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first_img Microsoft launched its self-developed AI chip Maia 300, with the key small chip using TSMC's 2-nanometer technology

According to a report by Central News Agency citing Reuters, Microsoft announced the launch of its third-generation self-developed AI chip, Maia 300, with plans to deploy over 1 million units next year to support internal AI services. The small chip responsible for key computing functions uses TSMC's 2-nanometer process. The Maia 300 can handle code writing and perform complex business tasks on behalf of users. The previous generation of chips has been used to run Microsoft's internal AI models and the OpenAI models provided through Microsoft Azure cloud computing services.Microsoft is taking a different technological approach compared to NVIDIA. The NVIDIA AI accelerator uses a large computing chip surrounded by high-bandwidth memory chips; the Maia 300 core processing unit is composed of small chips, with the small chips responsible for key computing functions using TSMC's 2-nanometer process, while other small chips use the lower-cost 3-nanometer process to handle data transmission out of the processor and transfer data to other locations within the system.The Maia 300 will be installed in cabinets, with each cabinet accommodating 96 chips and consuming about 167 kW of power. In contrast, NVIDIA's latest GB300 AI server cabinet is configured with 72 GPUs and consumes about 142 kW of power. Microsoft stated that it plans to deploy the Maia 300 on a large scale starting next year, reaching several gigawatts. Microsoft previously indicated that it expects its capital expenditures to exceed $175 billion this year.

first_img Thomson Reuters launched its self-developed AI model Thomson-1, based on Alibaba's open-source Qwen

According to Business Insider, Thomson Reuters launched its first self-developed AI model, Thomson-1, on Monday. This model is based on Snowdon and constructed through "re-alignment" of Alibaba's open-source Qwen model. Open-source means anyone can download and modify the model for free. Thomson-1 will take over some tasks previously handled by Anthropic's Claude, but it is not intended to completely replace collaboration with Anthropic and other labs, initially focusing on the company's areas of expertise, starting with document review.This move aims to address the high AI costs brought by models like Claude and OpenAI Codex, and reflects the use of cheaper Chinese open-source AI. CTO Joel Hron stated that the main reason is to better leverage Thomson Reuters' own expertise and control costs. The company expanded its collaboration with Anthropic in May this year for the AI legal assistant CoCounsel, which still primarily relies on Claude. Hron said, "Our main goal is to gradually make Thomson the model that drives more and more capabilities for CoCounsel."Thomson Reuters, in collaboration with a team from Imperial College London, spent months transforming Qwen to build Snowdon and ensured it is "ethically and politically bias-processed and safe to use." Hron pointed out that having a proprietary model allows for development based on its own intellectual property rather than continuously paying external AI companies, comparing it to renting versus buying a house: renting provides shelter but does not accumulate long-term equity.
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