"‘Startups Don’t Need to Spend Big to Get Big Results,’ Says CEO Robert Nishihara as Ray Summit Highlights AI Innovations"

The relentless complexity of AI infrastructure is a barrier for many companies eager to harness the power of artificial intelligence. From scaling AI platforms to managing distributed computing, developers often find themselves stuck in technical challenges, rather than focusing on innovation. This is the very problem Anyscale, a cutting-edge enterprise tech company, set out to solve when it was founded in 2019.

In the words of Robert Nishihara, Anyscale’s co-founder and CEO: "We started Ray and Anyscale because of our own experience struggling with the scaling challenges around machine learning. It’s striking to see how far the project has come, with industry leaders like Uber, OpenAI, Shopify, and ByteDance building their next-generation ML platforms using Ray."

Born from Scaling Challenges at Berkeley

The idea behind Anyscale began long before the company itself. It traces its origins to the University of California, Berkeley’s RISELab, where Nishihara and his co-founders, Ion Stoica, and Philipp Moritz, were grappling with the difficulties of scaling AI workloads. They identified a gap in the available tools, particularly in distributed computing for machine learning (ML), which led them to create Ray, an open-source project that would eventually serve as the bedrock for Anyscale.

Ray, introduced in 2017, was a game-changing distributed compute framework designed to handle machine learning workloads at scale, simplifying the task for developers who lacked large infrastructure teams. Ion Stoica, Anyscale's co-founder and executive chairman, highlighted the project's importance: "Scaling applications on clusters is a daunting challenge for machine learning engineers who don’t have teams of infrastructure experts behind them. The time wasted on low-level engineering would be better spent on designing algorithms."