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2 Folien12:50EN
Matthew Berman· 22. Mai 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 modelsEvalsModelle & Training
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Matthew Berman· 16. Mai 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
Folien27:07EN
Matthew Berman· 14. Mai 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 researchProdukt & UXModelle & Training
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Matthew Berman· 30. Apr. 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.BenchmarksModelle & TrainingCoding-Agenten+1
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Matthew Berman· 24. Apr. 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 inferenceModelle & TrainingBenchmarks+1
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Matthew Berman· 23. Apr. 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 AIBenchmarksModelle & Training+1
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Matthew Berman· 19. Apr. 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 modelsEvalsModelle & Training+1
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Cognitive Revolution "How AI Changes Everything"· 13. Apr. 2024PodcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Moderation: 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.Modelle & TrainingScaling LawsSynthetic data+3
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Cognitive Revolution "How AI Changes Everything"· 5. Apr. 2024PodcastA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens AheadModeration: 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.Modelle & TrainingModel InterpretabilityTransformers & attention+3
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Matthew Berman· 31. März 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 modelsModelle & TrainingEvals+1
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Cognitive Revolution "How AI Changes Everything"· 30. März 2024PodcastSeeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 DaysModeration: Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.Modelle & TrainingAI researchTransformers & attention+3
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Matthew Berman· 21. März 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 computeModelle & TrainingAI research+2
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Matthew Berman· 12. März 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 teamingSicherheit+1
2:47:17EN
Lex Fridman· 7. März 2024Podcast · 2 StimmenIf You Want Human-Level AI, Abandon Generative ModelsGast: Yann Lecun · Moderation: 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.Modelle & TrainingWorld modelsAGI+3
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Matthew Berman· 22. Feb. 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 modelsEvalsModelle & Training
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· 7. Feb. 2024PodcastA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Moderation: Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.Modelle & TrainingAI HistoryNeuroscience & AI+3
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Matthew Berman· 31. Jan. 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 AIModelle & TrainingLocal inference+1
40:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 25. Jan. 2024Podcast · 2 Stimmen99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses FirstModeration: Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.Modelle & TrainingRoboticsFoundation Models+3
2:30:06EN
Cognitive Revolution "How AI Changes Everything"· 22. Dez. 2023PodcastTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home TurfModeration: 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.Modelle & TrainingTransformers & attentionAI research+3
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Cognitive Revolution "How AI Changes Everything"· 17. Nov. 2023PodcastA Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.Moderation: Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.Modelle & TrainingAI researchML-Grundlagen+3
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Cognitive Revolution "How AI Changes Everything"· 14. Nov. 2023PodcastA 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.Moderation: 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.Modelle & TrainingSynthetic dataData quality & curation+3
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Matthew Berman· 7. Nov. 2023Testing Dolphin 2.2, a Mistral 7B Fine-TuneMatthew Berman · Forward FutureMatthew Berman tries a small open-weight model on coding, formatting and reasoning prompts, with mixed results.Open-weight modelsBenchmarksModelle & Training+1
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2. Nov. 2023Podcast · 2 StimmenReliability is the bottleneck. Autonomy is what would make AI feel alive.Moderation: 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.Modelle & TrainingAGIScaling Laws+3
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Cognitive Revolution "How AI Changes Everything"· 18. Okt. 2023Podcast1,000 H100s Take 115 Days; 22,000 Take FiveModeration: 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.Modelle & TrainingAI researchModel Interpretability+3
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