Blog

Scale – and its investors – are betting that the company can grow beyond a tool that helps customers prepare their data for AI and evolve into a software platform that plays a deeper role in developing their own custom AI.

Scale’s latest round was led by venture capital firm Accel and included additional commitments from investors such as Y Combinator, Founders Fund and Tiger Global Management.

New strategic investors included Cisco Investments, Amazon.com and the venture capital firms of chipmakers Qualcomm, Intel and Advanced Micro Devices. Existing investor Nvidia, the semiconductor giant, also participated in the round for the San Francisco-based startup.

Field Chief Technology Officer Vijay Karunamurthy spoke to the Wall Street Journal last week at the Collision conference in Toronto about Scale’s ambitions and how the company will use its new war chest in the AI ​​arms race. The interview has been edited for length and clarity.

WSJ: You’ve talked about being a platform that enables “artificial general intelligence” or AGI, where a machine can learn and think like a human. What does that mean for Scale AI and how are you collaborating with AI labs like OpenAI and Anthropic?

Karunamurthy: We’ve really changed our role and are now the “data foundry for AGI.” That’s the path we’ll be taking over the next few years. We’re working with pretty much all of the major (AI) research labs at one level or another. We’re seeing them increasingly interested, not just in specific capabilities, but in how to get a model that thinks about the world in general and answers questions reliably at a level where you can trust a human. That really has a huge impact on society. While the research labs are trying to keep up, we’re keeping our eye on the ball too.

WSJ: Why is data so important for the further development of generative AI, AGI and other future technologies?

Karunamurthy: As these models become more powerful and can store more knowledge and inferences, the amount of data required to saturate that model increases exponentially. That data needs to be diverse. We’re often asked today to build sophisticated datasets about how the world around us works. How do you answer a question about this table? Will the coffee stay in this cup if it’s tilted at a certain angle? That’s really important if we want to get robots to interact with the world around us. But the data is still lacking. Even if you think we’re still a long way from AGI, the next few years will still see advances in embodied agents that are able to use robotic arms or hands in a physical environment.

WSJ: What’s special about your recent $1 billion fundraise?

Karunamurthy: We wanted to bring in more strategic investors. All of their customers are asking about the data side of the equation. The (venture capital investments that companies make) are focused on how they can improve their product offerings to enterprises. I’ve met with some of our more strategic investors to see how we can partner with them. When you talk to Intel or Cisco, there’s a lot of emphasis on security and trust that their private knowledge that’s used to fine-tune these models doesn’t leave the boundaries of their company. They want to be able to audit access to these models and have strict access control.

WSJ: Scale has fresh capital. How is this being used throughout the company?

Karunamurthy: We’re hiring across the board – the number of full-time employees at Scale is up over 20% year-on-year. We’re also growing internationally. We just announced that London is our first official international office. We know there’s a lot of talent in London, and Europe in general has a wide range of AI talent, so some of the funding is going towards that expansion as well. A lot of our funding is helping to build out the human side of the equation and the model side of the equation. There’s a hybrid role that needs to be played with both people and technology.