, the Microsoft Surface 11 ticks those boxes. There are more options, too. Here are the best tablets for students in 2024.

Best Tablet For Students Overall: Apple iPad Pro M4
Best Budget Tablet For Students: Amazon Fire Max 11
Best Apple Tablet For Students: Apple iPad Air
Best Android Tablet For Students: Samsung Galaxy Tab S9 Ultra
Best Windows Tablet For Students: Microsoft Surface Pro Copilot+ PC (11th Edition)
Best E-Ink Tablet For Students: Amazon Kindle Scribe

Best Tablet For Students Overall

Seamless integration with your laptop, earbuds and more, apple ipad pro m4.

Adam has been a leader in the tech media field for over a decade, with bylines at a number of different publications. When he's not hosting the Benefit of the Doud podcast, he's busy getting his hands on as many phones, tablets and laptops as possible. He regularly uses both iOS and Android (six-month rotation for each), and he fully embraces technology. He hasn't carried cash money since 2018, and pays for everything with his phone wherever possible.

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Best for: Enjoying a fully integrated ecosystem

Powerful M4 processor
Gorgeous OLED display
Seamless integration with other Apple products
Keyboard/stylus not included

Apple has long dominated the tablet space since the introduction of the original iPad. Since then, the company has been pushing the boundaries of what a tablet can do and what a tablet can be. It offers a 13-inch Tandem OLED display, which is essentially two layers of OLED pixels stacked on top of one another, which solves two problems tablets have with OLED—brightness and burn-in. The dual-layer of OLED pixels allows for greater brightness and more power efficiency with less chance of burn-in during normal use.

Moreover, the iPad Pro gives you a huge screen with a fully integrated app ecosystem that allows you to do basically anything you might need during your studies, from writing to research. You can even start typing on your favorite MacBook and seamlessly transfer to the iPad to streamline your study session. Plus, Apple supports the iPad for a very long time. The longevity of iPads means that this tablet will stay with your student long after graduation. Just keep in mind that you'll need to add the Apple Pencil (2nd Gen) to take notes and the Magic Keyboard to make it function as a laptop.

Best Budget Tablet For Students

Amazon productivity combined with microsoft software, amazon fire max 11.

Inexpensive compared to the competition
Included trial of Microsoft Office 365
Underpowered
Weak app ecosystem (beyond MS Office)

Amazon tablets are a close second to iPad when it comes to tablet market share. Generally they’re pretty respectable devices for content consumption and some light gaming. Recently, Amazon decided to make a push into productivity, and its first steps into that arena come with this Amazon Fire Max 11. You can get the tablet on its own or you can get the Amazon Fire Max 11 bundle that includes a keyboard and stylus for typing and note taking. Amazon also partnered with Microsoft to bundle in a three-month trial of Office 365, meaning you get Word, Excel and Powerpoint for your classes and presentations at a discount for a short time. Bringing one of the most popular productivity suites to the Amazon Appstore was a great move because the rest of that app store is decidedly not great.

Specifically, the Amazon Appstore is something of a wasteland of broken and forgotten apps beyond the typical content streamers and Microsoft apps. You can get the main apps like Netflix and Hulu (and, of course, the Kindle app), but most simply aren’t available. Maybe that’s a good thing to send with your student to keep them from getting distracted. But mostly, this is a light and portable writing and streaming machine which should get your student through a day of studying and a night of relaxing.

Best Apple Tablet For Students

The best value for dollar of all ipad devices, apple ipad air.

Rich app ecosystem filled with productivity apps
Works great with other Apple devices.
Good balance of cost and power
Keyboard and stylus can be expensive
Not great for multitasking

If you want a great Apple tablet, but you don’t want to shell out for the best of the best, the iPad Air is a great alternative that will offer a similar experience at a significantly more affordable price. You still have the same disadvantages as the iPad Pro—notably the lack of included keyboard and stylus. Not only are they not included, but the cost of those accessories alone almost equal to the cost of the tablet by itself, effectively doubling your investment.

But if you’re carrying an iPhone and/or MacBook, the iPad Air is a wonderful companion serving as a second monitor for the MacBook, or syncing with the Wi-Fi hotspot from the iPhone for 5G connectivity. You can also use the devices almost interchangeably, snapping a photo with your iPhone and importing it directly into a PowerPoint slide on the iPad.

iPadOS has come a long way in terms of being a great tablet interface, but there’s still some work to do. It’s not the greatest multitasking experience, lacking the taskbar for easily switching apps. Other apps don’t work very well with multitasking in general, so don’t expect to get a full PC-like experience. Overall though, you still get a ton of power in a thin package that can almost completely replace a laptop in a pinch.

Best Android Tablet For Students

A productivity machine, powered by dex, samsung galaxy tab s9 ultra.

Huge, gorgeous display
Samsung DeX is a multitasking game changer
Keyboard case not included

Samsung is one of a couple of tablet makers still pushing the envelope when it comes to the devices. Samsung’s Galaxy Tab S9 Ultra is loaded with the best processor, RAM and storage space in an effort to draw in the productivity crowd. One of Samsung’s signatures is in the gorgeous display. The 14.6-inch AMOLED 2x display gives you that large canvas to work on with a high contrast ratio and super deep blacks. You also get the Snapdragon 8 Gen 2 processor, which was the flagship processor at the time when this tablet debuted in the summer of 2023. At the time, I tested this tablet, and you can read the full Samsung Tab S9 Ultra review for plenty of more insight.

