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Addressing a critical barrier to enterprise AI adoption

Nick Payton
December 14, 2023

Our mission is to build software to help make AI safe, reliable and secure. Our vision is for this type of testing to enable safe use of AI across all use cases, maximizing its impact. We’ve assembled a founding team of researchers, engineers and leaders with experience designing these systems at Bloomberg, Google, Intel, Meta, SigOpt, Slack, Stripe and Uber. And we raised $11M in Seed funding led by Andreessen Horowitz to make this a reality for our enterprise customers. 

Our relationship with Andreessen Horowitz dates back to 2016 when they funded SigOpt, the AI startup that Scott Clark, Distributional’s CEO, co-founded, ran, scaled and sold to Intel in 2020. We’ve been lucky to work with and stay in touch with Martin Casado and Matt Bornstein as enterprise AI has evolved from one-off projects to at scale products, from random forests to transformers.

During this time, we’ve seen the potential for AI explode. AlphaFold solved protein folding to enable drug and materials discovery. Stable Diffusion reduced the marginal cost of image and video generation by orders of magnitude. And ChatGPT popularized these techniques for the masses – my parents are Plus users today. These are just a few examples and it feels like we have only scratched the surface on AI’s potential.

As the power of these systems grows, so does their potential for harm. If you can discover a new molecule to save a life, you can also discover a molecule to take one. Although examples from hard sciences are often more striking, this is also true in the enterprise. We’ve spoken to many companies who have shelved many of their AI products because they lack ways to understand the potential for this harm and mitigate it. 

Martin and Matt have heard similar stories and believe this is a critical problem to solve. And they wrote a post explaining their take that I encourage you to read. We are thrilled to partner with them to remove this substantial barrier to enterprise adoption of these powerful AI systems.

Read a16z’s post on investing in Distributional: https://a16z.com/announcement/investing-in-distributional/

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