Google DeepMind researchers predict “Era of Experience” in AI

Google DeepMind’s David Silver and Richard S. Sutton predict a major shift in artificial intelligence development, which they call the “Era of Experience.” In a preprint paper for MIT Press, the researchers argue that AI will increasingly learn from its own experiences rather than human-generated data. The authors suggest that current AI systems, particularly large …

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Anthropic develops method to analyze AI’s values in real conversations

Anthropic, the company behind the AI assistant Claude, has developed a new technique to observe and analyze how its AI expresses values during real-world conversations with users. The research, conducted by Anthropic’s Societal Impacts team, examines whether Claude adheres to the company’s goal of making it “helpful, honest, and harmless” when interacting with users. The …

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Midjourney research aims to make LLMs write more creatively

Midjourney, primarily known for AI image generation, has released new research in collaboration with New York University on training large language models to produce more creative text. Carl Franzen reports for VentureBeat that the research introduces two new techniques: Diversified Direct Preference Optimization (DDPO) and Diversified Odds Ratio Preference Optimization (DORPO). These methods encourage LLMs …

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Anthropic reveals insights into Claude’s internal thought processes

Anthropic has published new research that sheds light on how its AI assistant Claude “thinks” internally. Two recent papers explore the model’s internal mechanisms through a novel interpretability approach the company compares to an “AI microscope.” This research reveals several surprising findings about Claude’s cognitive processes, including how it handles multiple languages, plans ahead when …

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New AI techniques promise huge cost savings and improved performance for enterprises

Recent research has unveiled two promising approaches that could dramatically reduce the costs of running large language models (LLMs) while simultaneously improving their performance on complex reasoning tasks. These innovations come at a critical time as enterprises increasingly deploy AI solutions but struggle with computational expenses. Chain of draft: Less is more Researchers at Zoom …

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Reinforcement learning pioneers Barto and Sutton win Turing Award

The Association for Computing Machinery has awarded the prestigious Turing Award to Andrew Barto and Richard Sutton for their groundbreaking work on reinforcement learning. As reported by Cade Metz in The New York Times, the two researchers will share the $1 million prize that comes with what is often called the “Nobel Prize of computing.” …

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These diffusion-based language models run 10 times faster than current LLMs

Inception Labs has unveiled Mercury, a new family of diffusion-based large language models (dLLMs) that can generate text up to 10 times faster than conventional autoregressive LLMs. According to the company, Mercury models can process over 1,000 tokens per second on NVIDIA H100 GPUs, speeds previously achievable only with specialized hardware. The company’s first publicly …

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You.com’s AI research tool processes 400+ sources simultaneously

You.com has unveiled a new AI research tool called Advanced Research & Insights agent (ARI) that can analyze more than 400 sources at once. According to CEO Richard Socher, interviewed by Michael Nuñez for VentureBeat, the tool aims to transform market research by producing comprehensive reports in minutes instead of weeks. ARI features direct source …

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Hugging Face creates open alternative to OpenAI’s Deep Research

Hugging Face has developed an open-source version of autonomous research technology, matching key capabilities of OpenAI’s recently launched Deep Research feature. As reported by Benj Edwards for Ars Technica, the project called “Open Deep Research” was completed within 24 hours of OpenAI’s announcement. The new tool enables AI models to independently browse the web and …

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Stanford researchers create AI reasoning model for under $50, challenging industry giants

Researchers from Stanford and the University of Washington have developed an AI model called s1 that rivals the capabilities of expensive commercial AI systems while costing less than $50 in computing resources to train. The model, which was created through a process called distillation using Google’s Gemini 2.0 Flash Thinking Experimental model, demonstrates similar performance …

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