Samsung adds DeX, its multitasking platform that imitates a desktop operating system, complete with floating windows and a task bar for fast app switching. If you’re looking for a desktop experience with Android’s extensive catalog of apps, look no further. But the tablet is expensive, and doesn’t include the keyboard (though the stylus comes in the box), so it doesn’t come cheaply. But it has all the power and more than you'll need for your studies, and some gaming afterward.

Best Windows Tablet For Students

The very best from microsoft, with a powerful processor, microsoft surface pro copilot+ pc (11th edition).

Full desktop OS
Snapdragon X Elite with Copilot
Built in kickstand
Keyboard not included
1st Gen processor could be tricky

If you want a combination laptop/tablet, the Surface Pro is about as close as you’ll get. The Surface Pro Flex Keyboard completes this package as a laptop replacement, but it isn’t shipped in the box, which means you’ll need to shell out extra for it. The Surface Pro certainly isn’t the only tablet that sells the keyboard separately, but it feels extra egregious when you consider that this is, for all intents and purposes, a Windows laptop.

The Surface comes with lovely industrial design that has become a trademark of the brand pretty much since its inception. The device has an all metal chassis with a tight hinge that can pose the tablet at any angle you might need. This year’s Surface also comes with Microsoft’s all-new Copilot button, which summons the AI engine when you press it—if one were so inclined.

The Surface also runs on Qualcomm’s new Snapdragon X Elite processor, which is the next generation in ARM-based processing. Essentially, it’s a hard pivot away from the likes of Intel and AMD, who have ruled this space for years. By all reports, the processor seems to hold up well compared to its x86 compatriots, but as of this writing, it’s still very new, so it’s hard to see how it’ll hold up long-term. Of course, the fact that Microsoft used the chip for its flagship hardware speaks to Microsoft’s confidence in the architecture.

Best E-Ink Tablet For Students

Great reader with pen support for highlights and notes, amazon kindle scribe.

All the Kindle reliability that you know and love
Adding markup to books is awesome
Amazing battery life
Limited functionality beyond just reading and note-taking

The Amazon Kindle is something of a staple in reading habits these days. Though people still appreciate the physical book, digital e readers are more often the norm when it comes to reading books. But one thing that e-readers have traditionally lacked was the ability to markup texts like what one might do if studying. To that end, the Kindle Scribe might have been made just for your student headed off to college.

The Scribe gives you a much larger canvas for reading and battery life that is measured in months, not weeks. That’s no small thing. It’s no good showing up to class with a dead tablet, especially if that tablet is your primary study device. The battery life on the Kindle Scribe should ensure that basically never happens.

The only problem is, that's about all this tablet does. The E Ink screen is not suitable for displaying anything except books—even web pages are a challenge. So while the Kindle Scribe can be great for reading and taking notes, it falls short when it comes to general research. Put simply, there is zero chance this is the only large-screened computing device you’ll use at college.

What our editors say: Consumer tech editor Rebecca Isaacs says in her full review , “One of my favorite things about the Scribe is the notebook feature and the writing experience itself. The notebook comes with complete customizability. If I wanted to swap between a large rule-lined page or a dotted grid, I could open the settings and change it with a couple of taps. Additionally, writing on the page felt smooth and fluid. One of my great concerns when I test out E Ink tablets is that my script can sometimes appear pixelated. The Kindle Scribe keeps my handwriting looking natural and like I actually used a pen to write.”

Lululemon’s “We Made Too Much” Section Is Full Of Hidden Gems Right Now

The best white noise machines that drown out sounds for better sleep, why trust forbes vetted.

The Forbes Vetted team has amassed an impressive library of tech content, including recommendations roundups and tested reviews .

The author of this story, Adam Doud , is a Chicago-based freelance reviewer who has been writing about consumer electronics for over a decade with a focus on mobile phones, tablets and cellular technology. He has tested almost every major phone on the market over the past several years, including the Samsung Galaxy Z Fold 5 and the Google Pixel 8 Pro .
Rebecca Isaacs is Forbes Vetted’s consumer tech editor, and she oversees and approved this article. She’s spent the past several years learning everything there is to know about consumer technology, with a special focus on smart home.
Since the computing world moves at lightning speed, we regularly review and fact-check our articles to make sure the recommendations are still current and accurate. This article was last updated in July 2024 to include an all-new lineup of tablets.

How We Chose The Best Tablets For Students

At Forbes Vetted, we’ve tested plenty of tablets to get a sense of the top picks across a range of needs. Our picks for best tablets for students largely came down to our experience with each device.

