AI represents a generational shift in computing — following in the footsteps of the microprocessor and the internet — and it will deliver commensurate improvements in cost, efficiency, and human productivity.
At a16z Infra, we believe that infrastructure underpins this coming shift just as it does for many other transformational technologies. That’s why we invest in founders and companies building at every level of the stack: from foundation models, core AI systems, and developer tools, to next-gen cloud, data, and security systems.
Braintrust is a devtool platform for any product effort — from simple apps to sophisticated products — based around large language models.
Bowen Peng and Jeffrey Quesnelle of Nous Research discuss their mission to accelerate open source AI research, including with a new project called DisTrO.
Fei-Fei Li and Justin Johnson are pioneers in AI. While the world has only recently witnessed a surge in consumer AI, our guests have long been laying the groundwork for innovations that are transforming industries today...
Ambience cofounder Nikhil Buduma discusses how to build vertical applications with AI models, including in health care, and why tech expertise isn't enough.
Fei-Fei Li and are team of experts at World Labs are building a spatial intelligence model that can generate 3D worlds that users can interact with.
Mintlify lets companies publish quality software documentation that aligns with their brands, including guides, API reference, and examples.
MotherDuck CEO Jordan Tigani discusses DuckDB's spiking popularity as the era of big data wanes, as well as the nexus of SQL and LLMs.
Pylon provides a single view of customer issues, wherever they are happening — Slack, Teams, chat widget, ticket forms, or emails.
Cursor is a fork of VS Code that’s heavily customized for AI-assisted programming, with loads of features designed to integrate AI into developer workflows.
Black Forest Labs founders Robin Rombach, Andreas Blattmann, and Patrick Esser discuss their new company building state-of-the-art image and video models.
Vijay Pande walks us through two decades of applying software engineering and AI to biotech and health care — from Folding@Home through AlphaFold and more.
PromptFoo creator Ian Webster discusses the importance of red-teaming for AI safety and security, and of bringing those capabilities to more organizations.
We're excited to announce our investment in Black Forest Labs (BFL), which is building the world’s best open visual models for developers.
Martin Casado and Ion Stoica argue that open-source models will power innovation without compromising security.
Command Zero CTO Dean de Beer discusses how large language models can help with cybersecurity incident response, and how to build products on LLMs.
Anyscale's Robert Nishihara discusses the challenges of training and running AI models at scale, and how a focus on video data will change generative AI.
Jiaming Song and Anjney Midha discuss Luma's Dream Machine 3D model that shows abilities to reason about the world across a variety of aspects.
Alasdair Monk discusses how generative AI is changing how developers — and the those building for developers — interact with the tools of their trade.
Senate Bill 1047 is designed to apply to models trained above certain compute and cost thresholds. It also holds developers legally liable for the downstream use or modification of their models.
In this AI + a16z episode, Inngest CEO Tony Holdstock-Brown discusses the reality of running AI agents and multistep AI workflows in production.
In this AI + a16z podcast episode, Mohammad Norouzi shares his story of building influential text-to-image models at Google and cofounding Ideogram.
We stitched together two episodes from the a16z Podcast, featuring Anjney Midha interviewing Arthur Mensch (Mistral) and Stefano Ermon (Stanford).
In this episode of the AI + a16z podcast, a16z partners Guido Appenzeller and Matt Bornstein discuss the state of the generative AI market, about 18 months after it really kicked into high gear with the release of ChatGP...
The stakes are high. The opportunities are profound. From the creation of new medicines to bolstering national defense, this is our vision for the AI-enabled future.
Regulators influenced by the big companies create barriers to entry for "little tech" and curtail innovation.
Security-startup founders Dean De Beer (Command Zero), Kevin Tian (Doppel), and Travis McPeak (Resourcely) share their thoughts on generative AI.
Mature code-generation technology, coupled with advanced generative AI image models, has shortened the journey from idea to fully operational application.
In 2009 Discord cofounder and CEO, Jason Citron, started building tools and infrastructure for games. Fast forward to today and the platform has over 200 million monthly active users. In this episode, Jason, alongside a1...
In this AI + a16z episode, a16z's Zane Lackey and Joel de la Garza discuss how generative AI and LLMs could effect profound change in cybersecurity.
Human nature fears the unknown, and with the rapid progress of AI, concerns naturally arise. Uncanny robocalls, data breaches, and misinformation floods are among the worries. But what about security in the era of large...
In this episode of the AI + a16z podcast, Socket's Feross Aboukhadijeh and a16z's Joel de la Garza discuss the open-source software supply chain.
