The a16z Show

As part of our summer replay series, we're revisiting one of our favorite conversations on the future of AI infrastructure. SemiAnalysis founder Dylan Patel joins Erin Price-Wright, Guido Appenzeller, and Erik Torenberg to examine the rapidly evolving economics of AI hardware, from GPUs and custom silicon to data centers, power, and the global race for compute. The conversation explores NVIDIA's competitive advantages, the rise of custom chips from Google, Amazon, and Meta, the economics of frontier AI models, and the infrastructure constraints shaping the industry's next phase. They also discuss AI startups, export controls, robotics, enterprise software, and why simply copying NVIDIA isn't enough to build a winning AI hardware company. Whether you're building AI products, investing in infrastructure, or trying to understand where the industry is headed, this conversation offers a practical look at the forces shaping the future of compute.

As part of our summer replay series, we're revisiting one of the standout conversations from Runtime, a16z's conference on AI infrastructure and the future of computing. Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George to examine the biggest questions surrounding today's AI investment cycle. Is AI a bubble? What does the unprecedented buildout of data centers, GPUs, and compute infrastructure mean for the economy? And how should investors think about the companies building the next generation of AI? The conversation explores frontier models, Nvidia, Google, custom silicon, AI infrastructure, application software, robotics, and why Baker believes today's AI investment cycle looks fundamentally different from the internet bubble of the early 2000s. Along the way, they discuss the economics of GPUs, enterprise software, AI business models, and what comes next as AI moves from experimentation into the broader economy.

Every blockchain today relies on replication techniques first developed in the 1980s by researchers who weren't thinking about cryptocurrencies at all. In this episode, Tim Roughgarden speaks with MIT professor and Turing Award winner Barbara Liskov, one of the pioneers of programming languages, fault tolerance, and distributed systems. Joined by a16z crypto research partner Ittai Abraham, they trace the evolution of ideas that now underpin modern blockchain networks. The conversation explores viewstamped replication, Practical Byzantine Fault Tolerance (PBFT), state machine replication, and why concepts developed decades before Bitcoin became the foundation for today's blockchain protocols. Along the way, Liskov reflects on the relationship between theory and practice, the importance of modularity and formal reasoning, and why AI is creating a new generation of systems research.

We're excited to share a special feed drop from The a16z Crypto Show. In the first episode of First Principles: The Scientific Roots of Blockchain Technology, Tim Roughgarden and Ittai Abraham trace the decades of computer science research that laid the foundation for modern blockchains. Long before Bitcoin, researchers were studying one of distributed computing's hardest challenges: how independent machines can reliably agree on a shared state, even when some participants are faulty or malicious. Bitcoin didn't invent that problem, but it introduced a breakthrough solution in a radically different, permissionless setting. The conversation explores Byzantine agreement, state machine replication, proof of work, proof of stake, Tendermint, Casper, DAG-based protocols, and why concepts developed decades ago continue to shape the design of today's fastest and most secure blockchain networks.

As part of our summer replay series, we're revisiting one of our favorite conversations from the past year. Mark Zuckerberg and Dr. Priscilla Chan join Ben Horowitz, Vineeta Agarwala, and Erik Torenberg to discuss the Chan Zuckerberg Initiative's ambitious effort to help cure, prevent, and manage disease by the end of the century. Rather than funding individual breakthroughs, CZI is focused on building the tools and infrastructure that can accelerate scientific discovery across entire fields. The conversation explores Biohub, Cell Atlas, virtual cell models, open biological datasets, and the growing role of AI in helping researchers better understand human biology. They discuss why biology still lacks a "periodic table of elements," how AI could help scientists test hypotheses before running expensive experiments, and why pairing frontier biology with frontier AI may unlock a new era of medical discovery.