Facebook’s parent company is staking its future on a new compute cluster.

What’s new: Meta unveiled AI Research SuperCluster (RSC), which is designed to accelerate training of large models for applications like computer vision, natural language processing, and speech recognition.

How it works: The company began building RSC in 2020, aiming for a system capable of training trillion-parameter models and processing up to an exabyte (1 billion gigabytes) of data. It currently incorporates 6,080 Nvidia A100s, the chip vendor’s flagship graphics processing unit (GPU).

  • Compared to its unnamed predecessor, RSC can perform computer vision tasks up to 20 times faster and train large-scale natural language models three times faster. Meta plans to add 9,920 more GPUs this year to further accelerate training across the board.
  • Facebook highlighted the system’s data-protection features. Its previous research infrastructure used only publicly available data to avoid compromising user privacy. RSC is designed to process user data while maintaining privacy or security. The data it uses undergoes a privacy review process before processing and remains encrypted prior to training, and the storage infrastructure keeps the data separate from the wider network.
  • The ability to tap internal data is expected to supercharge development of multimodal AI and home robots.

Behind the news: RSC’s emphasis on data protection has a backstory. French regulators recently fined the company $238 million for failing to allow users to disable tracking software. In September, Ireland charged Facebook’s WhatsApp messaging service nearly $270 million for lack of transparency around how it uses the user data it collects. Those actions came after the U.S. Federal Trade Commission responded to violations of user privacy by imposing a historic $5 billion penalty as well as restrictions on the company’s structure and operations.

Why it matters: Specialized in-house processing capacity is a strategic asset in the era of cloud computing. RSC is essential to Meta’s aspiration to build an immense virtual reality community it calls the metaverse. Microsoft and Nvidia likewise have built their own bespoke infrastructure.

We’re thinking: Less than a decade ago, the cutting-edge AI supercomputer was a $100,000 cluster (that Andrew Ng worked on). How much bigger — and, unfortunately, less accessible — these systems have become!

Share

Subscribe to The Batch

Stay updated with weekly AI News and Insights delivered to your inbox