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94개정렬
9:46EN
Matthew Berman· 2023년 7월 17일Orca Mini V2 vs. OpenOrca: A 2023 Informal Model ComparisonMatthew Berman · Forward FutureMatthew Berman tests two Orca-inspired models on coding, writing and reasoning, with results shaped by prompt setup and subjective scoring.
8:04ENMatthew Berman· 2023년 7월 11일WizardLM 13B v1.1 Tested on Coding, Writing and LogicMatthew Berman · Forward FutureMatthew Berman tries an instruction-tuned model on a small set of prompts, with mixed results and several subjective scoring choices.
2:00:19EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 6일팟캐스트1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2진행자 Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…
9:58ENMatthew Berman· 2023년 4월 26일HuggingChat’s 2023 Debut: Testing Writing, Reasoning and Python CodeMatthew Berman · Forward FutureMatthew Berman tries the early OpenAssistant-powered HuggingChat on writing, arithmetic, logic and a Snake game, then compares a few outputs with GPT-3.5 and GPT-4. The results illustrate both promise and limitations in this small historical test.
1:00:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 2월 2일팟캐스트 · 2명Forty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lesson진행자 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.
1:26:21EN
Lex Fridman· 2018년 12월 9일팟캐스트 · 2명The Machine Should Never Treat Its Objective as Gospel게스트 Stuart Russell · 진행자 Lex FridmanStuart Russell talks with Lex Fridman about metareasoning, self-driving reliability, and why uncertainty about human goals is the core of the control problem.
1:45:49ENCognitive Revolution "How AI Changes Everything"팟캐스트Trust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the Company진행자 Nathan LabenzAndreas Stuhlmüller and Jungwon Byun explain how Elicit keeps frontier models checkable for high-stakes science, and where they think AI reasoning is heading.
15:01ENLex Fridman팟캐스트 · 2명Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks게스트 Daniel Kahneman · 진행자 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.
10:16ENLex Fridman팟캐스트 · 2명Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
58:57ENCognitive Revolution "How AI Changes Everything"팟캐스트When the Model Learns to Look Around: Apollo Research on Testing o1 for Scheming진행자 Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.
57:25EN
Unsupervised Learning: With Jacob Effron팟캐스트From RAG to Reasoning: Why the Future of AI Is a System, Not a Model진행자 Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.
10:34ENLex Fridman팟캐스트 · 2명Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AI게스트 François Chollet · 진행자 Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.
1:03:10ENCognitive Revolution "How AI Changes Everything"팟캐스트Pause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgrades진행자 Nathan LabenzNathan Labenz and Trey Kollmer walk through five recent papers on pausing, backspacing, prompting, streaming and long-context training, and sketch how they might combine into a more capable model.