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344 件
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1:33:07ZH
Zhang Xiaojun Podcast· 2024年8月17日ポッドキャスト · 2 人广密复盘全球大模型这一年:Scaling Law、AGI 豪赌与中美格局ゲスト 李广密 · ホスト 张小珺拾象创始人李广密从硅谷一线观察出发,回顾 OpenAI、Anthropic、Google 与中国模型公司的竞争。他认为,模型能力与成本共同决定新一轮应用爆发,而巨额投入押注的是智能能否持续扩展以及 AI 对经济和产业的长期重构。モデルと学習Scaling LawsAI research+2
49:41ZH
Zhang Xiaojun Podcast· 2024年8月17日ポッドキャスト · 3 人傅盛:大模型是生产力革命,机器人迎来新的窗口ゲスト 傅盛 · ホスト 张小珺傅盛认为,大模型的核心是逻辑与推理能力,它带来的变化更像蒸汽机,而不是一次普通的互联网迭代。从平民化模型、服务机器人到创业者如何面对低谷,他也回看了自己的判断与心境。AI Strategyモデルと学習Robotics+2
2:04:15EN
Cognitive Revolution "How AI Changes Everything"· 2024年8月14日ポッドキャストA parrot cannot paraphrase — and Claude cannot be talked into harmホスト Nathan LabenzRobert Wright of the Nonzero podcast interviews Nathan Labenz on whether large language models understand anything, what Anthropic’s 10 million features actually show, and why open weights collide with U.S.–China policy.モデルと学習Model InterpretabilityMultimodal AI+3
スライド 6 枚15:24EN
Matthew Berman· 2024年8月13日Testing the Anonymous sus-column-r Model, Later Identified as Grok-2Matthew Berman · Forward FutureMatthew Berman tests a mysterious 2024 Arena model on coding and reasoning; its verbose answers prompted speculation about OpenAI that the later identification contradicted.モデルと学習評価(Evals)Reasoning & test-time compute+1
スライド 6 枚14:32EN
Matthew Berman· 2024年8月10日OpenAI Departures, Developer Tools and Synthetic Media: An August 2024 AI RoundupMatthew Berman · Forward FutureMatthew Berman reviews leadership changes, training-data disputes, structured API output, Qwen2-Math and emerging deepfake tools.AI researchGenerative mediaAI Safety+2
スライド 2 枚16:06EN
Matthew Berman· 2024年8月9日Q* and Strawberry: What Was Known and Speculated in August 2024Matthew Berman · Forward FutureMatthew Berman reviews contemporary rumors and research concepts around reasoning, search and self-play, while the underlying project remained undisclosed.モデルと学習AI researchAGI(汎用人工知能)
46:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月1日ポッドキャスト · 2 人Oriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are Numberedホスト Sarah Guo, Elad GilGoogle DeepMind’s VP of research on Gemini, long context, the coming shift from pretraining to RL, and why AGI may never have a finish line.モデルと学習AGI TimelinesPretraining & midtraining+3
スライド 3 枚13:40EN
Matthew Berman· 2024年7月29日Testing Llama 3.1 8B: Benchmark Gains and Mixed Practical ResultsMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and other prompts on the small model and finds several failures despite stronger reported benchmarks.Open-weight models評価(Evals)モデルと学習+1
スライド 5 枚10:02EN
Matthew Berman· 2024年7月24日Testing Llama 3.1 405B on Coding, Arithmetic and ReasoningMatthew Berman · Forward FutureMatthew Berman tries Meta's 2024 open-weight model on an informal set of prompts and demonstrates a sponsored dataset workflow.Open-weight modelsモデルと学習評価(Evals)+1
スライド 4 枚15:50EN
Matthew Berman· 2024年7月23日Llama 3.1: Meta’s 405B Model and the Open-Weight EcosystemMatthew Berman · Forward FutureMatthew Berman reviews Meta’s July 2024 release, the smaller models, reported benchmarks, synthetic data and the proposed Llama Stack.Open-weight modelsモデルと学習Benchmarks+2
0:58EN
Matthew Berman· 2024年7月11日NVIDIA NIM: Containerized AI Inference MicroservicesMatthew Berman · Forward FutureA sponsored overview of NVIDIA’s approach to packaging model inference for local and cloud applications.インフラとデプロイモデルと学習
スライド 6 枚18:57EN
Matthew Berman· 2024年7月9日AI News in July 2024: Small Models, Voice Tools and OpenAI SecurityMatthew Berman, Andrej Karpathy · Forward FutureMatthew Berman reviews AI product announcements, model evaluation and security reporting, and shares his predictions about the future of computing.AI researchモデルと学習AI security+2
1:42:16EN
