Why are Alphabet, Nvidia and Google Cloud Investing in SSI?

Global concern over AI safety has escalated to the global stage, from court cases over AI-generated misinformation to government-backed initiatives like the UK’s AI Safety Institute and multilateral efforts such as the International AI Safety Report involving 30 nations.

Tech giants including OpenAI and Google are also stepping up risk testing and safety research.

Now, Alphabet and Nvidia have joined a group of venture capital firms investing in Safe Superintelligence (SSI), a startup co-founded by former OpenAI Chief Scientist Ilya Sutskever.

Despite launching only months ago, SSI has swiftly become one of the most valuable companies in the AI space.

What is SSI and its impact on the AI market?

SSI was established in early 2025 with the explicit mission of developing advanced AI systems prioritising safety and aligning with human values.

The company's name reflects its core focus: creating super intelligent AI systems – those potentially capable of outperforming humans across virtually all cognitive tasks – while implementing rigorous safety protocols to prevent unintended consequences.

Ilya, widely regarded as one of the pioneers in deep learning research, departed OpenAI in March 2025 to found SSI.

Then his move sent ripples through the AI industry, as he had been instrumental in developing several breakthrough models at OpenAI, including the GPT series of large language models (LLMs).

The high-profile departure followed reported disagreements within OpenAI's leadership about the pace of AI development and the appropriate balance between commercial objectives and safety considerations.

This led Ilya to assemble a team of prominent AI researchers who share his conviction that super intelligent systems can be developed safely, but only with dedicated research focus on the alignment problem – ensuring AI systems reliably pursue goals that align with human intentions.

Now, SSI, which sources indicate was recently valued at US$32bn in a funding round led by Greenoaks Capital, has emerged as a prominent startup in AI model research, largely due to Ilya's background in identifying emerging trends in AI development.

The company requires significant specialised computing hardware to advance its research, which centres on creating artificial general intelligence (AGI) capable of performing any intellectual task a human can, while incorporating robust safety measures.

What big players are investing in SSI and why? 

The investments in SSI represent the growing trend and concern with AI safety and a renewed focus on investments in startups developing frontier AI systems.

Google Cloud
Google Cloud announced an agreement to sell SSI access to tensor processing units (TPUs), Google's proprietary AI chips designed specifically for machine learning (ML) workloads.

The investment also ensures Google's cloud infrastructure and TPU chips remain central to cutting-edge AI development.

Alphabet
Additionally, investment by Alphabet and Nvidia in SSI represent more than financial backing – but strategic positioning in the evolving field of advanced AI systems too.

For Alphabet, which already operates Google DeepMind, its own frontier AI research division, the investment in SSI provides access to complementary research and potential technological innovations.

Nvidia
Meanwhile, Nvidia's stake in SSI follows a pattern of strategic investments in leading AI research entities.

As the primary supplier of graphics processing units (GPUs) that power most AI training workloads, Nvidia benefits from maintaining close relationships with companies likely to require substantial computing resources.

Google’s TPUs vs Nvidia's GPU dominance

More broadly, the dual approach from Alphabet's corporate investment arm and cloud division with prominent AI research groups, including SSI and Anthropic, indicates an evolution in Google's AI hardware strategy.
Google initially reserved its TPUs exclusively for internal projects.

Now, the agreement to provide SSI with significant quantities of these specialised chips to support advanced AI research demonstrates its strategy to expand availability to external customers.

“With these foundational model builders, the gravity is increasing dramatically over to us,” says Darren Mowry, a Managing Director responsible for Google's partnerships with startups, in an interview with Reuters.

AI developers have historically favoured Nvidia's graphics processing units (GPUs), which control more than 80% of the AI chip market.

However, two sources told Reuters that SSI is primarily utilising TPUs rather than GPUs for its AI research and development efforts.

Yet Google offers both Nvidia GPUs and its own TPUs through its cloud computing platform.

This means that the company's proprietary chips are engineered to excel at specific AI functions and offer greater efficiency compared to general-purpose GPUs.

These processors are employed to develop large-scale AI models for companies including Apple and Anthropic, an OpenAI competitor with billions in funding from Google and Amazon.

“With these foundational model builders, the gravity is increasing dramatically over to us,” says Darren.

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