Google Cloud launches revolutionary Ironwood TPUs delivering 10X performance boost over previous generation chips, while AI company Anthropic prepares to harness up to one million TPUs as customers report dramatic improvements in speed and cost efficiency.
Lambda strikes massive multibillion-dollar partnership with Microsoft to construct AI infrastructure featuring tens of thousands of Nvidia chips, serving over 200,000 developers while planning a Kansas City AI factory by 2026.
Chinese researchers at Peking University develop groundbreaking analog chip using resistive memory that delivers 1,000x faster performance than top Nvidia and AMD GPUs while consuming 100x less energy, solving precision issues that have plagued analog computing for decades.
Large reasoning models now demonstrate genuine human-like thinking abilities through chain-of-thought reasoning, using pattern matching, working memory, and backtracking search to outperform average humans on logic tests, proving AI has evolved beyond simple pattern matching to possess real problem-solving capabilities.
University of Surrey scientists develop revolutionary brain-mimicking AI called Topographical Sparse Mapping that connects neurons only to nearby related ones, dramatically slashing energy consumption by over a million kilowatt-hours while boosting performance through biological pruning processes that refine connections during learning.
Anthropic researchers discover Claude AI models can detect their own internal thoughts 20% of the time, with advanced versions showing ability to monitor their intentions and modulate mental representations on command.
MediaTek sets ambitious goal to capture 10-15% of the $50 billion data center ASIC chip market, targeting $1 billion in cloud AI chip revenue by 2026 through partnerships with Nvidia on the GB10 Grace Blackwell Superchip.
Cognition unveils SWE-1.5, a breakthrough AI coding model with hundreds of billions of parameters that blazes at 950 tokens per second—13x faster than Sonnet 4.5—while delivering near state-of-the-art performance through advanced reinforcement learning and partnership with Cerebras infrastructure.
Cursor 2.0 launches with breakthrough Composer AI that codes 4x faster than competitors, completing most programming tasks in under 30 seconds while introducing agent-based interface that runs multiple coding processes simultaneously without interference.
Major AI interpretability research approaches including feature visualizations, saliency maps, and sparse autoencoders fail to decode how neural networks actually work after over a decade of investment, prompting Google DeepMind to abandon leading techniques and researchers to shift toward higher-level analysis methods.