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59:28ENFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductModeration: Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.
10:23ENTesting Hosted Falcon 40B and Document Chat in h2oGPTMatthew Berman · Forward FutureMatthew Berman tries H2O.ai’s 2023 hosted Falcon 40B interface on coding, writing and reasoning prompts, then demonstrates document chat.
19:38ENOrca: Teaching a Smaller Model with GPT-4 ExplanationsMatthew Berman · Forward FutureMatthew Berman reviews Microsoft Research’s 2023 Orca paper and its approach to training a 13-billion-parameter model on detailed teacher responses.
2:41:58ENZuckerberg showed up as Mark Elliott — then argued for many AIs, not oneGast: Mark Zuckerberg · Moderation: Lex FridmanOn his second Lex Fridman podcast, the Meta CEO treats a disguised first jiu-jitsu tournament, an open research model called LLaMA, and a future of many agents as the same bet: ship before it is perfect, and do not build a single god model.
10:40ENTesting Nous Hermes 13B Locally: Mixed Reasoning and Unsafe ResponsesMatthew Berman · Forward FutureMatthew Berman compares a 2023 quantized model on hosted and local hardware, with uneven results across coding, logic and safety.
8:51ENFalcon 40B: A 2023 Leaderboard Result and a Slow GPU TestMatthew Berman · Forward FutureMatthew Berman tries a quantized Falcon 40B Instruct checkpoint on a hosted GPU and finds useful output but slow generation.
11:42ENGuanaco and QLoRA: A 2023 Fine-Tuning and Model TestMatthew Berman · Forward FutureMatthew Berman reviews the QLoRA paper, explains the reported memory savings and tries Guanaco 65B on an informal prompt set.
7:51ENRunning Guanaco 65B on a Cloud GPU with Runpod and Text Generation Web UIMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 workflow for renting a GPU, loading a quantized model and generating text. Model requirements, pricing and interfaces depend on the chosen version.
1:20:49ENA Wafer-Scale Chip So AI Stops Waiting on AmdahlModeration: Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.
1:11:11ENEmad Mostaque on Open AI Models, National Data and the Race to DeployGast: Emad Mostaque · Moderation: Harry StebbingsThe Stability AI co-founder describes his 2023 vision for open models, healthcare applications and AI businesses, alongside concerns about a speculative boom.
11:07ENTesting MosaicML MPT-7B Chat and StoryWriter in 2023Matthew Berman · Forward FutureMatthew Berman examines MPT-7B model variants, their licenses and a mixed set of local tests.
1:06:02ENYann LeCun on Open AI Models, Safety and the Future of ResearchGast: Yann Lecun · Moderation: Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.
14:29ENA 2023 Google Memo on Open Models, LoRA and AI’s Competitive MoatMatthew Berman · Forward FutureMatthew Berman reviews a leaked employee essay arguing that rapid community iteration could challenge proprietary AI labs, and traces the early LLaMA ecosystem.
6:53ENStableVicuna’s 2023 Release: An Early RLHF Chatbot Put to the TestMatthew Berman · Forward FutureMatthew Berman reviews the 13-billion-parameter model and tests poetry, simple code, reasoning and a resignation email.
9:58ENHuggingChat’s 2023 Debut: Testing Writing, Reasoning and Python CodeMatthew Berman · Forward FutureMatthew Berman tries the early OpenAssistant-powered HuggingChat on writing, arithmetic, logic and a Snake game, then compares a few outputs with GPT-3.5 and GPT-4. The results illustrate both promise and limitations in this small historical test.
1:13:52ENAndriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.
40:25ENA 6-Billion-Parameter Clone of ChatGPT’s Core TrickModeration: Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.
7:16ENSetting Up Alpaca Turbo for Local Language Models: A 2023 TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early ChatGPT-style interface for local Alpaca models, from the Conda setup to a short test on a Mac.
8:05ENA 2023 Guide to Running the Original GPT4All Model LocallyMatthew Berman · Forward FutureMatthew Berman demonstrates an early CPU-based GPT4All release, its terminal installation and the resources available for fine-tuning.
1:21:20ENFreeze the eyes and the brain. Train only the optic nerve.Moderation: Nathan LabenzJunnan Li and Dongxu Li tell Nathan Labenz how BLIP cleaned noisy web captions, and how BLIP-2 connected a frozen vision model to a frozen language model in under ten days on one A100.
53:37EN30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsModeration: Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.
37:26ENWithout Open Source, Machine Learning Would Be Decades BehindModeration: Sarah Guo, Elad GilHugging Face CEO Clem Delangue on the Tamagotchi pivot, why the company never hired a community manager, and why he does not believe one model will rule them all.
45:03ENEmad Mostaque’s bet: open small models, not one giant brainModeration: Sarah Guo, Elad GilStability AI’s founder tells No Priors why foundation models should be public infrastructure, why small models can beat giant ones, and what that means for media, medicine, and AGI.
40:00ENThe Winds of Change: How Mistral Plans to Win the Open-Model EraModeration: Jacob EffronArthur Mensch explains Mistral's open-source strategy, enterprise distribution, model research, and views on AI regulation and sovereignty.
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