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Microsoft reportedly plans to unveil its Maia 300 AI chip in September, aiming to close the gap with Nvidia and other custom silicon rivals, backed by a large TSMC order and potential adoption by Anthropic.
Microsoft reportedly plans to unveil its Maia 300 custom AI chip this fall, claiming over 30% more tokens per dollar than existing silicon, and is in talks with TSMC for 300,000 chips by 2027 to reduce reliance on NVIDIA.
Anthropic is building a team to design its own custom AI chips, aiming to co-design hardware and models for greater efficiency as demand for Claude rises. The move follows OpenAI, Google, and Meta in pursuing in-house silicon.
A detailed history of the Rekursiv processor, a custom object-oriented CPU from the 1980s Scottish hi-fi company Linn Products, which pioneered hardware memory safety and persistent object storage. The article notes that these ideas are now appearing in modern ARM CHERI cores.
Meta announces it will start manufacturing its own AI chip, named Iris, in September, marking a move toward custom silicon for AI workloads.
OpenAI announces its first custom AI chip, Jalapeño, designed for LLM workloads and produced with Broadcom.
TechCrunch reports on the growing trend of major AI companies like OpenAI and SpaceX developing custom chips to reduce reliance on Nvidia, featuring a podcast discussion with hosts Kirsten Korosec, Anthony Ha, and Sean O'Kane.
The AI industry is fragmenting into three geopolitical stacks (US, China, EU) as OpenAI develops custom chips, Anthropic faces export controls, and Chinese models like DeepSeek dominate Hugging Face, ending the myth of a global AI commons.
OpenAI has announced its first custom AI inference chip, Jalapeño, developed in partnership with Broadcom to reduce reliance on Nvidia GPUs, with deployment expected by the end of 2026.
OpenAI and Broadcom unveiled Jalapeño, a custom LLM-optimized inference chip that promises substantially better performance per watt than current state-of-the-art, designed from the ground up for current and future AI models.
Xiaomi and TileRT achieved over 1,000 tokens per second inference on a 1-trillion parameter model using standard commodity GPUs, suggesting a major alternative to custom silicon.
A commentary arguing that the AI competition is shifting from model quality to hardware placement and infrastructure, highlighting Microsoft's Project Solara, NVIDIA's RTX Spark, and ByteDance's custom CPU efforts as signs that agentic workloads are driving new silicon and deployment strategies.