Our writers and editors have tested all of our picks.
We looked at tablets that spanned all operating systems. These days, personal technology is so interconnected, it makes a lot of sense for your phone and tablet to run on the same operating system, or at least comparable operating systems. This way, you can have the same apps and experiences from device to device.
In addition to our own testing, we spoke with industry experts and consumer tech analysts to determine the top features a student might need to complete their tasks.
Finally, cost came into play. Since some students will be buying their tablets themselves. To that end, we wanted to span as large a field as possible, while remaining within the confines of what a student will find useful.

Frequently Asked Questions (FAQs)

Can a tablet replace a laptop.

The answer to this question largely depends on individual needs. For many people, a tablet like the Apple iPad Pro M4 can absolutely replace a laptop for a thinner, lighter portable machine. Where you might run into trouble is when it comes to desktop-class apps like video editors, graphics programs and even some sound editing tools. Many of them aren’t available on tablets, but that is a rapidly evolving shift. There are indeed apps that can accomplish all of those tasks, but the key difference comes in missing some heavier duty features. All that being said, it’s fair to say that well over half of a computer’s capabilities can be replicated on a tablet with very little compromise involved.

What Are The Advantages Of Choosing A Tablet Over A Laptop?

The key advantage to choosing a tablet is in the touchscreen. Not all laptops have touch screens, and that can be a disadvantage when it comes to things like drawing or marking up documents—both of which happen frequently when conducting research and/or writing papers in school. The other advantage is the posture you take when working on them. Yes, you can lean back on a chair and read off of your laptop, but it’s a lot easier and nicer with a tablet. Laptops can also outperform tablets in some scenarios, such as when perched on someone’s lap during a lecture (hence the name). It will boil down to your needs.

Should A Student Have A Tablet And A Laptop?

There’s a good argument to invest in both for the school year, especially if you’re investing in a note taking tablet like the Amazon Kindle Scribe . Tablets can act as a second screen when conducting research, or just keeping track of a sports game while doing research. There are many apps that you can buy that allow you to extend your screen onto a tablet even when built-in functionality isn’t there. A art student may want a tablet for drawing, and a laptop for writing, as an example. When going into a versatile environment like school, those multiple options can make the difference.

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JSmol Viewer

A survey: security vulnerabilities and protective strategies for graphical passwords.

1. Introduction

2. graphical password schemes, 2.1. wyswye (“where you see is what you enter”) scheme, 2.2. ho et al.’s scheme, 2.3. gokhale and waghmare’s scheme, 2.4. por et al.’s scheme, 2.5. sun et al.’s scheme, 2.6. a combination of graphical password recognition and recall scheme, 2.7. a hybrid textual-graphical authentication scheme, 2.8. pinwheel scheme, 2.9. selfiepass scheme, 2.10. graphical password based on mouse behavior (gp-mb) scheme, 2.11. gra-pin scheme, 2.12. vgmsgp scheme, 2.13. multi-factor authentication (mfa) scheme, 2.14. choice-based graphical password (cgp) scheme, 2.15. passpoint selection of automatic graphical password based on histogram, 3. possible vulnerabilities in systems for graphical password schemes, 4. countermeasures and mitigation strategies, 4.1. guessing attack.

Randomization Technique: It has been found that one of the ways to mitigate the guessing attack is by using the randomization technique. To avoid the problem of guess attacks, the “Click-based Captcha as a Graphical Password (CaRP)” [ 44 ] system generates a random challenge image containing all password letters for the subsequent session.
ClickText Scheme: Specifically, the “ClickText” scheme within the framework of the CaRP system is used; in the challenge image, characters are mixed in a random order, in addition to the alphanumeric characters and special symbols are placed. This appending of random elements is an additional layer of challenge maximization, which deters the attackers from guessing the right password [ 44 ].
AnimalGrid Scheme: Another measure within the CaRP system is the “AnimalGrid” scheme, in which the graphical representations of animal images are included in the form of 2D images for authentication. The AnimalGrid scheme is similar to the ClickText scheme, and in addition to a variety of images used in this type of scheme, the randomness and variability of such images make it even more secure against guess attacks [ 44 ].

4.2. Spyware Attack

Randomization: Randomization has also been applied to one of the two proposed mobile authentication strategies, that is, coin passcode graphical password authentication by [ 45 ]. Of the two proposed, AuthMobile is the hybrid graphical-password mobile authentication approach. As for the functionality of this scheme in this malicious application, the users are to enter the correct passcode for the coins to verify them. Of the separated six inputs, the “keypads” of letters a, b, c, d, e and f are designated for each of the six inputs and are run six times in every iteration; randomly, another advantage is the fact that such randomization would fight against spying and is good at ensuring the safety of the devices.
Performing Tests during Authentication: This one is particularly a severe issue because performing tests during an authentication process leads to compromising the system, as well as valuable user and account data necessary to attackers and hackers. Here, several papers are being presented in this context [ 11 , 16 ] wherein CAPTCHA is described as Completely Automated Public Turing Tests to Tell Computers and Humans Apart, which include tests during authentication.

