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2:30:06EN
Cognitive Revolution "How AI Changes Everything"· 2023년 12월 22일팟캐스트Trained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turf진행자 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.
14:04EN
Matthew Berman· 2023년 12월 15일Mistral Medium in 2023: API Pricing and Informal Model TestsMatthew Berman · Forward FutureMatthew Berman compares the original Mistral Medium prototype with Mixtral and GPT-4, then tests coding, writing and reasoning through the API.
20:49ENMatthew Berman· 2023년 12월 12일Mixtral 8x7B: Mixture-of-Experts Architecture, Setup and Early TestsMatthew Berman · Forward FutureMatthew Berman reviews Mistral AI’s December 2023 open-weight model, demonstrates a cloud setup and tests its coding and reasoning responses.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 2023년 11월 17일팟캐스트A Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.진행자 Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.
1:21:50ENCognitive Revolution "How AI Changes Everything"· 2023년 11월 14일팟캐스트A 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.진행자 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.
11:05ENMatthew Berman· 2023년 11월 7일Testing 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.
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 11월 2일팟캐스트 · 2명Reliability is the bottleneck. Autonomy is what would make AI feel alive.진행자 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.
1:19:52ENCognitive Revolution "How AI Changes Everything"· 2023년 10월 18일팟캐스트1,000 H100s Take 115 Days; 22,000 Take Five진행자 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.
13:11ENMatthew Berman· 2023년 10월 5일Testing 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.
37:01ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 9월 28일팟캐스트 · 2명DNA Is Code, but You Compile It with a Pipette진행자 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.
12:49ENMatthew Berman· 2023년 9월 14일Falcon 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.
4:35ENMatthew Berman· 2023년 9월 5일Running 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.
36:33EN
20VC with Harry Stebbings· 2023년 8월 31일팟캐스트 · 2명Noam Shazeer on Character.AI, the Cost of Training Models and the Uses of General AI게스트 Noam Shazeer · 진행자 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.
55:08ENCognitive Revolution "How AI Changes Everything"· 2023년 8월 29일팟캐스트One Model Inside 38 Products: Paige Bailey on How Google Trains and Ships PaLM 2진행자 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.
6:28ENMatthew Berman· 2023년 8월 29일A 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.
52:48ENCognitive Revolution "How AI Changes Everything"· 2023년 8월 25일팟캐스트OpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the List진행자 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.
35:24ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 8월 24일팟캐스트 · 2명The Author of Attention Is All You Need Now Compiles mRNA Like Bytecode진행자 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.
7:09ENMatthew Berman· 2023년 7월 28일AI 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.
2:13:07ENCognitive Revolution "How AI Changes Everything"· 2023년 7월 27일팟캐스트Half an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3진행자 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.
4:59ENMatthew Berman· 2023년 7월 25일Testing 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.
9:40ENMatthew Berman· 2023년 7월 20일Testing 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.
5:53ENMatthew Berman· 2023년 7월 18일Petals: 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.
8:04ENMatthew Berman· 2023년 7월 11일WizardLM 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.
12:20ENMatthew Berman· 2023년 7월 10일Testing 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.더 보기347개 중 24개 표시