Meta Launches AI Chips to Reduce Reliance on Purchased Products

Meta is taking steps to increasingly rely on in-house AI chips as it moves to reduce its dependence on chips made by other companies. The firm revealed that it started this project back in 2023 and plans to release four new generations of its chips in the coming two years.

Its MTIA, or Meta Training & Inference Accelerator, chips are being made with emphasis on GenAI tasks, recommendations, and ranking in the products of the company.

The tech company revealed that its MTIA chips will form the core of the hardware they use and will then supplement these chips with chips procured from different firms rather than depending on silicon chips from only one company. This “portfolio approach” is intended to handle the company’s AI workloads as they grow and evolve.

Meta said it is already using thousands of its MTIA chips to handle the inference work linked to organic content as well as handling ads on its different apps. The firm said these chips are custom-built to perform the tasks required by the company rather than being designed for general use cases. In this way, the in-house chips allow the company to benefit from using silicon that was purpose-built for work that exists within Meta’s products.

The tech firm says its approach of using in-house purpose-built chips has delivered superior compute efficiency and led to cost reductions when compared to using externally sourced chips.

The company plans to implement its next phase of chip development that will result in rolling out four new chips during the next 24 months. It is working on MTIA 300, 400, MTIA 450 plus the 500 version. Each model is intended to be superior to the previous one in terms of memory bandwidth, efficiency and compute capacity. The company is currently producing the MTIA 300 AI chip and this version is intended to handle recommendations training and ranking.

The other three models will be capable of handling all workloads, but the company plans on focusing on deploying those chips to handle GenAI inference, at least in the short term. The company says all these chips are designed in a modular way which allows them to easily slide into the existing racks at the data centers of the firm. In this way, there is a reduction of the time required between completion of chip design and the deployment of that silicon.

Meta plans to break from the norm in the industry of having a new chip release every 2 years. Meta will release new versions within six months after the release of a previous model. This will be possible because the firm will be reusing existing modular designs rather than coming up with a totally new design from scratch.

Leading AI chip makers like Nvidia Corp. (NASDAQ: NVDA) will be analyzing the implications of this growing trend of tech leaders switching to in-house chips rather than purchasing from semiconductor companies.

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