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123개정렬
42:08EN
Sequoia Capital· 2024년 7월 30일팟캐스트Meta Trained a 405B Teacher on 16,000 GPUs — Then Told the World to Distill ItTwo days after Llama 3.1 405B shipped, Meta's generative-AI product lead walks Sequoia through why the most expensive model in the family is free, and why he thinks the frontier itself is heading toward commodity.
13:40ENTesting Llama 3.1 8B: Benchmark Gains and Mixed Practical ResultsMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and other prompts on the small model and finds several failures despite stronger reported benchmarks.
1:54:01EN
Cognitive Revolution "How AI Changes Everything"· 2024년 6월 26일팟캐스트A Tiny Network Grew a Salt Crystal the Training Data Never Showed진행자 Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.
16:06ENAI News: Video Generation, Apple Intelligence, Robotics and DeepSeek Coder V2Matthew Berman · Forward FutureMatthew Berman reviews a week of launches and research, from Luma and Runway to NVIDIA, robotics and coding models.
9:53ENTesting Microsoft Phi-3 Medium Locally: Mixed Coding and Reasoning ResultsMatthew Berman · Forward FutureMatthew Berman runs a quantized Phi-3 Medium on a MacBook and explores coding, arithmetic and reasoning prompts.
12:50ENTesting Smaug: Hosted 70B Versus a Smaller Local ModelMatthew Berman · Forward FutureMatthew Berman compares two Smaug configurations on Snake, math and reasoning puzzles.
51:00EN
20VC with Harry Stebbings· 2024년 4월 29일팟캐스트 · 2명Arthur Mensch on Mistral’s Open Models, Compute and Developer Strategy게스트 Arthur Mensch · 진행자 Harry StebbingsThe Mistral AI co-founder explains the company’s mix of open and commercial models, its compute constraints and its bet on efficient developer tools.
1:42:17ENCognitive Revolution "How AI Changes Everything"· 2024년 4월 20일팟캐스트The Cheapest Inference Provider Is the Most Dangerous진행자 Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.
15:01ENTesting Llama 3 at Launch: Code, Reasoning and Image GenerationMatthew Berman · Forward FutureMatthew Berman tries Meta AI’s new interface on a snake game, logic puzzles and rapid image generation.
14:23ENTesting DBRX: Coding Strengths and Reasoning GapsMatthew Berman · Forward FutureMatthew Berman examines Databricks’ open-weight model and puts it through coding, arithmetic and reasoning prompts.
14:11ENLM Studio in 2024: Local Models, Parallel Inference and a Local APIMatthew Berman · Forward FutureMatthew Berman demonstrates model downloads, hardware settings, JSON output and serving multiple local models.
2:47:17EN
Lex Fridman· 2024년 3월 7일팟캐스트 · 2명If You Want Human-Level AI, Abandon Generative Models게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.
23:00ENTesting Google Gemma 7B at Launch: Setup MattersMatthew Berman · Forward FutureMatthew Berman compares local and hosted tests of Google’s early open-weight model.
3:37ENMark Zuckerberg Announces Llama 3 Training and Meta’s AI PlansMatthew Berman, Mark Zuckerberg · Forward FutureIn January 2024, Matthew Berman reacts to Zuckerberg’s remarks on general intelligence, compute and AI devices.
19:10EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 1월 11일팟캐스트 · 2명The World's Only Capped-Profit Company진행자 Sarah Guo, Elad GilNo Priors looks back at 2023 through eight conversations on money, intelligence, jobs, and who should put the guardrails on a model.
2:16:27ENCognitive Revolution "How AI Changes Everything"· 2023년 12월 12일팟캐스트Superhuman Go Has a Blind Spot. Balaji Bets on a War of the Gods진행자 Nathan LabenzBalaji Srinivasan tells Nathan Labenz why adversarial inputs, missing actuators, and cryptography make a single runaway AI god less likely than a contest among many that still need priests.
32:57ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 11월 9일팟캐스트 · 2명A 7-billion-parameter model on a MacBook: Mistral's CEO reruns the cost of AI진행자 Sarah Guo, Elad GilArthur Mensch tells No Priors why Chinchilla made small models valuable, why open-sourcing Mistral 7B is not a bioweapon risk, and why guardrails belong on the application.
4:42ENConnecting AutoGen to a Local Model With LM StudioMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup and explains where agent behavior still needs work.
1:14:36ENCognitive Revolution "How AI Changes Everything"· 2023년 10월 13일팟캐스트Zulu Bypasses GPT-4, and a Hundred Examples Undo the Guardrails진행자 Nathan LabenzNathan Labenz reads seven papers — four hopeful, three not — on whether anyone can actually keep a language model under control.
1:04:38ENLex Fridman· 2023년 9월 28일팟캐스트 · 2명Hundreds of Miles Apart, Zuckerberg and Fridman Sat Close Enough to See the Wrinkles게스트 Mark Zuckerberg · 진행자 Lex FridmanLex Fridman sat in a dark room in Austin wearing a Quest headset; Mark Zuckerberg sat in another conference room, also wearing one, and it did not feel like a video call.
29:38ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 9월 21일팟캐스트 · 2명A Beginner Just Shipped a $250K Business. Professionals Got 30 Percent.진행자 Sarah Guo, Elad GilReplit CEO Amjad Masad on Ghostwriter, why a 3-billion-parameter model was enough, and the agents he wants earning bounties while you sleep.
30:03ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 9월 7일팟캐스트 · 2명A Dinner-Plate Chip Cut Training From 60 Days to 3.5진행자 Sarah Guo, Elad GilCerebras CEO Andrew Feldman tells No Priors why wafer-scale silicon, not another GPU, is the answer to the compute crunch — and why most production models will stay at 13 billion parameters or below.
52:48ENCognitive Revolution "How AI Changes Everything"· 2023년 8월 25일팟캐스트OpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the List진행자 Nathan LabenzNathan Labenz and Erik Torenberg walk through GPT-3.5 Turbo fine-tuning, why self-hosting still loses on total cost, and what is actually working in code, school, and medicine.
12:20ENTesting UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.
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