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18:08ENSix 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.
8:17ENUsing OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.
4:36ENTesting WizardCoder 15B as a Local Coding AssistantMatthew Berman · Forward FutureMatthew Berman runs the 2023 WizardCoder model locally, testing small Python exercises and a longer Snake game.
59:28ENFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductHost 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.
2:41:58ENZuckerberg showed up as Mark Elliott — then argued for many AIs, not oneGuest Mark Zuckerberg · Host 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.
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.
1:20:49ENA Wafer-Scale Chip So AI Stops Waiting on AmdahlHost 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 DeployGuest Emad Mostaque · Host Harry StebbingsThe Stability AI co-founder describes his 2023 vision for open models, healthcare applications and AI businesses, alongside concerns about a speculative boom.
1:06:02ENYann LeCun on Open AI Models, Safety and the Future of ResearchGuest Yann Lecun · Host Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.
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 TrickHost 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.
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.Host 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 modelsHost 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 BehindHost 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 brainHost 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 EraHost Jacob EffronArthur Mensch explains Mistral's open-source strategy, enterprise distribution, model research, and views on AI regulation and sovereignty.
1:12:15ENThe Open-Model Vibe Check: China, Containment, and the Data MoatHost Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.
45:27ENThe Agent State: How AI Flattened the Adversary Pyramid and Why Defenders Need Their Own Frontier ModelsHost Sarah Guo, Elad GilCrowdStrike CEO George Kurtz explains how low-skill attackers now wield nation-state tradecraft through AI agents, and how CrowdStrike and Nvidia are training security-specific models to fight back.
50:23ENOpenAI’s Platform Bet: Where AI Value Accrues, Why Open Source Trails, and When Superintelligence ArrivesHost Jacob EffronPeter Welinder explains OpenAI’s platform strategy, the case for proprietary frontier models over open source, the enterprise hallucination problem, and his speculative timeline for AGI and superintelligence.
1:34:27ENMatt Mullenweg on Open Source Ideals, the WP Engine Fight and Why Llama Isn't Really OpenGuest Matt Mullenweg · Host Lenny RachitskyThe WordPress co-creator and Automattic CEO gives his side of the WP Engine dispute, explains his open source philosophy, and talks AI, community building and acquisitions with Lenny Rachitsky.
33:31ENOpen Source Catches Up, Regulation Can Wait: Sarah Guo and Elad Gil Answer Listener QuestionsHost Sarah Guo, Elad GilTwo AI investors cover open-source models, autonomous agents, whether to regulate AI, where startups can win, and why healthcare innovation is so hard.
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