What Would Hayek Think of AI?
The International Monetary Fund promises that 'AI can enhance democratic institutions by ensuring citizens' voices are truly heard.' Power wielded by a few experts can enhance democracy? Isn't that what the early 20th-century Progressive movement promised? For that matter, isn't that the thinking behind Soviet 'scientific socialism'?
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33 minutes ago
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New memristor-based system by Chinese scientists boosts AI data sorting efficiency
In a bid to overcome shortcomings in scientific computing, Chinese scientists have unveiled a new approach to sorting data that promises both higher speed and lower energy consumption. The system combines memristors—electronic components that mimic the memory function of the human brain—with an advanced sorting algorithm to process large amounts of information more efficiently. Researchers say this method could help overcome performance bottlenecks in not just computing but also artificial intelligence (AI), and hardware design, where rapidly organizing and analyzing vast datasets is essential. Beyond AI, potential applications for this technology include smart traffic systems that analyze images in real time and financial services that require quick risk assessments. To demonstrate the potential of their technology, scientists from Peking University and the Chinese Institute for Brain Research created a hardware sorting prototype based on memristors. The system successfully handled tasks like route finding and neural network inference, delivering faster performance and lower energy consumption compared to traditional sorting methods, the South China Morning Post reported. Overall, the system achieved a 7.7-fold increase in throughput and improved energy efficiency by more than 160 times compared to conventional sorting methods. It also boosted area efficiency by over 32 times, marking a significant step towards integrating storage and computing for broader, general-purpose applications. In a paper published in Nature Electronics last month, the team explained that sorting remains a major performance limitation across applications ranging from artificial intelligence and databases to web search and scientific computing. Traditional computing systems rely on the Von Neumann architecture, which separates data storage and processing functions, typically using a central processing unit (CPU) to handle calculations. According to the researchers of the latest study, the conventional system has led to the Von Neumann bottleneck, which limits the speed of data transfer between memory and processing units. They explained that while sort-in-memory approaches using memristors could help overcome these limitations, current systems still depend on comparison operations, keeping sorting performance constrained. Unlike ordinary resistors, which simply reduce the flow of electricity in a circuit, memristors have the unique ability to remember how much electrical charge has passed through them. This memory function allows memristors to adjust their resistance based on previous activity, enabling them to act as both storage and processing components. By combining these functions, memristors could eliminate the need to transfer data between separate memory and processing units, potentially leading to faster and more energy-efficient computing systems. The scientific team aimed to simplify sorting by removing the need for comparison units. Traditional hardware sorting relies on CPUs, GPUs, or specialised chips that compare numbers step by step using sorting algorithms. Instead, the new method uses memristors to perform iterative search-based sorting, finding minimum or maximum values without directly comparing each pair, which in turn saves both time and energy.
Yahoo
33 minutes ago
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I'm a university lecturer concerned that students are using AI to cheat. It's made my workload skyrocket, and I've had to make drastic changes.
Risa Morimoto has been a lecturer for 18 years. In that time, she's always seen students cheat. But Morimoto said AI tools have made it harder to detect cheating, increasing her workload. Next year, Morimoto plans to introduce new assessment methods to address her AI concerns. This as-told-to essay is based on a transcribed conversation with Risa Morimoto, a senior lecturer in economics at SOAS University of London, in England. The following has been edited for length and clarity. Students always cheat. I've been a lecturer for 18 years, and I've dealt with cheating throughout that time, but with AI tools becoming widely available in recent years, I've experienced a significant change. There are definitely positive aspects to AI. It's much easier to get access to information and students can use these tools to improve their writing, spelling, and grammar, so there are fewer badly written essays. However, I believe some of my students have been using AI to generate essay content that pulls information from the internet, instead of using material from my classes to complete their assignments. AI is supposed to help us work efficiently, but my workload has skyrocketed because of it. I have to spend lots of time figuring out whether the work students are handing in was really written by them. I've decided to take dramatic action, changing the way I assess students to encourage them to be more creative and rely less on AI. The world is changing, so universities can't stand still. I've worked at SOAS University of London since 2012. My teaching focus is ecological economics. Initially, my teaching style was exam-based, but I found that students were anxious about one-off exams, and their results wouldn't always correspond to their performance. I eventually pivoted to a focus on essays. Students chose their topic and consolidated theories into an essay. It worked well — until AI came along. Cheating used to be easier to spot. I'd maybe catch one or two students cheating by copying huge chunks of text from internet sources, leading to a plagiarism case. Even two or three years ago, detecting inappropriate AI use was easier due to signs like robotic writing styles. Now, with more sophisticated AI technologies, it's