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1:01:26EN
Cognitive Revolution "How AI Changes Everything"· Jul 25, 2023PodcastAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.Host Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.
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Matthew Berman· Jul 18, 2023Petals: Distributing Large Language Model Inference Across DevicesMatthew Berman · Forward FutureIn 2023, Matthew Berman explains Petals as a way to use large models through a network of participating computers rather than loading every layer on one device.
9:33ENMatthew Berman· Jun 30, 2023Testing SDXL 0.9: Image Quality, Clipdrop and a Midjourney ComparisonMatthew Berman · Forward FutureIn June 2023, Matthew Berman tries Stability AI’s image model, compares selected prompts with Midjourney and demonstrates Clipdrop’s lighting tool.
7:21ENMatthew Berman· Jun 26, 2023Testing Orca Mini 13B, an Unofficial Model Inspired by OrcaMatthew Berman · Forward FutureMatthew Berman loads a quantized Orca Mini 13B and tries coding, reasoning, arithmetic, and summarization prompts. His 2023 informal test produces several failures and a few successes.
8:17ENMatthew Berman· Jun 22, 2023Using OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.
1:20:49ENCognitive Revolution "How AI Changes Everything"· May 25, 2023PodcastA Wafer-Scale Chip So AI Stops Waiting on AmdahlHost Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.
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No Priors: AI, Machine Learning, Tech, & Startups· Feb 2, 2023Podcast · 2 speakersForty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lessonHost Sarah Guo, Elad GilMeta’s Noam Brown tells Sarah Guo and Elad Gil how Cicero negotiated in English for 40 games on a tiny web community — and why thinking at decision time beat three years of scaling.
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Lex Fridman· Feb 9, 2020PodcastMoore’s Law Is Not Dead—It Is a Cascade of S-CurvesHost Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.
23:57ENNo Priors: AI, Machine Learning, Tech, & StartupsPodcast · 2 speakersChips, Agents and a Reckoning: Sarah Guo and Elad Gil on the 2023 AI BoomHost Sarah Guo, Elad GilThe hosts answer listener questions on the GPU crunch, how soon enterprises will ship AI products, how to build agents, and what 2024 holds for tech valuations.
1:18:48ENLex FridmanPodcastData Movement, Not Math: How to Make Deep Learning Fit on Robots and PhonesHost Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.
57:21ENCognitive Revolution "How AI Changes Everything"PodcastGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build NextHost Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
31:46ENNo Priors: AI, Machine Learning, Tech, & StartupsPodcast · 2 speakersWhy Rivian Threw Out Its First Self-Driving Stack and Built Its Own BrainHost Sarah Guo, Elad GilRivian founder RJ Scaringe explains the neural-net reset, in-house chips, software-defined architecture and the mass-market R2 bet.