Meta begins testing its first in-house AI training chip — TradingView ...
Facebook owner Meta is testing its first in-house chip for training artificial intelligence systems, a key milestone as it moves to design more of its own custom silicon and reduce reliance on external suppliers like Nvidia, two sources told Reuters.
Deployment and Production
The world's biggest social media company has begun a small deployment of the chip and plans to ramp up production for wide-scale use if the test goes well, the sources said.
Cost Reduction Strategy
The push to develop in-house chips is part of a long-term plan at Meta to bring down its mammoth infrastructure costs as the company places expensive bets on AI tools to drive growth. Meta, which also owns Instagram and WhatsApp, has forecast total 2025 expenses of $114 billion to $119 billion, including up to $65 billion in capital expenditure largely driven by spending on AI infrastructure.
Technical Details
The chip is the latest in the company's Meta Training and Inference Accelerator (MTIA) series. Meta executives have said they want to start using their own chips by 2026 for training, or the compute-intensive process of feeding the AI system reams of data to "teach" it how to perform. One of the sources said Meta's new training chip is a dedicated accelerator, meaning it is designed to handle only AI-specific tasks. This can make it more power-efficient than the integrated graphics processing units (GPUs) generally used for AI workloads. Meta is working with Taiwan-based chip manufacturer TSMC to produce the chip, this person said.
Development Process
The test deployment began after Meta finished its first "tape-out" of the chip, a significant marker of success in silicon development work that involves sending an initial design through a chip factory, the other source said. A typical tape-out costs tens of millions of dollars and takes roughly three to six months to complete, with no guarantee the test will succeed.
Industry Impact
The value of Nvidia's GPUs has been thrown into question this year as AI researchers increasingly express doubts about how much more progress can be made by continuing to "scale up" large language models by adding ever more data and computing power. Traders and investors use our platform. Top website in the world when it comes to all things investing. Mobile reviews with 4.9 average rating. No other fintech apps are more loved. Custom scripts and ideas shared by our users.
