絞り込み結果
258 件並び順
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。
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.
16:06ENQ* 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.
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.
13:40ENTesting 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.
0:58ENNVIDIA NIM: Containerized AI Inference MicroservicesMatthew Berman · Forward FutureA sponsored overview of NVIDIA’s approach to packaging model inference for local and cloud applications.
1:42:16ENCognitive 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.
34:09ENNo 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.
1:54:01ENCognitive 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.
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.
1:37:07ENCognitive 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.
13:18ENTesting 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.
1:06:04EN20VC 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.
1:03:12EN20VC with Harry Stebbings· 2024年6月5日ポッドキャスト · 2 人Aravind Srinivas on Reasoning, Model Economics and Building Perplexityゲスト Aravind Srinivas · ホスト Harry StebbingsThe Perplexity co-founder discusses AI scaling, foundation-model competition, advertising and the challenges of building a search product.
1:59:15ENCognitive Revolution "How AI Changes Everything"· 2024年5月25日ポッドキャストA Protein Backbone in a Minute: The Real Progress, Bottlenecks, and Risks of AI Biologyホスト Nathan LabenzThe White House set a thousand-fold lower reporting bar for biological models than for language models—and this conversation shows why that gap already looks prescient.
58:28ENCognitive Revolution "How AI Changes Everything"· 2024年5月22日ポッドキャストFrom Jailbreaking ChatGPT to Anthropic’s First Prompt Engineer: How Alex Albert Ships Claude 3ホスト Nathan LabenzA year after building jailbreakchat.com, Alex Albert walks Nathan Labenz through Claude 3’s writing, orchestration, character work, and the guardrails app developers still skip.
12:50ENTesting Smaug: Hosted 70B Versus a Smaller Local ModelMatthew Berman · Forward FutureMatthew Berman compares two Smaug configurations on Snake, math and reasoning puzzles.
13:37ENTesting 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.
27:07ENGPT-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.
17:12ENTesting 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.
16:28ENTesting 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.
15:01ENTesting 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.
1:01:39ENCognitive Revolution "How AI Changes Everything"· 2024年4月13日ポッドキャストGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?ホスト 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.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 2024年4月5日ポッドキャストA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Aheadホスト 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.もっと見る258 件中 24 件を表示