4.3. Shoulder Surfing Attack

GOTPass: It employs the WYSWYE strategy, where what people see is actually what they get to experience in the facility. Users do not choose password images; rather, they point to the response grid in relation to the images. Onlookers witness arbitrary points on the keyboard being touched; thus, the password cannot be recognized.
EvoPass: This method alters the chosen password images to generate what can be referred to as “decoy sets”, which are also dynamic in nature and transforms the images into which recognizable information is eliminated gradually. Users can go back to the previously saved drafts in case they have trouble recognizing evolved-pass sketches.
Coin Passcode Model: It blends color, numerical values, and icons to give it form different passcodes. In the coin password, components of the password are altered each time to improve security agains shoulder-surfing and brute force attacks. Interactions of the users with the interface do not disclose the true passcode.
2D Coordinates System: It employs random 2D coordinates to protect pictures and create passwords at the same time. During login, the images presented in the x and y coordinates randomly switch; thus, it becomes impossible to define the original image, and this contributes to the shields against shoulder-surfing attacks.

4.4. Video Recording Attack

4.5. filtering attack.

Utilize encryption and authentication at the possible sphere to shield information streams. This makes it impossible for an attacker to scan the messages, as would be done in the normal https protocol, where the attacker filters out certain content.
Improving network security: - Employ network redundancy. If going to be lose connections in one part of the network due to filtering, we should have the other connections ready beforehand. - Sprawl out the modes of communication rather than centralize them to one general protocol, port or connection. - Verify the source and authenticity of all the received messages. More importantly, make sure you are using checksums, hashes and the like to ensure that any alterations made to the original data are detected, and it is better to isolate on different physical buses, if attainable, for transmitting more sensitive messages, thereby improving network security. - Some of the communication ports/protocols should not be opened, especially those that are frequently targeted by hackers and other malicious individuals.

4.6. Reverse Engineering Attack

Code obfuscation: It makes it difficult for an attacker to reverse engineer the code.
Legal: Organizations should seek legal ways to protect their codes, such as copyright laws and end-user license agreements.
Control of source codes and encryption: organizations should ensure that they use strong access controls and encryption techniques to prevent an attacker from gaining access to confidential information.

4.7. Multiple Observations Attack

4.8. key/mouse logger attack, 4.9. brute force attack.

Randomization: Randomization is one of the ideas that can be implemented in an LMS to encourage learner participation, and it includes the pass-matrix of [ 12 ]. In the last, it presents a safe login area where users can select alphanumeric characters through an 8 × 8 matrix. All the chosen characters go through transpose operations on their columns, especially during the login sessions. This graphic (mutating) password scheme also prevents brute-force attacks since they act in a loop.
Large Password Space: The vibration and pattern (VAP) code, as proposed in [ 53 ], can be considered an instance of the large password space. It contains two quite different approaches and the password space, which helps to produce shields against brute force attacks.

4.10. Insider Threats

Perform background checks and screening of employees: This can help in the determination of increased risk employees, for instance, criminals or individuals with some financial related issues.
Limit access and implement segregation of duties: A general rule that should be observed is that no employee should be given full or complete access to any data and or systems used by the company, depending on the position they hold.
Monitor and analyze user activity: Permission from White Hat Hackers, as well as reviewing of auditing software such as data loss prevention, behavior analytics, or any other monitoring instruments, can show signs of malicious or unauthorized activity, transfer of sensitive information, violation of policies, and similar events.
Enforce endpoint security controls: Encapsulation of devices and networks, firewalls, antivirus, sequestration software that is frequently referred to as sandboxing, and restriction of the USB port helps in combating leakage and, hence, reducing the extent to which a company would lose.
Institute robust incident response and investigation capabilities: The insider threat should have a dedicated team and processes in place for a thorough evaluation in case the threat is realized and to effectively contain/remove the insider threat.

4.11. Dictionary Attack

Conundrum-Pass: This technique has been expounded in [ 6 ], and it entails choosing an image and a whole number, n, by the users where the said number will be used in the division of the targeted image into an n × n matrix; users can then choose parts of the image they want and come up with the required patterns. Shuffling is also explained when the login session is over, which means that the arrangement of the image chunks is random. To unlock the screen, the previous choice of the grids should be selected one by one in the correct sequence. This method also introduces certain randomness and randomness to the chosen patterns, thus making the method not vulnerable to dictionary attacks.
Spin-Wheel-Based Authentication: Another countermeasure that has been highlighted in [ 15 ] includes the spin-wheel-based graphical authentication mechanism. This approach provides a vast password space that does not allow for easy identification through a dictionary attack. The actual interface provided to the users is in the form of a spin wheel, four small spin wheels to be precise, each of which contains 36 slots labeled 1 through 36 in a peculiar manner. The user sets a password for the authentication by selecting four numbers from the sub-wheels and entering them in sequential order through the rotation of the main wheel. It also cascades elements of randomness and disorderliness in generating this password, making it difficult for it to be cracked by a dictionary attack.

