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跨国串门儿计划
跨国串门儿计划#447.2026 AI 趋势展望：推理革命、智能体进化与“氛围编程”的崛起📝 本期播客简介本期我们克隆了：硅谷知名 AI 技术播客《The TWIML AI Podcast》AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More with Sebastian Raschka - #762当预训练技术趋于成熟，大模型的下一个增长点在哪里？本期嘉宾 Sebastian Raschka 是一位顶尖的独立 LLM 研究员，也是畅销书《从头开始构建大语言模型》的作者。他认为我们正处于一场“推理革命”之中。在这期节目中，Sebastian 将深度拆解 DeepSeek R1 和 OpenAI o1 背后的技术逻辑，解释为什么“后期训练”和“可验证奖励”成为了压榨模型性能的关键。他还会分享自己如何利用 AI 进行“氛围编程”，在不精通 Swift 的情况下开发出原生的 macOS 应用。无论你是关注底层架构的开发者，还是希望利用 AI 提升效率的普通用户，这期关于 2026 年 AI 趋势的深度对谈都不容错过。👨‍⚕️ 本期嘉宾Sebastian Raschka，独立 LLM 研究员、知名 AI 教育家。他曾任 Lightning AI 研究主管，并著有《Python Machine Learning》和《Build a Large Language Model from Scratch》等多部经典著作。他致力于将复杂的 AI 理论转化为可落地的代码实践。⏱️ 时间戳00:00 开场 & 嘉宾介绍LLM 的范式转移01:50 推理革命：从“记忆提取”到“逻辑思考”的跨越03:54 工具包装器（Tool Wrapper）的兴起：大模型不再是孤岛07:37 渐进式改进：模型健壮性与“生活质量”的提升“氛围编程”与个人工作流11:05 开发者的新姿势：利用 LLM 构建自定义 macOS 效率工具13:54 确定性工具 vs 随机性模型：如何找到最佳平衡点15:33 氛围编程（Vibe Coding）：技术门槛的瓦解与底层原理的价值17:45 社交媒体上的“一次性搞定”：是奇迹还是幸存者偏差？深度拆解推理技术19:24 2026 三大核心主题：推理、推理侧扩展与智能体化22:03 可验证奖励（Verifiable Rewards）：为什么数学和代码走在最前面24:13 过程奖励模型（PRM）：如何教 AI 检查自己的思考步骤27:27 推理侧扩展：用推理阶段的算力换取更高的准确率30:59 自我改进（Self-Refinement）：让模型在循环中进化智能体与未来架构33:35 智能体（Agents）：从单次对话到闭环任务处理的演进35:54 多智能体系统：是噱头还是未来的生产力基石？38:45 架构演进：MoE、MLA 与稀疏注意力的实战落地43:00 持续学习的迷思：长上下文是否取代了模型更新的需求？46:23 文本扩散模型：Transformer 之外的另一种可能教育与新书预告47:31 从头构建推理模型：Sebastian 的新书计划与实验心得50:15 学习路径建议：如何系统掌握 LLM 的完整生命周期🌟 精彩内容💡 推理革命：后期训练成为新战场Sebastian 指出，预训练已经非常成熟，现在的“低垂果实”在于后期训练。通过推理侧扩展（Inference Scaling），我们可以在模型生成答案时投入更多算力，让模型拥有更多“思考时间”，从而解决复杂的逻辑问题。🛠️ 氛围编程（Vibe Coding）的实践嘉宾分享了自己如何通过 LLM 在短时间内开发出处理播客章节、arXiv 论文链接的 macOS 应用。他强调，LLM 的最大收益不在于直接完成任务，而在于帮助用户开发出“运行逻辑确定”的工具。🚀 可验证奖励与 DeepSeek 的突破讨论了 DeepSeek R1 如何利用数学和代码的确定性规则提供奖励信号。这种范式消除了人工标注的模糊性，使得模型可以通过强化学习进行大规模的自我进化。💻 架构的微调与创新虽然 Transformer 依然稳坐江山，但 DeepSeek 引入的 MLA（多头潜变量注意力）和稀疏注意力机制，证明了通过计算换内存、降低 KV 缓存成本在超大规模模型中的可行性。❤️ 持续学习与个人化Sebastian 认为，真正的自动化持续学习仍是梦想。目前，长上下文窗口和 RAG（检索增强生成）在很大程度上缓解了对实时更新模型的需求，但在处理具有广泛影响的新信息时，模型更新依然不可或缺。🌐 播客信息补充翻译克隆自：The TWIML AI Podcast:AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More
2026-03-0352 minDuarte O.Carmo\'s articles
Duarte O.Carmo's articles#64 Retrospectiva #5 I share a February roundup: returning home to Copenhagen, winter runs on Denmark’s flat terrain, and taking Allegra everywhere with the Ergo Baby Omni 360. On the tech side, I’m leaning more on coding agents, experimenting with agent skills and Pi, and I’ve replaced GitHub Copilot with my local llama.vim fork, llama.lua. I also highlight standout reads on AlphaFold and open-weight LLMs, Anthropic’s distillation-attack post, a few books I’m exploring, three timely podcast episodes, and my annual binge of Drive to Survive. Relevant links: Original article Instagram: Flattest countries in Europe Ergo Baby...