harder to detect, and I believe the scale of cheating has increased. I'll read 100 essays and some of them will be very similar using identical case examples, that I've never taught. These examples are typically referenced on the internet, which makes me think the students are using an AI tool that is incorporating them. Some of the essays will cite 20 pieces of literature, but not a single one will be something from the reading list I set. While students can use examples from internet sources in their work, I'm concerned that some students have just used AI to generate the essay content without reading or engaging with the original source. I started using AI detection tools to assess work, but I'm aware this technology has limitations. AI tools are easy to access for students who feel pressured by the amount of work they have to do. University fees are increasing, and a lot of students work part-time jobs, so it makes sense to me that they want to use these tools to complete work more quickly. During the first lecture of my module, I'll tell students they can use AI to check grammar or summarize the literature to better understand it, but they can't use it to generate responses to their assignments. SOAS has guidance for AI use among students, which sets similar principles about not using AI to generate essays. Over the past year, I've sat on an academic misconduct panel at the university, dealing with students who've been flagged for inappropriate AI use across departments. I've seen students refer to these guidelines and say that they only used AI to support their learning and not to write their responses. It can be hard to make decisions because you can't be 100% sure from reading the essay whether it's AI-generated or not. It's also hard to draw a line between cheating and using AI to support learning. My colleagues and I speak about the negative and positive aspects of AI, and we're aware that we still have a lot to learn about the technology ourselves. The university is encouraging lecturers to change their teaching and assessment practices. At the department level, we often discuss how to improve things. I send my two young children to a school with an alternative, progressive education system, rather than a mainstream British state school. Seeing how my kids are educated has inspired me to try two alternative assessment methods this coming academic year. I had to go through a formal process with the university to get them approved. I'll ask my students to choose a topic and produce a summary of what they learned in the class about it. Second, they'll create a blog, so they can translate what they've understood of the highly technical terms into a more communicable format. My aim is to make sure the assignments are directly tied to what we've learned in class and make assessments more personal and creative. The old assessment model, which involves memorizing facts and regurgitating them in exams, isn't useful anymore. ChatGPT can easily give you a beautiful summary of information like this. Instead, educators need to help students with soft skills, communication, and out-of-the-box thinking. In a statement to BI, a SOAS spokesperson said students are guided to use AI in ways that "uphold academic integrity." They said the university encouraged students to pursue work that is harder for AI to replicate and have "robust mechanisms" in place for investigating AI misuse. "The use of AI is constantly evolving, and we are regularly reviewing and updating our policies to respond to these changes," the spokesperson added. Do you have a story to share about AI in education? Contact this reporter at ccheong@ Read the original article on Business Insider
Forbes
40 minutes ago
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5 Ways AI Makes Google Search Work Harder For Your Brand
AI is giving Google Search superpowers, allowing it to go from helpfully responding to questions to intelligently anticipating intent. AI can help your brand unlock significant new business opportunities as consumers use Search's growing powers to ask, learn, discover, and buy more things than ever. This deeper understanding is changing how customers discover and connect with information and products online. In this fast-paced world of innovation, how can your marketing take advantage of these innovations and deliver new results for your business? Below are five ways AI is helping Google Search work harder for your brand, from the very first moment of consumer discovery all the way to when they decide to buy. Google Search is rapidly evolving with AI, opening up exciting new ways people can discover products and information. Tools like Google Lens and Circle to Search allow visual searches using images and video, a fast-growing trend with over 100 billion visual searches this year alone.1 Even better, 1 in 5 Lens searches have commercial intent.2 And with AI Overviews, people are searching more, are more satisfied with their results, and visit a greater diversity of websites, leading to higher-quality clicks for your brand. Rethink search: Prepare for AI-powered search by embracing Google's Performance Max and AI Max for Search campaigns. Focus on optimizing visuals and tags for shopping ads and supplying high-quality assets. Leverage your first-party data to train Google's AI, ensuring your ads intelligently connect with conversational and multi-modal queries across all Google surfaces. New search inputs—like images, voice, and follow-up questions—provide incredibly rich signals about what users are truly looking for. 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Updates to additional reports increase visibility into performance of AI-generated keywords, ad destinations, and AI-created assets. The integration of AI into Google Search isn't merely an incremental update; it's a profound transformation redefining the entire search landscape. For marketing leaders, the key takeaway is clear: as search formats and surfaces continue to evolve, so too must the strategies you employ. This shift empowers brands to connect with consumers in richer, more intuitive ways, moving beyond simple keyword matching to anticipating user intent and delivering highly personalized experiences at scale. 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