4.12. Social Engineering Attack

User Awareness: As it has been seen in most cases of social engineering, it will be relevant to point out the fact that no attacks happen if prevention methods are well employed, and this will, in most cases, be determined by the users at the terminal end. Individuals should be compelled to care for security or even be made to cultivate a security sense so as to observe threats that may exist and strategies used by the attackers. They can categorize the attack tactics, with phishing being now one of the most popular attacks out there.
HTTPS Verification: This also means that the users can protect themselves from these phishing attacks, for example, by verifying whether this specific site has an HTTPS prefix before entering the password. From this context, HTTPS is said to refer to a site that is safe from security breaches through SSL and or TLS, hence making the connection secure. These assist in showing the user which website is safe to visit and which is fake [ 34 ].
Certificate Verification: Also, the system must ensure the website’s authenticity, and this can be done by verifying the digital certificate, which consists of a public key that is matched with identification data and a signature. When a browser communicates with a website, it means that the browser has come across an online tool. Then, perhaps, it can proceed to understand the circumstances of the installation, and in case of finding an installation of a certificate that is signed by an untrusted certificate authority, it should warn the user. This alert is of caution in order for the user not to key in the correct password into the related site, which the legitimate site regards as fake [ 34 ].

4.13. SQL injection Attack

In this regard, the activity entails limiting the privileges of the database user account to the basic ones that will be useful for the application. This can help reduce the affected damage if the malicious user has successfully invaded and launched a SQL injection attack;
Use of Web Application Firewalls (WAFs) for to limit the risks of SQL injection attacks;
Use of encryption should be introduced when using different means for safeguarding the given data, in which case it becomes more difficult for attackers to access or modify it. By using the described countermeasures, it becomes possible to nearly fully minimize the threat of SQL injection attacks, as well as to enhance the protection of the application.

4.14. Computer Vision Attack

Randomizing Pictures: The first is to randomize the pictures, where the position of the touch point is changed for each login. The above randomization makes the authentication process more complicated, and it becomes difficult for the attackers who use computer vision techniques;
Dynamic Screen Changes: Some devices have the capabilities to change the color and brightness of the screen, which is why people cannot secretly record videos. This alteration bewilders the camera and does not allow the attackers to record a clear video of their ill intentions;
User Education: The precautions should be advocated to the users such that their fingers are well covered when drawing the pattern during the authentication. This reduces the possibility of an attacker gaining useful information through video recording;
Additional On-Screen Activities: Other on-screen activities can be included in the pattern unlocking process to improve security. For instance, requiring the user to input a sentence in the same manner as Swype or drawing different graphical shapes before or after the pattern can add more layers to the authentication process for any potential attacker;
Skipping Dots: Another technique that users can apply when drawing a pattern is the omission of some of the dots in a vertical, horizontal, or diagonal sequence. This intentional skipping also makes it difficult for tracking algorithms to determine which dots are intentionally left out and, thus, complicates computer vision-based attacks.

4.15. Image Gallery Attack

Watermarking Techniques: To prevent a breakthrough of image gallery attacks and modifications of images in the gallery, watermarking methods can be applied [ 39 ]. Watermarking is the process of applying a distinctive watermark to each of the digital images. A secret key is used to designate a specific location of the watermark within the image.
Verification Using Secret Key: In case the users or the system require the identification process of images in the gallery as genuine or original, the secret key is used. By extracting the watermark from an imprint and comparing it with an embedded watermark using the secret key, one can decide if the image has been tampered with or not.

4.16. Sonar Attack

Limiting microphone use in the background: When creating patterns is one way to counteract sonar attacks [ 40 ]. By restricting access to the microphone, attackers are unable to record acoustic signals and, thus, cannot identify fingertip movements on the screen.
Randomization of Pattern Grid Layouts: Moving the pattern grids in random positions in the network and varying the intervals between rows or columns also creates a high level of difficulty when mounting an attack [ 40 ]. This randomization also prevents the attacker from creating a valid database matching the movement features of a particular site with the password patterns. However, one must wonder how this can affect the overall user experience and whether it brings any benefits.
Restricting Frequency Range: Another countermeasure is to limit the operating frequency to prevent its transmission signal that is inaudible by the human ear [ 53 ]. Similarly, one can integrate the functionality for pop-up notifications, which informs a user that a specific high-frequency sound signal has been received, suggesting the possible existence of a side channel attack.
Acoustic Jamming: There are other methods that can be implemented to counter sonar attacks, and one of them is jamming in the acoustic channel. Interference is used as a method of preventing attackers from initiating the attack as planned.

4.17. Reply Attack

Numbers in sequences, names of devices and their corresponding timestamps: This should be assigned to each packet sent and include the sequence number and the timestamp. This is because flow control enables the receiver to detect duplicate or out-of-order packets that could be suggestive of a reply attack.
Authentication: Imposing an authentication process or cryptographic methods, such as digital signatures on the packets, complicates an attack since the attacker cannot send messages as a reply. This way, the receiver can easily tell whether the sender is genuine or not.
Filtering: It is also possible that networks can block packets having source IP addresses outside this network or packets arriving on ports/protocols that are not used. This makes the process of sending spoofed reply packets difficult for an attacker.
Disable response protocols: Eliminating any host’s available reply protocols with UDP reply services (e.g., chargen, echo) decreases the services offered to attackers in a reply attack.

