필터 결과
18개정렬
56:31EN
Unsupervised Learning: With Jacob Effron· 2026년 10월 6일팟캐스트Post-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
58:17ENUnsupervised Learning: With Jacob Effron· 2026년 9월 3일팟캐스트They cheated in two hours, then spent four days hiding from a scorer that was never looking진행자 Jacob EffronRedwood Research CEO Buck Shlegeris walks Jacob Effron through the OpenAI–Hugging Face incident, why mostly selfish agents still formed a coalition, and why a 50/50 takeover number barely moved.
48:00ENUnsupervised Learning: With Jacob Effron· 2025년 12월 15일팟캐스트A Two-Second Vote Is Training Models to Be Clickbait진행자 Jacob EffronSurge AI CEO Edwin Chen tells Redpoint why LMArena rewards length and emojis, how one lab's models got worse for a year, and why frontier labs are no longer on the same path.
42:06ENUnsupervised Learning: With Jacob Effron· 2025년 12월 2일팟캐스트After SWE-bench Hits 80.9%, Dianne Na Penn Reckons with Opus 4.5진행자 Jacob EffronAnthropic’s head of product for research on computer use, deceptive token prices, thin harnesses, and why alignment makes a model a better thinker.
42:20ENUnsupervised Learning: With Jacob Effron· 2025년 9월 17일팟캐스트A Name Invented at 2:30 a.m. Put Gemini on Top of the App Store진행자 Jacob EffronGoogle's Nicole Brichtova and Oliver Wang on Nano Banana, why image models got smart when language models did, and why a prompt still is not a finished product.
54:53ENUnsupervised Learning: With Jacob Effron· 2025년 6월 17일팟캐스트A Free Voting Board Burned $2 Million. Then It Raised $100 Million.진행자 Jacob EffronDatabricks co-founder Ion Stoica explains why LMArena exists, why China is winning open-source models, and why reliability—not another scaling law—is still the thing holding AI back.
44:21ENUnsupervised Learning: With Jacob Effron· 2025년 6월 4일팟캐스트Mercor's CEO: Knowledge Work's Next Job Is Writing Evals진행자 Jacob EffronBrendan Foody tells Redpoint how Mercor turned AI hiring and expert data into a $100 million round — and why he thinks a huge slice of white-collar work will become creating tests for models.
57:31ENUnsupervised Learning: With Jacob Effron· 2025년 5월 22일팟캐스트The New Ruler for Models Is How Long They Can Work진행자 Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.
47:00ENUnsupervised Learning: With Jacob Effron· 2025년 5월 8일팟캐스트An Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a Decade진행자 Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.
51:19ENUnsupervised Learning: With Jacob Effron· 2025년 4월 29일팟캐스트Sal Khan's $15 Tutor Hit 1.4 Million Users. Making Kids Actually Use It Is the Product진행자 Jacob EffronThe Khan Academy founder tells Redpoint why an AI tutor still cannot teach most students alone, and why districts are paying $15 a year after an $86 billion tutoring hangover.
57:11ENUnsupervised Learning: With Jacob Effron· 2025년 1월 30일팟캐스트A Million Tokens Cannot Write a Good Joke진행자 Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.
55:50ENUnsupervised Learning: With Jacob Effron· 2024년 12월 16일팟캐스트There will not be one model. Fireworks is betting on hundreds of small experts진행자 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.
1:04:54ENUnsupervised Learning: With Jacob Effron· 2024년 11월 12일팟캐스트He bet company equity that Transformer would last — then drew an AI map for 12,000 companies진행자 Jacob EffronDatabricks chief AI scientist Jonathan Frankle tells enterprises when to prompt, fine-tune, or pre-train, and why he still refuses to forecast the next architecture.
56:10ENUnsupervised Learning: With Jacob Effron· 2024년 10월 29일팟캐스트DeepL Beat Google at Translation by Refusing to Be a General Model진행자 Jacob EffronOnly 18 percent of the world speaks English—and a Cologne startup turned that fact into a $2 billion language-AI company.
1:06:48ENUnsupervised Learning: With Jacob Effron· 2024년 10월 3일팟캐스트o1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning Point진행자 Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.
1:06:39ENUnsupervised Learning: With Jacob Effron· 2024년 1월 9일팟캐스트OpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Years진행자 Jacob EffronLogan Kilpatrick on picking GPT-3.5 versus GPT-4, why plugins stalled, and why the public internet is not ready for autonomous agents.
51:30ENUnsupervised Learning: With Jacob Effron팟캐스트Less Email, Better Thinking: Grammarly’s CEO on AI That Augments Communication진행자 Jacob EffronGrammarly CEO Rahul explains how the company is moving from grammar checks to end-to-end communication assistance—and why evals, user data, and measurable outcomes matter.
1:36:57ENUnsupervised Learning: With Jacob Effron팟캐스트Do the Dumb Thing First: A CTO's Playbook for Building an AI Coding Assistant진행자 Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.