Nvidia invests in Ilya Sutskever's AI lab, shifting SSI away from Google chips
Quick Answer
Nvidia has invested a substantial amount in Ilya Sutskever's AI lab, Safe Superintelligence (SSI), shifting its reliance from Google TPU chips to Nvidia's Vera Rubin GPU platform, which promises a tenfold increase in compute capacity.
Quick Take
This partnership aims to advance research in safe superintelligence while positioning Nvidia against Google in the competitive AI chip market.
Key Points
- SSI, founded in 2024, focuses on advancing safe superintelligence.
- Nvidia's Vera Rubin GPU platform will enhance SSI's compute capacity by tenfold.
- The partnership marks a strategic shift away from reliance on Google chips.
- SSI has raised about $2 billion from notable investors, valuing it at $30 billion.
- This investment helps Nvidia strengthen its position against Google in the AI sector.
📖 Reader Mode
~1 min readNvidia is pouring what it calls a "substantial" sum into Safe Superintelligence (SSI), the AI lab run by Ilya Sutskever, OpenAI's former chief scientist. Both companies announced the deal on Monday. They didn't disclose the exact amount.
As part of a long-term partnership, SSI gets access to Nvidia's next-generation Vera Rubin GPU platform, which the companies say will boost its compute capacity tenfold. Until now, the lab had relied mainly on Google's TPU chips, according to the Wall Street Journal. The deal also helps Nvidia fend off Google as a rival chip supplier during the current AI boom.
Sutskever said the research focuses on "overlooked aspects of how the human brain functions." SSI was founded in 2024 with a single stated goal: a "straight-shot" sprint toward safe superintelligence. The company raised about $2 billion from Andreessen Horowitz, Sequoia Capital, DST Global, and Greenoaks, and was most recently valued at roughly $30 billion.
— Originally published at the-decoder.com
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.