4.18. Data Interception

Authentication Protocol: Only by using the correct authentication protocol in the construction of channels for interaction between the server and the client can such attacks be prevented. The new concept to explain is the change in the values shifted over an authentication session in which different values are used. This goes a long way in reducing the scenario whereby the same authentication data are intercepted by an attacker and are used to flood the system with similar values with the aim of “locking out” the genuine client.
Hashing Timestamps and Pass-image Components: English and Poet [ 22 ] also recommended utilizing this countermeasure in cases when hashing was implemented for some of the authentication components, including the timestamps and data related to the pass-image. When hashed, these components make it difficult for the attackers to analyze the authentication data given below: the use of hashing makes the authentication data look like a randomly generated string of characters even when it has been intercepted, hence making it immune to eavesdropping attacks.
Random Location Assignment for Passphrase: Authors English and Poet also propose that the passphrase should be placed in the system space randomly each time the attempt to authenticate is made [ 22 ]. This implies that while encrypting the session key with the passphrase, the position of the passphrase shifts with each session and has to be transmitted to the server for checking. This dynamic location assignment makes the data that are being used in the authentication process unique and not easily forged since the attacker will need to intercept the information sent several times before getting one right in his or her attack.

4.19. Histogram Manipulation Attacks

Implement a random generation of color palette or binning algorithm: This means that when drawing histograms, small differences can lead to completely different histograms being produced. The randomization process can be performed per image, or there can be groups of images that are randomized.
The image can be made blurry, or the contrast can be reduced so that it will be difficult to notice that changes are being made to the histogram. While this slightly reduces the quality of the image, it is not always an undesirable effect and can be utilized when necessary.
Another aspect is adding or subtracting some random noise to the image pixels, which alters the histogram shape and is randomly difficult for an attacker to manipulate. Again, this reduces quality.
Stamp or highlight critical areas of the image that must be fixed with a watermark. It helps to check the unalterable stamp sections by extracting the watermark at a later stage if needed.
Implement the process to monitor the metadata of the image contents, such as hashes and timestamps, at the database level in order to detect instances of tampering across the storage systems. It can expose other levels of manipulation.

5. Experimental Results

Testbed: To replicate a similar environment in the real world to that an attacker with bad intentions can take advantage of the hole to invade the system, we created a vulnerable web application on a virtual machine;
SQL Injection Attack;
Reverse Engineering Attack;
Brute Force Attack;
Image Gallery Attack.
Encryption and Authentication;
Web Application Firewall (WAF);
Dynamic Screen Changes and Randomness;
Image Watermarking and Encryption;
Filtering and Authentication.
Evaluation Metrics: Based on the protective strategies followed, the following measures were considered while assessing the efficiency:
ASR: 0% (all attacks have been prevented);
ADR: It was 100 percent (all the attacks were detected);
FPR: It indicated 0% false alarms, meaning no false alarms per day;
RT: 0.5 s (the median reaction time).
ASR: 20%; this means that four out of 20 attacks were successful;
ADR: 80%; such a performance means that during 20 attacks, it is possible to detect 16 of them;
FPR: 10% means that there are two false alarms;
RT: 1.2 s is the average response time.
ASR: 10% of the attacks were successful, that is, 2 of the 20 attacks;
ADR: 90%, that is, 18 out of the 20 attacks were successfully detected;
FPR: 5% (possibility that one is being false negative);
RT: 0.8 s (mean response time).
ASR: 15% of the supposed attempts were successful (three of the twenty attacks);
ADR: 85% percent of attackers were detected, with a mean number of 17 from 20 attacks;
FPR: 10% (2 false alarms);
RT: 1.5 s, which is the average time it takes to respond.
ASR: 25%; that is, five out of the 20 attacks made were successful;
ADR: 75% of possible attacks were detected (15 out of twenty possible attacks);
FPR: 15% of alarms were false alarms, that is, three false alarms out of total alarms;
RT: 2.1 s; it is approximate (average response time).

6. Discussion

7. conclusions and future research, author contributions, data availability statement, conflicts of interest.

