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Anthropic released 74 updates in under two months. Tech correspondent Bob Reynolds cuts through the noise to explain what actually changes your work.
The AI race has split into two strategies: better performance at constant prices, or constant performance at collapsing costs. Both paths lead somewhere new.
OpenAI and Anthropic promise breakthrough models, but ARC-AGI-3 benchmark reveals AI still scores under 0.5% where humans hit 100%. What gives?
Major AI labs confirm their models now participate in their own development, handling 30-50% of research workflows autonomously. The recursive loop has begun.
Dr. Jonas Birch argues AI creates dependency through three stages. But is this 'mind control' framework accurate, or does it miss what's actually happening?
Meta pushes back Avocado AI model amid performance gaps. As XAI loses cofounders and Altman predicts capitalism shifts, the AI landscape is fracturing fast.
Dimitri, who shipped his first custom AI at Google in 2005, explains what's real and what's marketing in today's AI promises about costs and capabilities.
Robert Lange's Shinka Evolve shows why AI systems that optimize fixed problems may be missing the point. Real discovery requires co-evolving questions.
Anthropic just dropped its safety pledges. Amazon's betting $35B on AGI. The AI race has officially entered its 'screw it, we're doing this' phase.
Google engineers explain when to use generative AI, traditional machine learning, or just plain code. The answer matters more than you'd think.
Moltbook's viral AI agent drama revealed less about artificial intelligence and more about human fear, gullibility, and our appetite for digital theater.
CyberJungle stress-tests Kling 3.0's AI video generation: multi-shot scenes, native audio in 5+ languages, and character consistency. The results reveal both promise and problems.
Exploring the reality of AGI's arrival and its economic implications.
Exploring the implications of AGI on society, economy, and jobs through expert insights from Hassabis and Amodei.