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Open Source Wins, AGI Is Here, and Scorsese's AI Toolkit with CEOs of Cerebras & Black Forest Labs
Brief
The episode moved from raw infrastructure to creative applications, with Cerebras CEO Andrew Feldman foregrounding the construction spree powering today's AI acceleration and Robin Rombach explaining how open visual models are evolving into multi‑modal systems that can drive real‑world action. Feldman emphasized the physical scale — football‑field sized data centers with city‑scale power draws — and urgent commercial demand: a roughly $25 billion Cerebras backlog and hyperscalers ordering chips before products ship. That pressure, he argued, makes fast inference the central constraint; extended internal token budgets and ‘‘unlimited’’ compute enable multi‑hour or multi‑day reasoning loops that amplify model capability. Feldman said Cerebras has broken the old Moore's Law trajectory for inference and expects more than 2× improvement in the next 18 months, claiming examples of orders‑of‑magnitude speedups on certain workloads.
The conversation then moved to safety, sovereignty and the model landscape. Feldman supported phased rollouts and government red‑teaming (citing recent regulatory scrutiny around frontier releases) while acknowledging polarization complicates policy. Both hosts and Feldman agreed that open source is essential for enterprise sovereignty — praising OSS 120B as a positive move — but also saw a two‑tier future: frontier closed models for the hardest problems and robust open models for mass automation. Rombach described Black Forest Labs’ evolution from latent diffusion and Stable Diffusion into multi‑modal, action‑predicting models intended to span image/video/audio and ultimately robotics. She recounted showing tools to Martin Scorsese to externalize cinematic visions, noted production use cases (backgrounds replacing green screens, fan films), and stressed human‑in‑the‑loop workflows and IP/licensing as key to commercial adoption. Overall, guests struck a cautious‑optimistic tone: they emphasized rapid, recursive capability gains and real risks (breaches, black‑swan events), but argued thoughtful engineering, staged safety testing, on‑prem/open options, and new creative workflows can steer the technology toward massive societal and industry benefits.
Why it matters
Andrew Feldman (CEO, Cerebras) says global AI data-center demand vastly outstrips supply — Cerebras currently carries roughly a $25 billion backlog and customers (OpenAI, Anthropic, Google, Microsoft, SpaceX AI, AWS) are ordering chips before designs are finished.
Key details
- Feldman argues inference (reasoning) is the new bottleneck: blazing-fast inference enables extended internal token use (‘‘unlimited tokens’’) for long-form reasoning, and Cerebras claims chip performance improvements that break traditional Moore’s Law — he expects >2× gains in the next 18 months and cited examples of up to ~15× faster runs for some workloads.
- Feldman and hosts contend we have effectively reached AGI by older definitions — reasoning agents now understand intent, vet strategies, and can perform recursive/looping improvements; they also urged staged rollouts and government red‑teaming for safety (Feldman supported phased releases and national-level vulnerability checks).
- Feldman and hosts described a global buildout of massive data centers — individual facilities the size of football fields with power needs comparable to mid-sized cities — being deployed across the U.S., Canada, Nordics, Europe, Middle East and unexpected locations (Georgia, Armenia, Kazakhstan, Tajikistan).
- Robin Rombach (co‑founder & CEO, Black Forest Labs) described her team’s roots in latent-diffusion (Stable Diffusion) and said Black Forest is building multi‑modal visual models that combine image, video, audio and action prediction so a single model can generate media and predict real‑world actions for robotics.
- Rombach confirmed active production and creative partnerships: Black Forest has offices in Freiburg (Black Forest) and San Francisco, crossed ~100 employees, is hiring researchers and infra engineers, and showed generative tools to Martin Scorsese to help him visualize scenes; she also noted real-world film uses (e.g., Gal Gadot’s Bitcoin film using AI backgrounds) and growing fan‑film ecosystems.