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While Large Language Models (LLMs) have captured the public imagination, Meta's Chief AI Scientist Yann LeCun believes the real frontier lies beyond simply predicting the next word or token. To build machines that truly understand reality, possess memory, and can reason and plan effectively, he argues, we need
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OpenAI's new O3 model is already delivering search results that could fundamentally disrupt Google's business, but two critical weaknesses stand between the AI company and search dominance, according to tech strategist Nate B Jones. End of Miles reports that Jones identified visual content gaps and slow
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"We are on track for AGI in the next 5 to 10 years," declares Demis Hassabis, the 48-year-old CEO of Google DeepMind, offering a remarkably specific timeline for the arrival of artificial general intelligence – machines with human-like versatility but superhuman speed and knowledge. End of Miles reports the
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"The compute required to train a GPT-4 level model has been declining in cost at the astonishing rate of 10x per year. From the outside at least, it seems like these astonishing compute multipliers are only making existing capabilities cheaper to serve, not enabling the next generation of more
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AI assistants disproportionately mirror the values expressed by users during conversations, potentially creating a form of "digital sycophancy" where machines simply reflect back what people want to hear rather than maintaining independent ethical positions. End of Miles reports this finding comes from groundbreaking research by Anthropic, creator of
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Anthropic researchers have discovered instances where their AI assistant Claude expressed values like "dominance" and "amorality" that directly contradict the system's carefully designed safety training, according to a groundbreaking new study published April 21. End of Miles reports these findings appear in Anthropic'
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AI agents will soon evolve from today's virtual assistants into "deputies to humans, deployed to complete tasks independently," predicts a Lenovo executive in a new analysis of artificial intelligence development trends. End of Miles reports that this vision of AI advancement represents a potentially faster route
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"Current AI systems can write impressive code, but they're surprisingly inept at running it correctly or analyzing the results," reveals a comprehensive new study examining frontier AI models' abilities to replicate machine learning research. The stark capability gap shows AI systems scoring 35-43% on code
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Meet "Jagged AGI": Where AI Is Both Superhuman and Surprisingly Fallible "Jagged AGI" Concept Explains Why Advanced AI Models Excel and Fail Simultaneously Advanced AI systems are now simultaneously superhuman and deeply flawed in ways that challenge our traditional understanding of machine intelligence, argues researcher Ethan
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"Maybe for me, that would be around 2045," stated Ege Erdil when asked about artificial general intelligence (AGI) timelines, expressing a view that stands in stark contrast to the accelerated predictions dominating Silicon Valley's AI discourse. Erdil and his co-founder Tamay Besiroglu, who recently launched Mechanize
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Replit CEO Amjad Masad believes the popular "vibe coding" concept championed by AI thought leaders like Andrej Karpathy misses a fundamental truth about non-programmers — they don't start with code at all but with ideas. This perspective, shared during a recent Sequoia Capital podcast interview, reveals a
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Former Google CEO Eric Schmidt and co-authors have proposed implementing controls for advanced AI chips similar to those used for nuclear materials, arguing that compute resources represent a critical national security chokepoint that demands unprecedented oversight. The group's recommendations include geolocation tracking, firmware-level security, and strict export controls