Pinecone Founder and CEO Edo Liberty discusses the promises, challenges, and opportunities for vector databases and retrieval augmented generation (RAG).
Anjney Midha shares his thoughts on how hardware for AI might evolve over the years to come as we place more emphasis on AI inference workloads.
Jennifer Li is being promoted to General Partner at a16z. She will continue to invest broadly within the enterprise space, focusing on infra.
Naveen Rao of Databricks joins a16z's Matt Bornstein and Derrick Harris to discuss where we're at in terms of large language model (LLM) adoption.
This episode of the AI + a16z podcast features a panel discussion from back in February, focused on the state — and future — of open source AI models.
a16z's Martin Casado lays out the case for AI as a driving force behind incredible advancements in tech, creativity, and the human experience.
a16z announces its second batch of a16z Open Source AI Grant recipients. This cohort focuses mainly on LLMs and visual AI models.
Arthur Mensch is the co-founder of Mistral and the co-author of Deepmind’s pivotal 2022 "Chinchilla" paper. In September 2023, Mistral released Mistral-7B, an advanced open-source language model that has rapidly become the top choice for developers. Just this week, they introduced a new mixture of experts model – Mixtral — that’s already generating significant buzz among AI developers. As the battleground around large language models heats up, join us for a conversation with Arthur as he sits down with a16z General Partner Anjney Midha. Together, they delve into the misconceptions and opportunities around open source; the current performance reality of open and closed models; and the compute, data, and algorithmic innovations required to efficiently scale LLMs.
No one knows how generative AI will play out from a product perspective. The speakers at our Connect/Enterprise event shared their thoughts and experiences.
To date, a handful of large companies have captured the value created by advances in AI. With generative AI, that’s changing.
As CTO of OpenAI, Mira Murati oversaw the development and release of GPT-4 and ChatGPT. Here she tells Martin Casado the story behind the release of ChatGPT—and what it tells us about the future of AI and human-machine interactions.
a16z announces its Open Source AI Grant program, which will support a small group of open source developers through grant funding.
With generative AI, we’re already seeing use cases with orders-of-magnitude improvement in time, cost, and performance over previous AI waves.
A very simple “getting started with AI” template for those who want to play with core technologies, but not have to think too much about tooling.
A reference architecture for the LLM app stack. It shows the most common systems, tools, and design patterns used by AI startups and tech companies.
A curated list of resources we’ve relied on to get smarter about modern AI, including generative AI, LLMs, and transformer models.
Composable customer data platforms are taking advantage of a shift in data infrastructure and embracing a “warehouse-first” architecture.
Highlights from the a16z Data and AI Forum, featuring founders building products across the spectrum of data and AI use cases.
The generative AI boom is compute-bound and, as a result, a predominant factor driving the industry is simply the cost of training and inference.
We're starting to see the very early stages of a tech stack emerge in generative artificial intelligence (AI). Hundreds of new startups are rushing into the market to develop foundation models, build AI-native apps, and...
Understanding how to build a company in the face of a new, immature, or non-existent market is a topic startups should obsess about.
Why AI models will replace artists long before they'll replace programmers
Vertical clouds are on the rise, as traditional clouds give way to specialization.
The pressure the cloud puts on margins can start to outweigh the benefits you scale and growth slows. Understand how much market cap is being suppressed by the cloud to help inform the decision-making framework on managing infrastructure as companies scale.
To help data teams stay on top of the changes happening in the industry, this article reviews an updated set of data infrastructure architectures.
The stakes are high. The opportunities are profound. Explore our vision for the AI-enabled future.
START LISTENINGWe’re former founders leveraging our know-how to invest in entrepreneurs building at every level of the AI stack: from foundation models, core AI systems, and developer tools, to next-gen cloud, data, and security systems.
See Full TeamAny investments or portfolio companies mentioned, referred to, or described on this page are not representative of all investments in vehicles managed by a16z and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. Exits include current and former a16z portfolio companies which have been acquired as well as companies which have undergone an initial public offering or direct public offering of shares. Certain publicly traded companies on this list may still be held in Andreessen Horowitz funds. A list of investments made by funds managed by a16z is available here: https://a16z.com/investment-list/. Excluded from this list are investments for which the issuer has not provided permission for a16z to disclose publicly as well as unannounced investments in publicly traded digital assets. Further, the list of investments is updated monthly and as such may not reflect most recent a16z investments. Past results of Andreessen Horowitz’s investments, pooled investment vehicles, or investment strategies are not necessarily indicative of future results.