Facebook Inc is building a team to design its own semiconductors, adding to a trend among technology companies to supply themselves and lower their dependence on chipmakers such as Intel Corp and Qualcomm Inc, according to job listings and people familiar with the matter.
The social media company is seeking to hire a manager to build an “end-to-end SoC/ASIC, firmware and driver development organization,” according to a job listing on its corporate Web site, indicating the effort is still in its early stages.
A system on chip, or SOC, is a type of semiconductor that contains several discrete components built into one piece of silicon. They are typically used in mobile devices, where their space and power-saving properties are more valuable.
An application-specific integrated circuit, or ASIC, is a chip designed for a narrow purpose. Such components are often the fastest or most efficient at running a particular piece of software.
Facebook would join other technology giants tackling the massive effort to develop chips.
In 2010, Apple Inc started shipping its own chips and now uses them across many of its major product lines.
Alphabet Inc’s Google has developed its own artificial intelligence (AI) chip as well.
Facebook could use such chips to power devices, AI software and servers in its data centers.
Next month, the company is to launch the Oculus Go, a US$200 standalone virtual-reality headset that uses a Qualcomm processor.
Facebook is also working on a slew of “smart” speakers.
Future generations of those devices could be improved by custom chipsets. By using its own processors, the company would have finer control over product development, and would be able to better tune its software and hardware together.
Facebook declined to comment on the job postings.
The postings did not make it clear to what kind of use Facebook wants to put the chips, other than the broad umbrella of AI.
A job listing references “expertise to build custom solutions targeted at multiple verticals, including AI/ML,” indicating that the chip work could focus on a processor for AI and machine learning tasks.
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