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No.	Type of Security Attack	Related Graphical Password Schemes
	Guessing Attack.	WYSWYE (“Where You See is What You Enter”) scheme. VGMSGP scheme. Multi-Factor Authentication (MFA) scheme. PassPoint Selection of Automatic Graphical Password Based on Histogram.
	Spyware Attack.	WYSWYE (“Where You See is What You Enter”) scheme. A combination of graphical password recognition and recall scheme. GRA-PIN scheme. VGMSGP Scheme. Multi-Factor Authentication (MFA) scheme.
	Shoulder Surfing Attack	WYSWYE (“Where You See is What You Enter”) scheme. Ho et al.’s scheme [ ]. Gokhale and Waghmare’s scheme [ ]. Por et al.’s scheme [ ]. Sun et al.’s scheme [ ].
	Video Recording Attack	Ho et al.’s scheme [ ]. Por et al.’s scheme [ ]. Sun et al.’s scheme [ ].
	Filtering Attack	Gokhale and Waghmare’s scheme [ ]. A combination of graphical password recognition and recall scheme. Multi-Factor Authentication (MFA) Scheme.
	Reverse Engineering Attack	Gokhale and Waghmare’s scheme [ ]. Por et al.’s scheme [ ]. Sun et al.’s scheme [ ]. A combination of graphical password recognition and recall scheme. A Hybrid Textual-Graphical Authentication scheme. PinWheel scheme. SelfiePass scheme. GRA-PIN scheme.
	Multiple Observations Attack	Sun et al.’s scheme [ ].
	Key/Mouse Logger Attack	A Hybrid Textual-Graphical Authentication Scheme. PinWheel scheme. SelfiePass scheme. Graphical Password based on Mouse Behavior (GP-MB) scheme.
	Brute Force Attack	Graphical Password based on Mouse Behavior (GP-MB) scheme. PassPoint Selection of Automatic Graphical Password Based on Histogram.
	Insider Threats	Graphical Password based on Mouse Behavior (GP-MB) scheme.
	Dictionary Attack	Graphical Password based on Mouse Behavior (GP-MB) scheme.
	Social Engineering Attack	A hybrid textual-graphical authentication scheme. PinWheel scheme. SelfiePass scheme. GRA-PIN scheme. Graphical Password based on Mouse Behavior (GP-MB) scheme.
	SQL Injection ASttack	Gokhale and Waghmare’s scheme [ ]. PinWheel scheme. Choice-Based Graphical Password (CGP) scheme. PassPoint Selection of Automatic Graphical Password Based on Histogram.
	Computer Vision Attack	Choice-Based Graphical Password (CGP) scheme.
	Image Gallery Attack	Choice-Based Graphical Password (CGP) scheme.
	Sonar Attack	Choice-Based Graphical Password (CGP) scheme.
	Reply Attack	PassPoint Selection of Automatic Graphical Password Based on Histogram.
	Data Interception Attack “Man-In-The-Middle”	PassPoint Selection of Automatic Graphical Password Based on Histogram. Ho et al.’s scheme [ ].
	Histogram Manipulation Attack	PassPoint Selection of Automatic Graphical Password Based on Histogram.

Type of Security Attack	Countermeasures	Applicability	Implementation Cost	Usability
Guessing Attack	Random distribution of challenge images.	High	Low	High
Spyware Attack	Randomization. Performing tests during authentication. Different input methods.	High	Moderate	Moderate
Shoulder Surfing Attack	Confusion. Randomization.	Moderate	Low	High
Video Recording Attack	Randomization. Visual Complexity.	High	Moderate	High
Filtering Attack	Utilize encryption and authentication. Improving network security.	High	Moderate	Moderate
Reverse Engineering Attack	Code obfuscation. Control of source codes and encryption.	High	High	Low
Multiple Observations Attack	Monitoring and adjusting the privacy settings. Encryption.	High	Moderate	Moderate
Key/Mouse Logger Attack	Taking the safety measures. Multi-factor authentication and encryption.	High	Moderate	High
Brute Force Attack	Randomization. Large password space use. More layers of authentication. Limiting login attempts.	High	Moderate	High
Insider Threats	Imposing security controls on employees and peripheral devices.	High	Moderate	Moderate
Dictionary Attack	Randomization in Conundrum-Pass technique. Large password space in Spin-Wheel-Based Authentication.	High	Moderate	High
Social Engineering Attack	Increased users’ awareness. The usage of HTTPS on the website. Inform the users when the certificate check is not successful.	High	Low	High
SQL Injection Attack	Limiting the privileges of the database. Use Web Application Firewalls (WAFs). Encryption.	High	Moderate	Moderate
Computer Vision Attack	Randomness of pictures. Awareness of users. Dynamic Screen Changes.	High	Moderate	High
Image Gallery Attack	Method of watermarking. Using a Secret Key for Verification.	High	Moderate	Moderate
Sonar Attack	Changing of the pattern grid arrangement. Limit the use of the microphone and the frequency band that a device can operate in. Educate the users about the possibility of the attacks. Jamming on the acoustic channel.	High	Moderate	High
Reply Attack	Authentication. Filtering. Disable response protocols.	High	Moderate	High
Data Interception Attack ”Man-In-The-Middle”	Authentication Protocol. Hashing Timestamps and Pass-image Components. Random Location Assignment for Passphrase.	High	High	Low
Histogram Manipulation Attack	Adding randomness. Blur or the contrast; Adding or subtracting some random noise. Checking integrity at multiple levels (hashes and timestamps).	High	Moderate	High

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Saadi, Z.M.; Sadiq, A.T.; Akif, O.Z.; Farhan, A.K. A Survey: Security Vulnerabilities and Protective Strategies for Graphical Passwords. Electronics 2024 , 13 , 3042. https://doi.org/10.3390/electronics13153042

Saadi ZM, Sadiq AT, Akif OZ, Farhan AK. A Survey: Security Vulnerabilities and Protective Strategies for Graphical Passwords. Electronics . 2024; 13(15):3042. https://doi.org/10.3390/electronics13153042

Saadi, Zena Mohammad, Ahmed T. Sadiq, Omar Z. Akif, and Alaa K. Farhan. 2024. "A Survey: Security Vulnerabilities and Protective Strategies for Graphical Passwords" Electronics 13, no. 15: 3042. https://doi.org/10.3390/electronics13153042

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A photo illustration showing watermelon and other fruits cut up and stacked in a precarious tower.

