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1:19:24EN
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
1:21:50EN
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
5 Folien11:05EN
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
1:19:52EN
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
5 Folien13:11EN
Matthew Berman· 5. Okt. 2023Testing Mistral 7B OpenOrca: A 2023 Cloud Setup and Prompt TrialMatthew Berman · Forward FutureMatthew Berman runs a quantized OpenOrca variant on a rented GPU and reviews coding, writing and reasoning examples.Open-weight modelsLocal inferenceBenchmarks+2
37:01EN
No Priors: AI, Machine Learning, Tech, & Startups· 28. Sept. 2023Podcast · 2 StimmenDNA Is Code, but You Compile It with a PipetteModeration: Sarah Guo, Elad GilGinkgo Bioworks CEO Jason Kelly tells No Priors why cells are worth the magic, why biology has no AWS, and why a pandemic should look like cybersecurity.Modelle & TrainingAI for scienceBiosecurity+3
6 Folien12:49EN
Matthew Berman· 14. Sept. 2023Falcon 180B: A 2023 Review of TII’s Open-Weight ModelMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and writing prompts while examining the model’s training scale and license.Open-weight modelsBenchmarksModelle & Training+1
4 Folien4:35EN
Matthew Berman· 5. Sept. 2023Running WizardCoder on a Cloud GPU: A 2023 RunPod WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates downloading a quantized 13B coding model into a hosted text-generation interface, then explains how to stop the pod and avoid ongoing charges.Modelle & TrainingInfrastruktur & DeploymentCoding-Agenten
36:33EN
20VC with Harry Stebbings· 31. Aug. 2023Podcast · 2 StimmenNoam Shazeer on Character.AI, the Cost of Training Models and the Uses of General AIGast: Noam Shazeer · Moderation: Harry StebbingsThe Character.AI co-founder explains his consumer strategy, language-model training and why he expects users to invent applications the company cannot predict.Foundation ModelsModelle & TrainingAI startups & small teams+2
55:08EN
Cognitive Revolution "How AI Changes Everything"· 29. Aug. 2023PodcastOne Model Inside 38 Products: Paige Bailey on How Google Trains and Ships PaLM 2Moderation: Nathan LabenzAt Google I/O in May 2023, PaLM 2 arrived already running in more than two dozen products — and its lead product manager walks through what that actually took.Modelle & TrainingMultimodal AIEvals+3
2 Folien6:28EN
Matthew Berman· 29. Aug. 2023A Historical GPT-3.5 Fine-Tuning WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates generating synthetic examples in Colab and training a model to use a distinctive tone.Fine-TuningSynthetic dataModelle & Training
52:48EN
Cognitive Revolution "How AI Changes Everything"· 25. Aug. 2023PodcastOpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the ListModeration: Nathan LabenzNathan Labenz and Erik Torenberg walk through GPT-3.5 Turbo fine-tuning, why self-hosting still loses on total cost, and what is actually working in code, school, and medicine.Modelle & TrainingFine-TuningAI cost & performance+3
35:24EN
No Priors: AI, Machine Learning, Tech, & Startups· 24. Aug. 2023Podcast · 2 StimmenThe Author of Attention Is All You Need Now Compiles mRNA Like BytecodeModeration: Sarah Guo, Elad GilJakob Uszkoreit on why Transformers won, why models spend compute on the wrong things, and why drug discovery has to become generation rather than screening.Modelle & TrainingAI for scienceTransformers & attention+2
5 Folien7:09EN
Matthew Berman· 28. Juli 2023AI News in July 2023: SDXL, Worldcoin, and Biological ComputingMatthew Berman · Forward FutureMatthew Berman reviews a week of AI developments, from Google’s Gemini project and new generative models to biometric identity and experiments with cultured neurons.Generative mediaModelle & TrainingBrain-Computer Interfaces+2
2:13:07EN
Cognitive Revolution "How AI Changes Everything"· 27. Juli 2023PodcastHalf an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3Moderation: Nathan LabenzArthur Conmy walks Nathan Labenz through ACDC, the algorithm that automates the most tedious step of mechanistic interpretability: finding which transformer components actually do a task.Modelle & TrainingModel InterpretabilityAI research+3
2 Folien4:59EN
Matthew Berman· 25. Juli 2023Testing Airoboros L2 70B on Coding, Writing and ReasoningMatthew Berman · Forward FutureMatthew Berman runs a small set of prompts against a Llama 2 fine-tune, finding useful structured output alongside failures on code and logic.Open-weight modelsEvalsModelle & Training+1
7 Folien9:40EN
Matthew Berman· 20. Juli 2023Testing Llama 2 70B on Coding, Writing and ReasoningMatthew Berman · Forward FutureMatthew Berman tries Meta’s 70-billion-parameter chat model through a hosted interface, highlighting both useful outputs and inconsistent reasoning.Open-weight modelsBenchmarksModelle & Training+2
2 Folien5:53EN
Matthew Berman· 18. Juli 2023Petals: Distributing Large Language Model Inference Across DevicesMatthew Berman · Forward FutureIn 2023, Matthew Berman explains Petals as a way to use large models through a network of participating computers rather than loading every layer on one device.Distributed training & inferenceLocal inferenceInference+2
5 Folien8:04EN
Matthew Berman· 11. Juli 2023WizardLM 13B v1.1 Tested on Coding, Writing and LogicMatthew Berman · Forward FutureMatthew Berman tries an instruction-tuned model on a small set of prompts, with mixed results and several subjective scoring choices.EvalsOpen-weight modelsModelle & Training+1
3 Folien12:20EN
Matthew Berman· 10. Juli 2023Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.Open-weight modelsEvalsModelle & Training+1
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 6. Juli 2023PodcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandModeration: Nathan LabenzNathan Labenz spends a solo episode walking through what general-purpose models can do, how they are trained, how capabilities unlock, and whether they understand anything at all.Modelle & TrainingML-GrundlagenScaling Laws+3
6 Folien18:08EN
Matthew Berman· 29. Juni 2023Six Language Models Compared on an Informal 2023 Prompt SetMatthew Berman · Forward FutureMatthew Berman tests coding, writing and reasoning with H2O GPT, finding a tie under a small and subjective rubric.BenchmarksOpen-weight modelsModelle & Training+1
1:32:22EN
Cognitive Revolution "How AI Changes Everything"· 29. Juni 2023PodcastA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer AwayModeration: Nathan LabenzLili Yu of Meta AI explains a multiscale transformer that predicts million-byte sequences, skips tokenization, and aims to model any file as raw bytes.Modelle & TrainingMultimodal AITransformers & attention+3
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