最近更新されたチャンネル

選ぶとそのチャンネルだけを表示すべてのチャンネル →

絞り込み結果

80 件
並び順
スライド 2 枚30:29EN
Matthew Berman· 2025年1月3日How Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.Reinforcement Learningモデルと学習AI research+1
55:50EN
Unsupervised Learning: With Jacob Effron· 2024年12月16日ポッドキャストThere will not be one model. Fireworks is betting on hundreds of small expertsホスト Jacob EffronPyTorch veteran Lin Qiao argues that inference is a compound system hyperscalers cannot buy their way through, and that the products with real traction still keep a human in the loop.インフラとデプロイInferenceModel routing & gateways+3
42:21EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年12月12日ポッドキャスト · 2 人They Cooled 5,000 Watts per Square Centimeter in Space. Now Diamond Goes on AI Chipsホスト Sarah Guo, Elad GilAkash Systems founders Felix Ejeckam and Ty Mitchell tell Sarah Guo why heat is the real limiter on AI, and how lab-grown diamond bonded to semiconductors is their answer.インフラとデプロイAI cost & performanceSemiconductors+1
44:16EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月21日ポッドキャスト · 2 人Cohere's Aidan Gomez: The Model Curve Is Flattening, and $20 Million Now Buys GPT-4ホスト Sarah Guo, Elad GilThe Attention Is All You Need co-author tells No Priors why enterprises should stop waiting for the next model and start putting today's models into production.企業と戦略エンタープライズ AIAI Strategy+3
36:49EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月7日ポッドキャスト · 2 人Jensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI Factoriesホスト Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO walks through hyper Moore’s law, NVLink, a 100,000-GPU cluster stood up in weeks, and why tokens are the new commodity.インフラとデプロイAI cost & performanceInference+3
2:29:04EN
Lex Fridman· 2024年10月6日ポッドキャスト · 2 人Keep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy Editingゲスト Cursor Team · ホスト Lex FridmanMichael Truell, Aman Sanger, Sualeh Asif, and Arvid Lunnemark tell Lex Fridman why they forked VS Code, how Tab and Apply actually work, and why most programming still needs a human iterating in real time.コーディングエージェント開発ワークフローとテストAI interface design+3
37:47EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月30日ポッドキャスト · 2 人Working Backwards from AGI: Magic's Five-Million-Token Betホスト Sarah Guo, Elad GilEric Steinberger wants a coding colleague you trust like a teammate — and a world that is still a good place thirty years after AGI.コーディングエージェントコンテキストエンジニアリングInference+3
42:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月29日ポッドキャスト · 2 人AWS Is a $100 Billion Cloud. Matt Garman Still Sees a 10x Migration Aheadホスト Sarah Guo, Elad GilAmazon Web Services’ new CEO tells No Priors why 85 percent of workloads are still on-prem, how Bedrock was built from three bets, and why startups remain the company’s growth engine.インフラとデプロイエンタープライズ AIAI Strategy+3
42:42EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月22日ポッドキャスト · 2 人Ethereum Once Held Two Thousand GPT-3 Clusters of GPUsホスト Sarah Guo, Elad GilFoundry CEO Jared Quincy Davis on idle H100s, why today's AI cloud is still colocation, and how compound systems move work off giant interconnected clusters.インフラとデプロイAI cost & performanceDistributed training & inference+3
39:18EN
Sequoia Capital· 2024年8月13日ポッドキャストOpen and Closed Will Tie at the Same Size: PyTorch's Former Lead on Fast InferenceA six-month library swap at Meta became a five-year rebuild. Lin Qiao wants the rest of the industry to get that stack in five weeks.インフラとデプロイInferenceファインチューニング+3
1:00:28EN
Sequoia Capital· 2024年7月9日ポッドキャストScaling Laws Aren't Done. Don't Lock Yourself Into Yesterday's Architecture.Microsoft CTO Kevin Scott on why the exponential is still compounding, why inference will dwarf training, and why a language model is the world's crappiest database.企業と戦略Scaling LawsInference+3
1:42:16EN
Cognitive Revolution "How AI Changes Everything"· 2024年7月4日ポッドキャスト267 Papers in Seven Months: Albert Gu Explains the State Space Model Revolutionホスト Nathan LabenzThe Mamba co-author walks through five years of recurrent-model work, why selective compression beats a growing KV cache, and what Mamba 2 trades away to train faster.モデルと学習Transformers & attentionInference+3
1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月20日ポッドキャストThe Cheapest Inference Provider Is the Most Dangerousホスト 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.インフラとデプロイInferenceAI cost & performance+3
スライド 3 枚51:11EN
Matthew Berman· 2024年3月22日Inside Groq’s LPU: Compilers, Chip Networks and Fast InferenceMatthew Berman, Andrew Ling, Igor Arsovski · Forward FutureGroq engineers Andrew Ling and Igor Arsovski explain their hardware and software design in a sponsored 2024 interview.インフラとデプロイInferenceAI cost & performance
38:33EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年3月21日ポッドキャスト · 2 人Speed Is the Thing You Can Buy: Baseten’s Bet on Inferenceホスト Sarah Guo, Elad GilTuhin Srivastava tells Sarah Guo and Elad Gil why a six-person chatbot company running a billion tokens a day should not be building its own serving stack.インフラとデプロイInferenceAI cost & performance+3
39:03EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月29日ポッドキャスト · 2 人MI300 Leads Inference by 2x: AMD's CTO on Winning Chip Competition Without a Walled Gardenホスト Sarah Guo, Elad GilWhen Mark Papermaster became AMD's CTO in fall 2011, nearly all of the company's revenue sat on PCs and gaming, Moore's Law was slowing, and everyone knew it needed a turnaround.インフラとデプロイInferenceAI cost & performance+3
スライド 10 枚30:39EN
Matthew Berman· 2024年2月25日NVIDIA’s GEAR Research, Gemini 1.5 and Fast AI InferenceMatthew Berman · Forward FutureMatthew Berman reviews embodied-agent research and a February 2024 set of AI releases and demonstrations.RoboticsAI researchBenchmarks+2
1:22:43EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月9日ポッドキャストFive billion minutes of calls: why Dialpad trained its own business LLMホスト Nathan LabenzDan O’Connell on real-time speech, verticalizing the stack, and why he and Nathan Labenz disagree about when AI employees show up.企業と戦略音声 AIエンタープライズ AI+3
32:57EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年11月9日ポッドキャスト · 2 人A 7-billion-parameter model on a MacBook: Mistral's CEO reruns the cost of AIホスト 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.オープンソースとコミュニティOpen-source ecosystemsOpen-weight models+3
30:03EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年9月7日ポッドキャスト · 2 人A Dinner-Plate Chip Cut Training From 60 Days to 3.5ホスト 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.インフラとデプロイInferenceAI cost & performance+3
52:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月25日ポッドキャストOpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the Listホスト 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.モデルと学習ファインチューニングAI cost & performance+3
1:01:26EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月25日ポッドキャストAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.ホスト Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.インフラとデプロイAI cost & performanceDistributed training & inference+3
1:20:49EN
Cognitive Revolution "How AI Changes Everything"· 2023年5月25日ポッドキャストA Wafer-Scale Chip So AI Stops Waiting on Amdahlホスト 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.インフラとデプロイInferenceAI cost & performance+3
1:00:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年2月2日ポッドキャスト · 2 人Forty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lessonホスト 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.エージェントAI researchReasoning & test-time compute+3
もっと見る80 件中 24 件を表示