Scale AI, a startup focused on data preparation for Artificial Intelligence, has raised $1 billion in a Series F round that values it at $13.8 billion – and which brought in new investors from Amazon, AMD, Intel, and Meta.
Scale AI was founded by MIT dropout Alexandr Wang, 27, who was 19 when he conceived the company. It has nearly doubled its valuation since April 2021, when it raised $325 million at a $7.3 billion valuation.
The round represents a resounding vote of confidence in the vision of Wang; who grew up in New Mexico, with parents who were weapons physicists working for Los Alamos National Lab – and who has built a customer base for Scale AI that includes the Department of Defense.
Scale AI’s customers have included Meta, Microsoft, OpenAI, and Toyota. The company did not respond to a request for comment on its revenues, but said it “supplies data to power nearly every leading AI model.”
Scale AI delivers reinforcement learning with human feedback (RLHF). i.e. If AI is built on data, compute, and algorithms, then its métier is the data element. It employs contract workers to clean and label data, as well as using RLHF; i.e. refining AI performance with human feedback.
Recent customer wins include the DoD's Chief Data and Analytics Office (CDAO), where Scale AI has landed a one-year contract to deliver "a framework to deploy AI safely by measuring model performance, offering real-time feedback for warfighters, and creating specialized public sector evaluation sets to test AI models for military support applications, such as organizing the findings from after action reports.”
As Wang put it in a 2023 podcast with lead investor Accel: “Our beginning thesis was that there needed to be an infrastructure platform like an AWS or Stripe to power the AI industry specifically focused on data…”
Emphasising the criticality of improved data, he added: “I think there's a lot of hype in the industry. I think in many cases for good reason, the technology is very impressive, but the models are still not good at various things. They still hallucinate, they're still not great at reasoning.
“[But] I think it's very clear that multimodality is going to continue improving. So models are going to get better at understanding images, they're going to get better at creating images, they're going to be better at the audio stuff is going to get better. And then maybe perhaps most impactfully, I think video, video models are going to keep improving pretty dramatically over time as well. So we're going to continue seeing not just text, but basically all the data formats that we as humans create and consume are going to be very convincingly generated by AI systems.”
Wang and his investors have built a formidable team including field CTO, Vijay Karunamurthy; a Sequoia Capital scout who was previously head of engineering at Apple and earlier Head of Search and Discovery at YouTube
Wang said in a May 21st blog on the Scale AI Series F funding round that “we believe the future of AI data in turn rests on three principles:
Data Abundance: We must build the data foundry that ushers in an era of AI-ready data abundance, and not resign ourselves to data scarcity.
Frontier Data: As we develop progressively more powerful AI, we must build frontier data which is always pushing the boundaries of AI capabilities towards complex reasoning, agents, multimodality, and more.
Measurement and Evaluation: We must build an evaluation system that enables measurement of AI to build confidence, drive adoption, and scale impact.
Scale AI’s funding round follows AI cloud infrastructure startup CoreWeave’s $1.1 billion raise at a $19 billion valuation earlier in May.
CoreWeave (the AI compute-focused startup to ScaleAI’s data-focused one) swiftly followed that with a $7.5 billion debt raise from Blackstone, as it looks to double its number of data centers to 28 this year.
CoreWeave, which is building out GPU-centric DCs for AI workloads, has raised more than $12 billion in equity and debt in 12 months.
