絞り込み結果
96 件並び順
20:55EN
AI Engineer· 2026年10月26日Jesse Hall：语音智能体要为对话而优化，而非只看排行榜Jesse Hall · LiveKitLiveKit 的 Jesse Hall 解释了为什么语音智能体必须像实时系统一样接受评测：听清用户、允许打断、在工具调用期间继续对话，并在用户真正听到声音之前控制延迟。
1:50:48EN
Y Combinator· 2026年10月24日Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
1:09:00EN
Dwarkesh Patel· 2026年10月22日ポッドキャスト · 9 人Dwarkesh Patel: What will computer chips look like in 2045?ゲスト Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · ホスト Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.
1:25:33EN
Latent Space· 2026年10月22日ポッドキャスト · 2 人Why GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, Modalゲスト Erik Bernhardsson · ホスト Vibhu SapraModal’s CEO tells Latent Space why AI demand almost never looks like a three-year GPU contract, how the company pools compute across thousands of customers, and why sandboxes grew from a product they almost killed into a third of revenue.
17:42ENAI Engineer· 2026年10月21日Is a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月8日ポッドキャストThere Likely Is a Level of Intelligence We Shouldn't Go Pastホスト Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
1:10:12ENCognitive Revolution "How AI Changes Everything"· 2026年10月7日ポッドキャストOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell Anywayホスト Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
1:04:26EN
Sequoia Capital· 2026年10月6日ポッドキャストAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
35:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月2日ポッドキャスト · 2 人Compute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That Ratioホスト Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:28:08ENCognitive Revolution "How AI Changes Everything"· 2026年10月1日ポッドキャストThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missedホスト Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
1:46:04ENCognitive Revolution "How AI Changes Everything"· 2026年9月27日ポッドキャストThe Training Worked. It Just Worked Too Well.ホスト Nathan LabenzA week of Cognitive Revolution clips: OpenAI agents colluding on a German wiki, $200 million checks for safety orgs that do not exist yet, a GPU price index, and two opposite bets on biological data.
38:14ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026年9月18日ポッドキャスト · 2 人Diffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Siliconホスト Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
1:06:47ENCognitive Revolution "How AI Changes Everything"· 2026年9月17日ポッドキャストEighty percent of what agents do should still be ordinary codeホスト Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.
37:07ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026年9月3日ポッドキャスト · 2 人Arm’s 98.5% margin business just started shipping chipsホスト Sarah Guo, Elad GilCEO Rene Haas tells No Priors why the IP company built a physical CPU for Meta, and why CPUs still sit at the center of AI systems.
55:19ENSequoia Capital· 2026年8月25日ポッドキャストHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
2:06:11ENCognitive Revolution "How AI Changes Everything"· 2026年8月14日ポッドキャストLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Bannedホスト Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
1:13:48EN
Unsupervised Learning: With Jacob Effron· 2026年7月16日ポッドキャストCarriers Spend $200 Billion a Year. The Money Went Up the Stackホスト Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
50:57ENUnsupervised Learning: With Jacob Effron· 2026年7月9日ポッドキャストA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuberホスト Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
41:05ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026年7月9日ポッドキャスト · 2 人There is no moat: Booking’s CEO on a $1 stock, agentic travel, and why AI still doesn’t move the numbersホスト Sarah Guo, Elad GilGlenn Fogel cashed his 1999 bonus, joined Priceline in February 2000, and watched the Nasdaq peak a week later — then spent 25 years turning a near-delisting into a thousand-fold ride he now wants to spend on AI travel agents.
1:47:38ENCognitive Revolution "How AI Changes Everything"· 2026年7月4日ポッドキャスト19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chipホスト Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:01:27ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026年7月2日ポッドキャスト · 2 人Two Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times Cheaperホスト Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.
1:10:15ENSequoia Capital· 2026年6月30日ポッドキャストThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.
1:06:36ENUnsupervised Learning: With Jacob Effron· 2026年6月12日ポッドキャストBills Doubled Overnight. Next, the APIs Might Vanish.ホスト Jacob EffronSix months after their last roundup, Ari Morcos and Rob Toews tell Jacob Efron why coding agents finally work, why near-frontier open weights may have peaked, and why a compute famine could pull the plug on public APIs.
41:20ENSequoia Capital· 2026年6月10日ポッドキャストA $4 Million Cabinet and a Trillion-Dollar Year: Jensen Huang Turns the AI Factory Into a Manufacturing StoryOn Sequoia's Training Data stage, NVIDIA's CEO walks a sixty-country audience from ChatGPT's parlor tricks to agentic work, a five-layer industrial cake, and why radiology hiring went up.もっと見る96 件中 24 件を表示