Opinion David Wallace-Wells

Food as You Know It Is About to Change

Credit... Alma Haser

Supported by

By David Wallace-Wells

Opinion Writer

July 28, 2024

This essay is part of What to Eat on a Burning Planet, a series exploring bold ideas to secure our food supply. Read more about this project in a note from Eliza Barclay, Opinion’s climate editor.

From the vantage of the American supermarket aisle, the modern food system looks like a kind of miracle. Everything has been carefully cultivated for taste and convenience — even those foods billed as organic or heirloom — and produce regarded as exotic luxuries just a few generations ago now seems more like staples, available on demand: avocados, mangoes, out-of-season blueberries imported from Uruguay.

But the supermarket is also increasingly a diorama of the fragility of a system — disrupted in recent years by the pandemic, conflict and, increasingly, climate change. What comes next? Almost certainly, more disruptions and more hazards, enough to remake the whole future of food.

The world as a whole is already facing what the Cornell agricultural economist Chris Barrett calls a “food polycrisis.” Over the past decade, he says, what had long been reliable global patterns of year-on-year improvements in hunger first stalled and then reversed. Rates of undernourishment have grown 21 percent since 2017. Agricultural yields are still growing, but not as quickly as they used to and not as quickly as demand is booming. Obesity has continued to rise, and the average micronutrient content of dozens of popular vegetables has continued to fall . The food system is contributing to the growing burden of diabetes and heart disease and to new spillovers of infectious diseases from animals to humans as well.

And then there are prices. Worldwide, wholesale food prices, adjusted for inflation, have grown about 50 percent since 1999, and those prices have also grown considerably more volatile, making not just markets but the whole agricultural Rube Goldberg network less reliable. Overall, American grocery prices have grown by almost 21 percen t since President Biden took office, a phenomenon central to the widespread perception that the cost of living has exploded on his watch. Between 2020 and 2023, the wholesale price of olive oil tripled ; the price of cocoa delivered to American ports jumped by even more in less than two years. The economist Isabella Weber has proposed maintaining the food equivalent of a strategic petroleum reserve, to buffer against shortages and ease inevitable bursts of market chaos.

Price spikes are like seismographs for the food system, registering much larger drama elsewhere — and sometimes suggesting more tectonic changes underway as well. More than three-quarters of the population of Africa, which has already surpassed one billion, cannot today afford a healthy diet; this is where most of our global population growth is expected to happen this century, and there has been little agricultural productivity growth there for 20 years. Over the same time period, there hasn’t been much growth in the United States either.

How climate change could transform yields of two major crops

Projected change in corn and wheat yields in 2050, based on an upper-middle scenario for global warming.

Change in crop yield in 2050

Corn production in 2050

Drought conditions have already led Mexico to import a record amount

of corn in recent years. Climate change could further decrease its yields.

China is the world’s second-largest

producer of corn, but yields are projected to decrease across most of the country.

Wheat production in 2050

Pakistan, where wheat accounts for nearly two-thirds

of all calories

consumed, could

see sharp declines.

The U.S., one of the largest exporters of wheat, could see increased yields, especially in more northern latitudes.

Drought conditions have already led Mexico to import a record amount of corn in recent years. Climate change could further decrease its yields.

Rising temperatures could make the highlands of Peru

a more productive area for corn.

Pakistan, where wheat accounts for nearly two-thirds of all calories consumed, could see sharp declines.

producer of corn,

but yields are

projected to decrease across most of the country.

consumed, could see sharp declines.

Sources: Jägermeyr et al. (2021) “ Climate Impacts on Global Agriculture Emerge Earlier in New Generation of Climate and Crop Models ,” Nature Food ; World Bank; U.S.D.A.

Note: Yields shown are for the SSP370 middle-upper warming scenario and are compared with a 1983-2013 baseline.

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Essay on Importance of Computer

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100 Words Essay on Importance of Computer

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250 Words Essay on Importance of Computer

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500 Words Essay on Importance of Computer

Introduction.

The computer, a revolutionary invention of the twentieth century, has become a fundamental part of our daily lives. Its importance cannot be overstated as it has revolutionized various sectors including business, education, healthcare, and entertainment. This essay explores the significance of computers in our contemporary world.

The role of computers in education is transformative. They serve as an interactive medium where students can learn and explore new concepts. Online learning platforms, digital libraries, and educational software have made learning more accessible, engaging, and personalized. Furthermore, computers have also simplified research, data analysis, and presentation of academic work, enhancing the overall educational experience.

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Healthcare Advancements

Entertainment and communication.

The entertainment industry has been revolutionized by computers. They have given birth to digital media, video games, and computer-generated imagery (CGI) in films. Moreover, computers have redefined communication, making it instant and borderless. Social media, email, and video conferencing are now integral parts of our social and professional lives.

Challenges and Future Prospects

Despite the numerous benefits, the use of computers also brings challenges such as cybersecurity threats and digital divide. Addressing these issues is crucial for a safe and inclusive digital future. On the brighter side, the future of computers is promising with advancements like quantum computing, artificial intelligence, and virtual reality. These technologies are expected to further enhance our lives, solve complex problems, and open new avenues of exploration.

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