최근 업데이트된 채널

선택하면 해당 채널만 표시모든 채널 보기 →

필터 결과

279개
정렬
슬라이드 3장13:37EN
Matthew Berman· 2024년 5월 16일Testing Gemini 1.5 Pro’s Long Context and Video UnderstandingMatthew Berman · Forward FutureMatthew Berman’s 2024 tests show useful image and video summaries alongside blocked code and missed details.Multimodal AIBenchmarks비전과 영상+1
슬라이드27:07EN
Matthew Berman· 2024년 5월 14일GPT-4o's Launch: Voice, Vision and a More Conversational InterfaceMatthew Berman, Mira Murati · Forward FutureMatthew Berman reviews OpenAI's May 2024 demonstrations of GPT-4o and considers what a faster multimodal assistant could enable.AI research제품과 UX모델과 학습
슬라이드 4장17:12EN
Matthew Berman· 2024년 4월 30일Testing the Mystery 'gpt2-chatbot' Model in April 2024Matthew Berman · Forward FutureMatthew Berman tries an anonymous model on coding, arithmetic and reasoning tasks while its identity remains uncertain.Benchmarks모델과 학습코딩 에이전트+1
슬라이드 7장21:47EN
Matthew Berman· 2024년 4월 24일Phi-3 Mini: Microsoft’s Small Model, Phone Deployment and an Uncertain Local TestMatthew Berman · Forward FutureMatthew Berman reviews Microsoft’s 2024 technical report and runs informal prompts, with an unresolved model label in the demonstration.Local inference모델과 학습Benchmarks+1
슬라이드 3장16:28EN
Matthew Berman· 2024년 4월 23일Testing Reka Core: Multimodal Benchmarks, Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman reviews Reka’s reported model comparisons and tests Core on code, logic and image understanding.Multimodal AIBenchmarks모델과 학습+1
슬라이드 3장15:01EN
Matthew Berman· 2024년 4월 19일Testing Llama 3 at Launch: Code, Reasoning and Image GenerationMatthew Berman · Forward FutureMatthew Berman tries Meta AI’s new interface on a snake game, logic puzzles and rapid image generation.Open-weight models평가(Evals)모델과 학습+1
1:01:39EN
Cognitive Revolution "How AI Changes Everything"· 2024년 4월 13일팟캐스트GPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?진행자 Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.모델과 학습Scaling LawsSynthetic data+3
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· 2024년 4월 5일팟캐스트A Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Ahead진행자 Nathan LabenzNortheastern’s Bau Lab shows that a 40,000-parameter soft prompt can read a model’s future words, and that about ten attention heads carry the task itself.모델과 학습Model InterpretabilityTransformers & attention+3
슬라이드 3장14:23EN
Matthew Berman· 2024년 3월 31일Testing DBRX: Coding Strengths and Reasoning GapsMatthew Berman · Forward FutureMatthew Berman examines Databricks’ open-weight model and puts it through coding, arithmetic and reasoning prompts.Open-weight models모델과 학습평가(Evals)+1
1:20:44EN
Cognitive Revolution "How AI Changes Everything"· 2024년 3월 30일팟캐스트Seeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Days진행자 Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.모델과 학습AI researchTransformers & attention+3
슬라이드 5장22:17EN
Matthew Berman· 2024년 3월 21일Q* Rumors, Energy-Based Models, and Research on ReasoningMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines an anonymous, unverified account of Q* and compares its ideas with published research on teaching language models to reason.Reasoning & test-time compute모델과 학습AI research+2
2:47:17EN
Lex Fridman· 2024년 3월 7일팟캐스트 · 2명If You Want Human-Level AI, Abandon Generative Models게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.모델과 학습World modelsAGI(범용 인공지능)+3
슬라이드 3장23:00EN
Matthew Berman· 2024년 2월 22일Testing Google Gemma 7B at Launch: Setup MattersMatthew Berman · Forward FutureMatthew Berman compares local and hosted tests of Google’s early open-weight model.Open-weight models평가(Evals)모델과 학습
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· 2024년 2월 7일팟캐스트A Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.진행자 Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.모델과 학습AI HistoryNeuroscience & AI+3
슬라이드 2장0:42EN
Matthew Berman· 2024년 1월 31일LLaVA 1.6 Adds Higher-Resolution Image UnderstandingMatthew Berman · Forward FutureMatthew Berman reviews the January 2024 release of LLaVA 1.6 and its local availability through Ollama.Multimodal AI모델과 학습Local inference+1
40:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 1월 25일팟캐스트 · 2명99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses First진행자 Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.모델과 학습RoboticsFoundation Models+3
2:30:06EN
Cognitive Revolution "How AI Changes Everything"· 2023년 12월 22일팟캐스트Trained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turf진행자 Nathan LabenzIn a solo emergency episode, Nathan Labenz argues that Albert Gu and Tri Dao's selective state space model is the first architecture since 2017 that deserves to share the Transformer’s throne.모델과 학습Transformers & attentionAI research+3
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· 2023년 11월 17일팟캐스트A Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.진행자 Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.모델과 학습AI research머신러닝 기초+3
1:21:50EN
Cognitive Revolution "How AI Changes Everything"· 2023년 11월 14일팟캐스트A 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.진행자 Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.모델과 학습Synthetic dataData quality & curation+3
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 11월 2일팟캐스트 · 2명Reliability is the bottleneck. Autonomy is what would make AI feel alive.진행자 Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.모델과 학습AGI(범용 인공지능)Scaling Laws+3
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 2023년 10월 18일팟캐스트1,000 H100s Take 115 Days; 22,000 Take Five진행자 Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.모델과 학습AI researchModel Interpretability+3
37:01EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 9월 28일팟캐스트 · 2명DNA Is Code, but You Compile It with a Pipette진행자 Sarah Guo, Elad GilGinkgo Bioworks CEO Jason Kelly tells No Priors why cells are worth the magic, why biology has no AWS, and why a pandemic should look like cybersecurity.모델과 학습AI for scienceBiosecurity+3
슬라이드 6장12:49EN
Matthew Berman· 2023년 9월 14일Falcon 180B: A 2023 Review of TII’s Open-Weight ModelMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and writing prompts while examining the model’s training scale and license.Open-weight modelsBenchmarks모델과 학습+1
36:33EN
20VC with Harry Stebbings· 2023년 8월 31일팟캐스트 · 2명Noam Shazeer on Character.AI, the Cost of Training Models and the Uses of General AI게스트 Noam Shazeer · 진행자 Harry StebbingsThe Character.AI co-founder explains his consumer strategy, language-model training and why he expects users to invent applications the company cannot predict.Foundation Models모델과 학습AI startups & small teams+2
더 보기279개 중 24개 표시