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1:06:04ENAlexandr 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.
1:03:12ENAravind 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.
1:59:15ENA 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.
58:28ENFrom 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.
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.
21:47ENPhi-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.
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.
1:01:39ENGPT-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.
1:19:24ENA 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.
14:23ENTesting DBRX: Coding Strengths and Reasoning GapsMatthew Berman · Forward FutureMatthew Berman examines Databricks’ open-weight model and puts it through coding, arithmetic and reasoning prompts.
1:20:44ENSeeing 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.
22:17ENQ* 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.
8:26ENTesting 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.
19:59ENTesting 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.
2:47:17ENIf 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.
13:57ENMistral 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.
23:00ENTesting Google Gemma 7B at Launch: Setup MattersMatthew Berman · Forward FutureMatthew Berman compares local and hosted tests of Google’s early open-weight model.
1:58:43ENA 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.
0:42ENLLaVA 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.
40:58EN99% 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.
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