SHOW DIRECTORY
The a16z Show
The venture firm’s view of startups, AI, software, markets, company building, and the technological shifts creating new categories.
BIDCLUB DESCRIPTION
The Chip That Could Unlock AGI.
Unconventional is pursuing physical learning circuits, arguing that analog dynamics could complement digital computing for stochastic, time-dependent workloads rather than simply extend matrix multiplication.The thesis targets an energy wall: U.S. data centers use roughly 4% of the national grid, while some estimates call for 400 additional gigawatts over the next decade.Commercial significance depends on finding a manufacturable paradigm within five years, with TSMC partnership, a potentially very large analog prototype and unresolved AGI claims creating major execution risk.
"Is there an AI bubble?” Gavin Baker and David George
Gavin Baker argues AI does not resemble 2000: NVIDIA trades near 40 times trailing earnings versus Cisco’s 150–180 times, GPUs are fully utilized, and major buyers’ ROIC has risen roughly 10 points.The open risk is whether returns persist through Blackwell spending, while Google’s TPU competition, incumbent distribution, and outcome-based pricing could reshape infrastructure, SaaS margins, and AI monetization.
Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
Raghu RaghuramAmin VahdatJeetu Patel
AI infrastructure demand is outpacing deployment: Google’s seven- and eight-year-old TPUs remain at 100% utilization, while power, permitting, land, and supply chains may constrain trillions in committed spending for 3–5 years.Specialized silicon, distributed networking, and inference-native systems could deliver 10–100x efficiency gains, but bursty workloads and the need for full-stack co-design make utilization, architecture, and durable product differentiation central risks.
Dylan Patel on GPT-5’s Router Moment, GPUs vs TPUs, Monetization
Dylan PatelErin Price-WrightGuido AppenzellerErik Torenberg
GPT-5’s router is an economic release, directing simple queries to mini models while reserving “ungodly amounts of compute” for transactions OpenAI could monetize through agentic commerce.Flat-rate subscriptions face heavy-user losses, while custom silicon threatens Nvidia mainly if demand stays concentrated among hyperscalers; powered sites, grid equipment, and Intel’s capital needs remain near-term constraints on broader deployment.
From the Dot-Com Crash to the AI Era: How Builders Survive Waves of Disruption
Martin CasadoRaghu RaghuramJeetu Patel
VMware’s cycle shows how a software abstraction can disrupt an incumbent before AWS retains the virtual machine and captures developers, a constituency VMware “had no idea how to work with.”Cisco’s reset targets market in nine months, $1 billion in three to four years, and 8–10 repeatable winners by combining protected two-pizza teams with scaled distribution.AI could expand infrastructure demand 100–1,000x as agents create sustained inference workloads, but vertical integration must remain open enough to include competitors such as Microsoft Teams.
What DeepSeek Means For The Future Of AI | Tech Veterans Weigh In
Steph SmithMartin CasadoSteven Sinofsky
DeepSeek R1’s permissive MIT-like license and released reasoning traces enable broad adoption and distillation into smaller models, shifting strategic advantage toward distribution and “AGI in your pocket.”Model value may migrate from benchmark leadership to stateful workflows as competitors catch up, while scale-out expands endpoints without eliminating hyperscale compute.The clearest policy signal is that chip and open-source restrictions did not prevent capable Chinese research, making faster domestic innovation and permissionless diffusion the unresolved US advantage.





