필터 결과
79개정렬
56:31ENPost-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.
58:17ENThey 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.
1:04:14ENThe Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your House진행자 Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.
1:13:48ENCarriers Spend $200 Billion a Year. The Money Went Up the Stack진행자 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.
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuber진행자 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.
1:06:36ENBills Doubled Overnight. Next, the APIs Might Vanish.진행자 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.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Miss진행자 Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
56:10ENReid Hoffman Pledged a Billion to Free DeepMind. Hassabis Never Played the Card진행자 Jacob EffronSebastian Mallaby's biography of Demis Hassabis, discussed with Jacob Effron, is a story of a founder who tried to stop the AI race and then became one of its central players.
59:41ENThe GPT moment for video hasn’t arrived, but AGI may already be here진행자 Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
1:21:56ENYann LeCun Left Meta Because LLMs Will Not Get You to Intelligence진행자 Jacob EffronThe Turing Award winner tells Jacob Effron why he spun AMI Labs out of Meta, why JEPA-style world models beat pixel generators, and why he thinks Hinton changed his mind in 2023.
58:46ENTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028진행자 Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGI진행자 Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
1:18:05ENThe Real Bottleneck in AI Research Is Compute, Not Ideas진행자 Jacob EffronAfter NeurIPS, Ari Morcos and Rob Toews sit down with Jacob Effron to argue about plateauing models, SSI’s secrecy, OpenAI’s cash burn, and a set of spicy 2026 bets.
48:00ENA 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.
57:37ENThe hot-swap era for models is over, OpenAI's enterprise product chief says진행자 Jacob EffronOlivier Godement on GPT-5.1, Codex, enterprise harnesses, and the three practices that actually make AI land inside large companies.
1:09:48ENChina's AI Labs Went From 15 to Six. The Compute Gap Is 15-to-1.진행자 Jacob EffronJordan Schneider tells Unsupervised Learning that Chinese models were a private-capital story, that Beijing still thinks in hardware, and that the West's real edge is chips it can serve — not a state master plan.
42:06ENAfter 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.
1:16:53ENKarpathy Called Today's Models Slop. His Decade Timeline Still Sounds Bullish진행자 Jacob EffronDatology AI's Ari Morcos and Radical Ventures' Rob Toews walk through Karpathy's cold water, OpenAI's dealmaking, and who actually pays for the data-center boom.
1:02:05EN$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Math진행자 Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
42:20ENA 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.
59:06ENInference Costs Fell 100x. Tri Dao Says There's Another 10x — and NVIDIA's 90% Won't Hold진행자 Jacob EffronThe FlashAttention author and Together AI chief scientist on why hardware portability is a myth, how Claude Code made him 1.5x faster, and why workloads will split the chip market.
57:52ENThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.진행자 Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.
54:53ENA 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.
44:21ENMercor'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.
더 보기79개 중 24개 표시









