Founders Everywhere: Liz O'Sullivan and Justin Norman
Liz O'Sullivan and Justin Norman are the co-founders of Vera, the world's first conversational assistant to enforce and automate your privacy, security, and performance policies in enterprise AI.
Welcome to Founders Everywhere, where we highlight the incredible people behind the companies we’ve backed at Everywhere Ventures, a global pre-seed fund supported by a community of 500 founders and operators.
Artificial Intelligence (AI) is the talk of the
town world. It’s permeating every sector and transforming the way we live and work. It stands at the forefront of innovation, sparking conversations about its capabilities, ethical considerations, and the future it holds for humanity. As AI technology continues to advance, particularly generative AI, so do the associated threats and challenges. Vera is empowering enterprises to navigate the complexities of AI, allowing them to leverage its benefits while proactively managing the risks associated with its use, whether in shaping policies, ensuring compliance, or moderating interactions.
Vera’s co-founders Liz O'Sullivan, CEO, and Justin Norman, CTO, are seasoned experts in the field of AI. Liz has over a decade of experience on the business side of enterprise AI startups and was the co-founder of model monitoring startup Arthur AI. She’s currently a member of the National AI Advisory Committee (NAIAC) through the Department of Commerce, and facilitated by The National Institute of Science and Technology. Justin is a data science leader, having built teams at Fitbit and Yelp before pursuing an AI PhD at UC Berkeley. This year, Justin was appointed to the Navy Science and Technology board. They teamed up to create Vera in 2022 to become the guardrails that make companies feel more safe when they get ready to enact their generative AI strategies. Liz and Justin share more about how Vera is making it easy for companies to deploy safe, reliable AI.
What is Vera’s North Star?
We're on a mission to fix AI so it works for everybody. We aim to be transparent about AI's limitations, help companies understand and craft policies that leverage its benefits while avoiding potential harm.
What makes Vera a must-have vs a nice-to-have?
Generative AI has taken the field to a whole new level, with capabilities to do things that we weren't sure were even possible. At the same time, you see a lot of research and viral posts about the ways that it can create real harm. Earlier this year, a man committed suicide after an AI chatbot encouraged him to sacrifice himself to stop climate change. And that's just one of the many ways that this technology can cause harm, damage or risk. If you're a big enterprise and you are thinking about embedding AI, especially if it's in a customer facing capacity, you can't take these things lightly. It's something you really need to be proactive about and Vera serves as a crucial tool in the process of understanding and creating policies around AI.
What have been some of the greatest challenges founding Vera?
We see a lot of extremes in this space. On one end, we see people who believe that AI is going to solve every single problem and on the flip side, there are those who deem AI entirely useless and damaging. Categorically labeling AI as purely good or bad is incorrect, as its effectiveness depends on the specific applications. It's crucial to adopt a practical and realistic approach, acknowledging both the benefits and limitations of current AI capabilities. The focus should be on fostering reasonable discussions about policy and governance, rather than sensationalizing risks of extinction or potential consciousness, which represent only a fraction of actual concerns in AI practices. The real challenge lies in managing and preventing the unpredictable behaviors that AI can exhibit.
Tell us about some recent milestones Vera crushed.
We announced our $2.7 million raise in October, which will support the growth of our team, research and development efforts, and the expansion of enterprise deployments.
We’re also really excited to be in closed beta and deploying the platform off of our growing waitlist.
We also launched some new features that can optimize Generative AI model costs, by routing prompt requests to the model best fit for the job.
Any favorite books?
Liz: One of my favorites is Janelle Shane’s, You Look Like a Thing and I Love You. It's an artistic rumination on AI’s current state and demonstrates just how weird AI can get and I love it. But some more serious books that are definitely worth the read are Cathy O'Neil's Weapons of Math Destruction and Meredith Broussard’s Artificial Unintelligence and I’m excited to check out her newest book More Than a Glitch. But I think Do Androids Dream of Electric Sheep by Philip K. Dick will always be my favorite!
Justin: On the research side of things, Ian Goodfellow's foundational Deep Learning is something you'll always find on my desk, with lots of bookmarks. On the other hand Adam Grant's Think Again and Stacy Abrams' Lead from the Outside both remind me to explore and even embrace alternative ideas and organizational designs. For fun, I find myself coming back to Samuel R. Delany's classic, The Einstein Intersection.
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