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8:04EN
Matthew Berman· 11 jul 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.
12:20ENMatthew Berman· 10 jul 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.
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 6 jul 2023PódcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandPresenta: 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.
18:08ENMatthew Berman· 29 jun 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.
1:32:22ENCognitive Revolution "How AI Changes Everything"· 29 jun 2023PódcastA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer AwayPresenta: 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.
1:52:46ENCognitive Revolution "How AI Changes Everything"· 27 jun 2023PódcastCharge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can SeePresenta: Nathan LabenzMIT physicist Ziming Liu walks Nathan Labenz through BIMT, a brain-inspired training trick that sparsifies networks until you can read them by looking.
4:36ENMatthew Berman· 20 jun 2023Testing 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.
59:28ENCognitive Revolution "How AI Changes Everything"· 16 jun 2023PódcastFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductPresenta: Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.
2:00:19ENCognitive Revolution "How AI Changes Everything"· 6 jun 2023Pódcast1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2Presenta: Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…
11:49ENMatthew Berman· 1 jun 2023Testing Wizard-Vicuna 30B: Responses, Reasoning, and CodeMatthew Berman · Forward FutureMatthew Berman examines a model marketed as uncensored, demonstrates a 2023 cloud setup, and runs an informal collection of tests.
1:25:35ENCognitive Revolution "How AI Changes Everything"· 21 may 2023PódcastTwo and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical SchoolPresenta: Nathan LabenzVivek Natarajan walks Nathan Labenz through Med-PaLM and Med-PaLM 2: the data-light techniques, the nine-axis clinician evals, and why a high USMLE-style score is the wrong trophy.
42:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 18 may 2023Pódcast · 2 vocesTen Percent of Search Is Health — and the Doctor Is Googling TooPresenta: Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.
11:07ENMatthew Berman· 16 may 2023Testing 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.
5:24ENMatthew Berman· 12 may 2023Google I/O 2023: Bard, PaLM 2 and AI Across Google's ProductsMatthew Berman · Forward FutureMatthew Berman reviews Google's 2023 AI announcements and weighs its focus on improving established products.
4:14:33EN
Lex Fridman· 9 may 2023Pódcast · 2 vocesThe Next Token Is Not a Proof: Stephen Wolfram on ChatGPT and Computational TruthInvitado: Stephen Wolfram · Presenta: Lex FridmanIn his fourth conversation with Lex Fridman, Stephen Wolfram contrasts large language models with Wolfram|Alpha, then follows computational irreducibility from ChatGPT through observers, thermodynamics, and the three great theories of twentieth-century physics.
9:58ENMatthew Berman· 26 abr 2023HuggingChat’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.
5:47ENMatthew Berman· 19 abr 2023Sam Altman on Scaling AI Models: Matthew Berman Examines OpenAI’s 2023 DirectionMatthew Berman · Forward FutureA 2023 discussion of model scaling, possible ways to improve GPT-4 and the safety priorities OpenAI described at the time.
40:25ENNo Priors: AI, Machine Learning, Tech, & Startups· 6 abr 2023Pódcast · 2 vocesA 6-Billion-Parameter Clone of ChatGPT’s Core TrickPresenta: 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.
7:53ENMatthew Berman· 4 abr 2023HuggingGPT: Using a Language Model to Coordinate AI ToolsMatthew Berman · Forward FutureMatthew Berman explains a research system that routes multimodal tasks to specialist models using a language model as controller.
8:05ENMatthew Berman· 29 mar 2023A 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.
6:50ENMatthew Berman· 19 mar 2023Running LLaMA and Alpaca Locally: A 2023 Dalai TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup on a MacBook Air and explains the settings that control generation.
7:55ENMatthew Berman· 20 feb 2023How to Train a Custom Image Model in Leonardo.aiMatthew Berman · Forward FutureMatthew Berman walks through Leonardo.ai’s 2023 model galleries, training-set guidance, and custom model workflow, then shares results from several experiments.
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跟李沐学AI· 12 ene 2023多模态论文串讲：BLIP、CoCa 与 BEiT-3从图文数据清理到统一预训练，梳理三种视觉语言模型的结构、目标函数与相互联系。
1:07:10ZH跟李沐学AI· 29 dic 2022InstructGPT 论文精读：从人工反馈到语言模型对齐从监督微调、奖励模型到 PPO，梳理 InstructGPT 的训练流程、实验结果与局限。Cargar másMostrando 24 de 329