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1:06:04EN
20VC with Harry Stebbings· Jun 12, 2024Podcast · 2 speakersAlexandr Wang on AI Data, Model Development and Building ScaleGuest Alexandr Wang · Host Harry StebbingsScale’s founder discusses his data-bottleneck thesis, enterprise adoption, AI security and the challenges of growing a team.Data quality & curationModels & trainingAI Strategy+2
1:03:12EN
20VC with Harry Stebbings· Jun 5, 2024Podcast · 2 speakersAravind Srinivas on Reasoning, Model Economics and Building PerplexityGuest Aravind Srinivas · Host Harry StebbingsThe Perplexity co-founder discusses AI scaling, foundation-model competition, advertising and the challenges of building a search product.Models & trainingReasoning & test-time computeAI Strategy+2
1:59:15EN
Cognitive Revolution "How AI Changes Everything"· May 25, 2024PodcastA Protein Backbone in a Minute: The Real Progress, Bottlenecks, and Risks of AI BiologyHost 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.Models & trainingAI for scienceComputational Biology+3
58:28EN
Cognitive Revolution "How AI Changes Everything"· May 22, 2024PodcastFrom Jailbreaking ChatGPT to Anthropic’s First Prompt Engineer: How Alex Albert Ships Claude 3Host 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.Models & trainingSafety & governanceEvals+3
2 slides12:50EN
Matthew Berman· May 22, 2024Testing Smaug: Hosted 70B Versus a Smaller Local ModelMatthew Berman · Forward FutureMatthew Berman compares two Smaug configurations on Snake, math and reasoning puzzles.Open-weight modelsEvalsModels & training
3 slides13:37EN
Matthew Berman· May 16, 2024Testing 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 AIBenchmarksVision & video+1
Slides27:07EN
Matthew Berman· May 14, 2024GPT-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 researchProduct & UXModels & training
4 slides17:12EN
Matthew Berman· Apr 30, 2024Testing 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.BenchmarksModels & trainingCoding agents+1
7 slides21:47EN
Matthew Berman· Apr 24, 2024Phi-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 inferenceModels & trainingBenchmarks+1
3 slides16:28EN
Matthew Berman· Apr 23, 2024Testing 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 AIBenchmarksModels & training+1
3 slides15:01EN
Matthew Berman· Apr 19, 2024Testing 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 modelsEvalsModels & training+1
1:01:39EN
Cognitive Revolution "How AI Changes Everything"· Apr 13, 2024PodcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Host 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.Models & trainingScaling LawsSynthetic data+3
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· Apr 5, 2024PodcastA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens AheadHost 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.Models & trainingModel InterpretabilityTransformers & attention+3
3 slides14:23EN
Matthew Berman· Mar 31, 2024Testing 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 modelsModels & trainingEvals+1
1:20:44EN
Cognitive Revolution "How AI Changes Everything"· Mar 30, 2024PodcastSeeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 DaysHost Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.Models & trainingAI researchTransformers & attention+3
5 slides22:17EN
Matthew Berman· Mar 21, 2024Q* 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 computeModels & trainingAI research+2
3 slides8:26EN
Matthew Berman· Mar 18, 2024Testing Grok on X After the 2024 Grok-1 Weight ReleaseMatthew Berman · Forward FutureMatthew Berman tries coding and reasoning prompts in the hosted Grok interface, with mixed results.Open-weight modelsBenchmarksModels & training+1
4 slides19:59EN
Matthew Berman· Mar 12, 2024Testing Model Responses to Masked Harmful RequestsMatthew Berman · Forward FutureMatthew Berman compares refusals, decoding errors and inconsistent responses in informal 2024 experiments across several language models.AI SafetyAgent red teamingSecurity & safety+1
2:47:17EN
Lex Fridman· Mar 7, 2024Podcast · 2 speakersIf You Want Human-Level AI, Abandon Generative ModelsGuest Yann Lecun · Host 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.Models & trainingWorld modelsAGI+3
5 slides13:57EN
Matthew Berman· Feb 27, 2024Mistral Large: A 2024 Review of Coding, Reasoning and Safety ResponsesMatthew Berman · Forward FutureMatthew Berman reviews Mistral’s launch claims and tests the model with a small set of prompts.Models & trainingBenchmarksAI Safety+1
3 slides23:00EN
Matthew Berman· Feb 22, 2024Testing 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 modelsEvalsModels & training
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· Feb 7, 2024PodcastA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Host Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.Models & trainingAI HistoryNeuroscience & AI+3
2 slides0:42EN
Matthew Berman· Jan 31, 2024LLaVA 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 AIModels & trainingLocal inference+1
40:58EN
No Priors: AI, Machine Learning, Tech, & Startups· Jan 25, 2024Podcast · 2 speakers99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses FirstHost Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.Models & trainingRoboticsFoundation Models+3
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