AI + a16z

Pinecone Founder and CEO Edo Liberty joins a16z's Satish Talluri and Derrick Harris to discuss the promises, challenges, and opportunities for vector databases and retrieval augmented generation (RAG). He also shares insights and highlights from a decades-long career in machine learning, which includes stints running research teams at both Yahoo and Amazon Web Services.Because he's been at this a long time,  and despite its utility, Edo understands that RAG — like most of today's popular AI concepts — is still very much a progress:"I think RAG  today is where transformers were in 2017. It's clunky and weird and hard to get right. And it  has a lot of sharp edges, but it already does something amazing. Sometimes, most of the time, the very early adopters and the very advanced users are already picking it up and running with it and lovingly deal with all the sharp edges ..."Making progress on RAG, making progress on information retrieval, and making progress on making AI more knowledgeable and less hallucinatory and more dependable, is a complete greenfield today. There's an infinite amount of innovation that will have to go into it."More about Pinecone and RAG:Investing in PineconeRetrieval Augmented Generation (RAG)Emerging Architectures for LLM ApplicationsFollow everyone on X:Edo LibertySatish TalluriDerrick Harris Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

a16z General Partner Anjney Midha joins the podcast to discuss what's happening with hardware for artificial intelligence. Nvidia might have cornered the market on training workloads for now, but he believes there's a big opportunity at the inference layer — especially for wearable or similar devices that can become a natural part of our everyday interactions. Here's one small passage that speaks to his larger thesis on where we're heading:"I think why we're seeing so many developers flock to Ollama is because there is a lot of demand from consumers to interact with language models in private ways. And that means that they're going to have to figure out how to get the models to run locally without ever leaving without ever the user's context, and data leaving the user's device. And that's going to result, I think, in a renaissance of new kinds of chips that are capable of handling massive workloads of inference on device."We are yet to see those unlocked, but the good news is that open source models are phenomenal at unlocking efficiency.  The open source language model ecosystem is just so ravenous."More from Anjney:The Quest for AGI: Q*, Self-Play, and Synthetic DataMaking the Most of Open Source AISafety in Numbers: Keeping AI OpenInvesting in Luma AIFollow everyone on X:Anjney MidhaDerrick Harris Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

Naveen Rao, vice president of generative AI at Databricks, joins a16z's Matt Bornstein and Derrick Harris to discuss enterprise usage of LLMs and generative AI. Naveen is particularly knowledgeable about the space, having spent years building AI chips first at Qualcomm and then as the founder of AI chip startup Nervana Systems back in 2014. Intel acquired Nervana in 2016.After a stint at Intel, Rao re-emerged with MosaicML in 2021. This time, he focused on the software side of things, helping customers train their own LLMs, and also fine-tune foundation models, on top of an optimized tech stack. Databricks acquired Mosaic in July of 2023.This discussion covers the gamut of generative AI topics — from basic theory to specialized chips — to  although we focus on how the enterprise LLM market is shaping up. Naveen also shares his thoughts on why he prefers finally being part of the technology in-crowd, even if it means he can’t escape talking about AI outside of work.More information:LLMs at DatabricksMosaic ResearchMore AI content from a16zFollow everyone on X:Naveen RaoMatt BornsteinDerrick Harris Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

There are few terms in the world of AI — if any — that invoke more of a reaction than a simple four-letter word: Open. Whether it’s industry debates over business models and the actual definition of open, or the US government actively discussing how to regulate open models, seemingly everyone has an opinion on what it means for AI models to be open. The good, the bad, and the ugly.But to be fair, there’s good reason for this. In a world where many developers have come to expect open source tools at every level of the stack, the idea of powerful models locked behind enterprise licenses and corporate ethics can be disconcerting — especially for a technology as game-changing as AI promises to be. It’s a matter of who has the ability to innovate in the space, and whose release schedules and guardrails they’re beholden to.This is why, back in February, a16z convened a panel of experts to discuss the state — and future — of open source AI models.Featuring:Jim Zemlin (Executive Director, Linux Foundation)Mitchell Baker (Executive Chair, Mozilla Corp.)Percy Liang (Associate Professor, Stanford; Cofounder, Together AI)Anjney Midha (General Partner, a16z)Derrick Harris (Editorial Partner, a16z) Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

The AI + a16z podcast captures our thinking on AI across a broad swath of areas, from the infrastructure that powers today’s foundation models to how specific tools, like LLMs, are reshaping the hiring process. Looking forward, you can expect to hear about a list of topics that includes the latest advances in generative AI, cybersecurity, and the emerging stack of tools for building and running LLMs.Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.