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156 件
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スライド 6 枚12:49EN
Matthew Berman· 2023年9月14日Falcon 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 modelsBenchmarksモデルと学習+1
30:03EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年9月7日ポッドキャスト · 2 人A Dinner-Plate Chip Cut Training From 60 Days to 3.5ホスト Sarah Guo, Elad GilCerebras CEO Andrew Feldman tells No Priors why wafer-scale silicon, not another GPU, is the answer to the compute crunch — and why most production models will stay at 13 billion parameters or below.インフラとデプロイInferenceAI cost & performance+3
52:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月25日ポッドキャストOpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the Listホスト 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.モデルと学習ファインチューニングAI cost & performance+3
スライド 2 枚10:22EN
Matthew Berman· 2023年8月4日Matthew Berman on Llama 2, AI Tools, Robots, and the LK-99 ClaimMatthew Berman · Forward FutureA 2023 AI news roundup covers open-weight models, synthetic influencers, tool use and robotics, alongside an early superconductivity claim that later research challenged.Open-weight modelsRoboticsAI agents+2
スライド 3 枚12:20EN
Matthew Berman· 2023年7月10日Testing 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 models評価(Evals)モデルと学習+1
スライド 6 枚18:08EN
Matthew Berman· 2023年6月29日Six 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 modelsモデルと学習+1
スライド 3 枚8:17EN
Matthew Berman· 2023年6月22日Using 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.Open-weight modelsInferenceインフラとデプロイ+1
スライド 7 枚4:36EN
Matthew Berman· 2023年6月20日Testing 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.モデルと学習Local inferenceSoftware engineering+2
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023年6月16日ポッドキャストFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Productホスト Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.モデルと学習ファインチューニングPretraining & midtraining+3
スライド 4 枚10:23EN
Matthew Berman· 2023年6月15日Testing 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.Open-weight models評価(Evals)AI research+1
2:41:58EN
Lex Fridman· 2023年6月8日ポッドキャスト · 2 人Zuckerberg showed up as Mark Elliott — then argued for many AIs, not oneゲスト Mark Zuckerberg · ホスト 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.企業と戦略Open-source ecosystemsOpen-weight models+3
スライド 2 枚10:40EN
Matthew Berman· 2023年6月7日Testing 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.Open-weight modelsLocal inferenceBenchmarks+1
スライド 4 枚11:42EN
Matthew Berman· 2023年5月31日Guanaco 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.ファインチューニングQuantizationOpen-weight models+1
1:20:49EN
Cognitive Revolution "How AI Changes Everything"· 2023年5月25日ポッドキャストA Wafer-Scale Chip So AI Stops Waiting on Amdahlホスト 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.インフラとデプロイInferenceAI cost & performance+3
1:11:11EN
20VC with Harry Stebbings· 2023年5月17日ポッドキャスト · 2 人Emad Mostaque on Open AI Models, National Data and the Race to Deployゲスト Emad Mostaque · ホスト Harry StebbingsThe Stability AI co-founder describes his 2023 vision for open models, healthcare applications and AI businesses, alongside concerns about a speculative boom.Foundation ModelsOpen-weight modelsAI in healthcare+2
1:06:02EN
20VC with Harry Stebbings· 2023年5月15日ポッドキャスト · 2 人Yann LeCun on Open AI Models, Safety and the Future of Researchゲスト Yann Lecun · ホスト Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.AI researchAI SafetyOpen-weight models+2
1:13:52EN
Matthew Berman· 2023年4月15日Andriy 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.Local inferenceOpen-weight modelsData quality & curation+2
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年4月6日ポッドキャスト · 2 人A 6-Billion-Parameter Clone of ChatGPT’s Core Trickホスト 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.モデルと学習Open-weight modelsファインチューニング+3
スライド 5 枚8:05EN
Matthew Berman· 2023年3月29日A 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.Open-weight modelsモデルと学習インフラとデプロイ
1:21:20EN
Cognitive Revolution "How AI Changes Everything"· 2023年3月9日ポッドキャストFreeze the eyes and the brain. Train only the optic nerve.ホスト 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.マルチモーダルとメディアMultimodal AI画像と動画+3
53:37EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年3月9日ポッドキャスト · 2 人30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsホスト Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.評価とオブザーバビリティAI researchFoundation Models+3
37:26EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年2月23日ポッドキャスト · 2 人Without Open Source, Machine Learning Would Be Decades Behindホスト 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.オープンソースとコミュニティOpen-source ecosystemsOpen-weight models+3
45:03EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年2月16日ポッドキャスト · 2 人Emad Mostaque’s bet: open small models, not one giant brainホスト 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.オープンソースとコミュニティOpen-weight modelsMultimodal AI+3
40:00EN
Unsupervised Learning: With Jacob EffronポッドキャストThe Winds of Change: How Mistral Plans to Win the Open-Model Eraホスト Jacob EffronArthur Mensch explains Mistral's open-source strategy, enterprise distribution, model research, and views on AI regulation and sovereignty.企業と戦略Open-source ecosystemsAI Strategy+3
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