Cognitive Revolution "How AI Changes Everything"· 2024年7月4日ポッドキャスト267 Papers in Seven Months: Albert Gu Explains the State Space Model Revolutionホスト Nathan LabenzThe Mamba co-author walks through five years of recurrent-model work, why selective compression beats a growing KV cache, and what Mamba 2 trades away to train faster.モデルと学習Transformers & attentionInference+3
スライド 5 枚13:30EN
Matthew Berman· 2024年7月2日AI News in July 2024: Smart Glasses, Robot Skin and Model RoutingMatthew Berman, Mark Zuckerberg · Forward FutureMatthew Berman surveys early plans for AI glasses, robotics demonstrations, generative video and RouteLLM's model-routing results.RoboticsAI agentsモデルと学習+2
34:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年6月27日ポッドキャスト · 2 人Five Independent Teams Found the Same 10-to-1 Mix That Beats Transformersホスト Sarah Guo, Elad GilThe authors of S4 and Mamba argue that mostly state-space layers plus a dash of attention is the architecture that actually works—and they are shipping it first as real-time speech.モデルと学習Transformers & attention音声 AI+3
1:54:01EN
Cognitive Revolution "How AI Changes Everything"· 2024年6月26日ポッドキャストA Tiny Network Grew a Salt Crystal the Training Data Never Showedホスト Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.モデルと学習AI for science機械学習の基礎+3
58:18EN
20VC with Harry Stebbings· 2024年6月24日ポッドキャスト · 2 人David Luan on Model Scaling, AI Agents and Competition Across the Chip Stackゲスト David Luan · ホスト Harry StebbingsThe Adept co-founder explains his views on compute, vertical integration, enterprise agents and why human interaction should shape AI product design.AI agentsモデルと学習Semiconductors+2
スライド 5 枚12:55EN
Matthew Berman· 2024年6月23日Testing Mixture-of-Agents on Coding, Arithmetic and ReasoningMatthew Berman · Forward FutureMatthew Berman tries a multi-model setup on his informal LLM rubric and finds strong individual answers alongside coding and counting failures.Multi-agent systemsモデルと学習評価(Evals)+1
1:37:07EN
Cognitive Revolution "How AI Changes Everything"· 2024年6月22日ポッドキャストA Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.ホスト Nathan LabenzGoogle researchers Vivek Natarajan and Khaled Saab walk Nathan Labenz through five medical-AI papers, from radiology reports to an AI doctor that still has to earn trust.モデルと学習AI in healthcareMultimodal AI+3
スライド 4 枚16:11EN
Matthew Berman· 2024年6月22日AI News in June 2024: SSI, Tree Search, Meta, Claude and ARC PrizeMatthew Berman · Forward FutureMatthew Berman reviews new AI research, product launches and a competition, with context on historical benchmarks and uncertain claims.AI researchモデルと学習AI Safety+2
スライド 4 枚16:49EN
Matthew Berman· 2024年6月21日How Apple's On-Device and Private Cloud Models WorkMatthew Berman · Forward FutureMatthew Berman examines Apple's 2024 foundation-model overview, from training data and quantization to task adapters and human evaluations.Local inferenceモデルと学習Privacy & data governance+1
スライド 5 枚13:18EN
Matthew Berman· 2024年6月20日Testing Local AI on a Dual RTX 6000 WorkstationMatthew Berman · Forward FutureMatthew Berman tests language models, concurrent inference, and image generation on a Dell Precision tower supplied by Dell and NVIDIA.Local inferenceInferenceモデルと学習+2
27:37EN
Matthew Berman· 2024年6月17日Leo Pekelis on Extending Llama 3 to a Million-Token ContextMatthew Berman, Leo Pekelis · Forward FutureGradient’s chief scientist explains long-context training, coding use cases, inference costs and why retrieval benchmarks tell only part of the story.コンテキストエンジニアリングモデルと学習Inference+2
1:06:04EN
20VC with Harry Stebbings· 2024年6月12日ポッドキャスト · 2 人Alexandr Wang on AI Data, Model Development and Building Scaleゲスト Alexandr Wang · ホスト Harry StebbingsScale’s founder discusses his data-bottleneck thesis, enterprise adoption, AI security and the challenges of growing a team.Data quality & curationモデルと学習AI Strategy+2
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