Air Street Press

As an AI-native investor, we believe it’s important to be a hands-on contributor to the community. Since our earliest days, we’ve been building in public - whether that’s sharing our perspectives on the direction of the field, emerging best practice for building AI-first companies, organizing meet-ups, and campaigning for policy change.Air Street Press brings together all of our content under one umbrella. Subscribe to listen to our analysis, portfolio news, Guide to AI monthly newsletter, annual State of AI Report, and our policy work.

Air Street Press is a technology podcast hosted by Nathan Benaich (Air Street Capital), with 142 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Nathan Benaich (Air Street Capital) hosts Air Street Press, a technology show with 142 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Air Street Press

  AI needs science’s search history

  Aug 13, 202610 min

  Scientific papers preserve the happy path and lose the abandoned experiments and arguments that produced it. Starting with Alasdair Russell's genome editing group at the CRUK Cambridge Institute, Nathan Benaich examines whether scientific search histories could teach AI research taste. The essay explains why logs are not automatically training data, how selective labels hide the outcomes of rejected experiments, and what autonomous laboratories and Registered Reports can contribute. From Air Street Press. Subscribe at press.airstreet.com, read the State of AI Report at stateof.ai, and leave a rating - it helps the show.

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  Air Street Press

  Poolside’s model factory is shipping: Laguna S 2.1 and the Desktop Assistant

  Jul 29, 202610 min

  Poolside trained Laguna S 2.1 on 4,096 NVIDIA H200s and published the open weights sixty days later. The 118-billion-parameter mixture-of-experts model runs multi-hour autonomous coding sessions, handles up to a million tokens of context, and fits quantized on a single desktop-class machine. Nathan Benaich of Air Street Capital walks through the Model Factory that made that schedule possible, the system co-founders Jason Warner, GitHub’s former CTO, and Eiso Kant built to take a research idea to a production run in under a week. The episode covers the 409,000 training environments behind the model, the 50-minute session in which it built a browser rendering engine with no human intervention and no ability to see its own output, why the licenses attached to open weights differ so sharply between Poolside, Tencent and Moonshot, and what it means for a company to run a capable coding model inside its own security boundary rather than renting one through an API. Read the full piece: press.airstreet.com Poolside’s launch post: poolside.ai/blog/introducing-laguna-s-2-1 Evaluation trajectories: trajectories.poolside.ai RAAIS 2025 - Eiso Kant, Inside poolside’s path to AGI: press.airstreet.com/p/eiso-kant-poolside-ai-raais-2025 From Air Street Press. Subscribe at press.airstreet.com, read the State of AI Report at stateof.ai, and leave a rating - it helps the show.

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  Air Street Press

  Black Forest Labs FLUX 3: from video generation to robot control

  Jul 27, 20267 min

  Description: Black Forest Labs has launched FLUX 3, a multimodal foundation model that learns jointly from images, video and audio within a single architecture, and mimic robotics has released FLUX-mimic, a video-action model built on that backbone and being tested on real assembly work in Audi's Production Lab. Nathan Benaich of Air Street Capital, an investor in Black Forest Labs, reads his Air Street Press essay on why a model trained to predict how scenes evolve turns out to be a usable robot controller. Covers the FLUX 3 preference results against Runway Gen-4.5, Grok Imagine Video, Kling v3 Pro, Seedance 2.0 and Gemini Omni Flash; how a lightweight action decoder reads the video prediction path without ever generating video; the frozen-backbone ablation against π0.5; the 101-millisecond system reaction time on a single RTX 5090; and what Air Street's own robotics deal flow says about where the constraint really sits. Chapters (estimated at ~150 wpm, slide proportionally against final audio): 0:00 A robot arm in Audi's Production Lab 0:40 What Black Forest Labs and mimic released 1:20 Early access and open weights 1:50 The preference-test results 2:40 What a model must represent to predict video 3:30 Reading actions off the video path 4:20 The frozen-backbone ablation 5:00 101 milliseconds, and the Audi tasks 5:50 What we see in robotics deal flow 6:30 The road to physical intelligence Links: FLUX 3 · FLUX-mimic (BFL) · FLUX-mimic (mimic) · Odyssey Series B · BFL Series B ·

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  Air Street Press

  The case for intelligence beyond language

  Jul 21, 20267 min

  Raia Hadsell, VP of Research at Google DeepMind, makes the case that intelligence is more than language: the same recipe that learns the patterns of text can learn the patterns of any complex system. She walks through DiffusionGemma and text diffusion, the Genie world models, and DeepMind's robotics stack, where world models now generate training data you cannot tell from the real thing. Recorded at RAAIS 2026. Timestamps 0:00 Introduction (Nathan Benaich) 0:35 From philosophy to DeepMind: the frontiers of intelligence 2:37 The twenty-year lesson: one recipe for complex systems 4:34 DiffusionGemma and the Gemma 4 open models 5:32 How text diffusion works 7:34 Speed, self-correction, and the sudoku test 10:51 World models: better agents need better worlds 12:56 Genie 1 to Genie 3 15:01 Genie 3 demos: typing a world into being 18:20 World models for education 19:38 Grounding Genie in Street View 20:41 Robotics: a brain and a spine 23:14 Gemini Robotics-ER 1.6 and Boston Dynamics' Spot 24:42 The vision-language-action model 25:45 The data bottleneck and closing the loop 27:24 Beyond language: the domains still to crack

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  Air Street Press

  Europe’s air defense gap

  Jul 16, 20267 min

  At RAAIS 2026, Nathan Benaich sits down with Hadrien Canter, co-founder and CEO of Alta Ares, the air-defense company building AI-guided interceptors to shoot down cheap drones and cruise missiles. They get into why Europe has lost air superiority for the first time in modern history, what the data loop looks like when you run it on a freezing front line instead of a laptop, why "quantity is the quality" in the industrialization race, and how the talent pool is shifting toward European defense. Recorded live at RAAIS 2026 in London. Chapters 00:00 — Introducing Hadrien Canter and Alta Ares 00:47 — 2022 in Ukraine, and how Europe lost air superiority 03:23 — The Series A and the Airbus partnership 05:13 — The data loop, edge AI, and the three phases of a mission 08:22 — What no simulation can reproduce 10:09 — Hiring for the mission; defense as the precondition for peace 12:36 — Open research questions and the human in the loop 14:22 — How the adversary uses AI: evasive Shaheds, drone mesh, China 17:27 — Two interceptors, and why quantity is the quality 20:50 — Iron Dome math, budgets, and peace-time vs war-time 23:41 — Q&A: keeping pace with a fast-changing front 26:31 — Q&A: talent and the shift toward European defense 29:30 — Q&A: re-arming without permanent war 32:56 — Freedom doesn't come for free

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