AI

Language models have come a long way in being able to answer simple questions efficiently. However, when it comes to handling complex tasks that require reasoning and planning, special prompting techniques are necessary. These techniques, also known as “System 2” techniques, push language models to generate intermediate steps towards problem-solving, enhancing their reasoning capabilities. While
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In recent years, generative artificial intelligence has become a dominant force in the online world. From AI-generated summaries in Google search results to Meta’s AI tools on Facebook, the influence of AI is ubiquitous. This trend can be attributed to OpenAI’s release of ChatGPT in 2022, which sparked Silicon Valley’s obsession with generative AI. Fast
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Khanmigo, an AI-powered tutor, takes a unique approach to helping students by guiding them to find solutions on their own. Instead of providing direct answers to questions, Khanmigo encourages students to think critically and come up with ideas to solve problems. This method aims to empower students and help them become more independent learners. According
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In today’s digital age, the spread of misinformation and disinformation has become a major concern. A recent incident involving a piece of Russian disinformation about Ukrainian president Volodymyr Zelensky’s wife buying a Bugatti car with American aid money illustrates the speed at which false information can travel across the internet. The disinformation in question originated
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The landscape of AI has transformed significantly since November 2022, shifting from a technology in the background to a frontstage disruptor. Today, we are already witnessing the next phase of generative AI, with consumers embracing the technology and organizations making substantial investments. Gen AI is poised to revolutionize how businesses operate and succeed, particularly in
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The advent of large language models (LLMs) has revolutionized the way we approach writing, especially in the academic and scientific spheres. Researchers have recently conducted a study to evaluate the impact of LLMs on scientific writing by analyzing a vast number of abstracts published between 2010 and 2024. Their findings shed light on the extent
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AI agents are a cutting-edge research direction with significant potential applications. However, a recent analysis by researchers at Princeton University has revealed critical shortcomings in current agent benchmarks and evaluation practices that hinder their real-world usefulness. One major issue highlighted by the researchers is the lack of cost control in agent evaluations. Unlike single model
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The tech world has long been fascinated by large language models (LLMs) powered by Nvidia GPUs. However, a quieter revolution is taking place in AI hardware, with the emergence of neuromorphic computing. Traditional deep learning architectures are facing limitations in terms of energy demands, leading to the rise of neuromorphic systems that promise to drastically
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