Meta wants to use exotic, custom CPUs in its data centers for machine learning and AI – another indication that Nvidia’s most formidable rivals are developing their own alternatives to their hardware
We previously reported that Meta Platforms, Facebook’s parent company, plans to deploy its own custom-designed artificial intelligence chips, codenamed Artemis, into its data centers this year, but would also continue to use Nvidia H100 GPUs for the foreseeable future at least.
However, The register now claims that job openings for ASIC engineers with expertise in architecture, design and testing have been spotted in Bangalore, India, and Sunnyvale, California, indicating that Meta plans to develop its own AI hardware.
The job descriptions reveal that Meta is looking for professionals to “help design state-of-the-art machine learning accelerators” and to design complex SoCs and IPs for data center applications. Some of these positions were first posted on LinkedIn in late December 2023 and reposted two weeks ago, with the positions in Sunnyvale offering salaries approaching $200,000.
Artificial general intelligence
While the exact nature of Meta’s project has not yet been specified, it is likely related to the company’s previously announced ‘Meta Training Inference Accelerators’, which will be launched later this year.
Meta’s ambitions also extend to artificial general intelligence, an endeavor that could require specialized silicon.
With the increasing demand for AI and Nvidia’s struggle to meet this demand, Meta’s move to develop its own technology is a strategic move to ensure it doesn’t have to compete with rivals for hardware in a super-hot market.
The Register reports that the Indian government is likely to welcome Meta’s decision to advertise in Bangalore as the country aims to become a major player in the global semiconductor industry.
Furthermore, rumors suggest that Microsoft is also reducing its dependence on Nvidia by developing a server network card to optimize machine learning workload performance. This trend suggests that Nvidia’s most formidable rivals are looking for ways to reduce their dependence on its hugely in-demand hardware.