2026-03-0100 minThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More with Sebastian RaschkaIn this episode, Sebastian Raschka, independent LLM researcher and author, joins us to break down how the LLM landscape has changed over the past year and what is likely to matter most in 2026. We discuss the shift from raw model scaling to reasoning-focused post-training, inference-time techniques, and better tool integration. Sebastian explains why methods like self-consistency, self-refinement, and verifiable-reward reinforcement learning have become central to progress in domains like math and coding, and where those approaches still fall short. We also explore agentic workflows in practice, including where multi-agent systems add real value and where reliability constraints still dominate...
2026-02-271h 18Latent Space: The AI Engineer Podcast
Latent Space: The AI Engineer Podcast[LIVE] Anthropic Distillation & How Models Cheat (SWE-Bench Dead) | Nathan Lambert & Sebastian RaschkaSwyx joined SAIL! Thank you SAIL Media, Prof. Tom Yeh, 8Lee, Hamid Bagheri, c9n, and many others for tuning into SAIL Live #6 with Nathan Lambert and Sebastian Raschka, PhD. Sharing here for the LS paid subscribers.We covered: This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe
2026-02-2652 minDjango Chat
Django ChatFreelancing & Community - Andrew Miller🔗 Links Personal website GitHub, Mastodon, and LinkedIn In Progress podcast Hamilton Rock Comprehension Debt Builder Methods 📦 Projects django-prodserver django-health-check Online Community Working Group 📚 Books How to Build a LLM From Scratch by Sebastian Raschka World of Astrom Rob Walling books Jonathan Stark books David Kadavy books Manifesto of winning without pitching 🎥 YouTube YouTube Channel: @djangochat Sponsor This episode is brought to you by Six Feet Up, the Python, Django, and AI experts who solve hard software problems. Whether it’s scaling an application, deriving insights from data, or getting results from A...
2026-02-251h 00Digital Disruption with Geoff Nielson
Digital Disruption with Geoff NielsonLLMs in 2026: What’s Real, What’s Hype, and What’s Coming NextIs AI actually going to replace developers? Or is the hype getting ahead of reality?On this episode of Digital Disruption, we’re joined by Sebastian Raschka, AI Research Engineer and author.Sebastian Raschka sits down with Geoff Nielson to unpack the real state of Large Language Models (LLMs) in 2026. As an LLM research engineer, Sebastian bridges deep technical expertise with practical, real-world AI implementation. In this conversation, he cuts through AI hype to focus on what’s actually achievable with modern LLMs, reasoning models, reinforcement learning, and inference scaling and where the limitations still exis...
2026-02-231h 14Miner Vino
Miner VinoREAD/DOWNLOAD Build a Large Language Model (From Scratch) EBOOKTo Read or Download Build a Large Language Model (From Scratch) by Sebastian Raschka Visit Link Bellow You Can Download Or Read Free Books   Link To Download => https://softebooks.com/?book=1633437167 Available versions: EPUB, PDF, MOBI, DOC, Kindle, Audiobook, etc. read (PDF) Build a Large Language Model (From Scratch) pdf read (PDF) Build a Large Language Model (From Scratch) ebook read (PDF) Build a Large Language Model (From Scratch) PDF [All Chapters]
2026-02-0600 minMiner Vino
Miner VinoREAD/DOWNLOAD Build a Large Language Model (From Scratch) EBOOKTo Read or Download Build a Large Language Model (From Scratch) by Sebastian Raschka Visit Link Bellow You Can Download Or Read Free Books   Link To Download => https://softebooks.com/?book=1633437167 Available versions: EPUB, PDF, MOBI, DOC, Kindle, Audiobook, etc. read (PDF) Build a Large Language Model (From Scratch) pdf read (PDF) Build a Large Language Model (From Scratch) ebook read (PDF) Build a Large Language Model (From Scratch) PDF [All Chapters]
2026-02-0600 min播客翻译计划
播客翻译计划2026 AI 现状大盘点：中美竞赛、Scaling Laws 与 AGI 终局📝 本期播客简介本期节目我们翻译了著名访谈播客《Lex Fridman Podcast》。主持人 Lex Fridman 邀请了两位 AI 领域的顶尖研究者与教育家——艾伦人工智能研究所（Ai2）后训练负责人 Nathan Lambert，以及《从零开始构建大语言模型》的作者 Sebastian Raschka。这场长达四小时的深度对话，全面剖析了 2026 年人工智能的最新版图。从 DeepSeek R1 引发的全球震荡，到中美 AI 巨头的算力博弈；从 Scaling Laws 是否失效的争议，到推理模型（Reasoning Models）如何改变编程与科研的范式。您将听到专家们对 GPT-5、Claude 4.5、Gemini 3 以及国产开源模型实战表现的硬核点评，并深入理解预训练、后训练与推理时计算（Inference-time Compute）背后的技术逻辑。这不仅是一场技术趋势的预判，更是一份理解 AI 时代底层演进的权威指南。⚙️ 本期嘉宾Nathan Lambert：艾伦人工智能研究所（Ai2）后训练负责人，RLHF（基于人类反馈的强化学习）领域的权威专家，著有《The RLHF Book》。Sebastian Raschka：著名机器学习研究员、工程师，著有《从零开始构建大语言模型》及《从零开始构建推理模型》，致力于 AI 技术的普及与教育。🌟 精彩内容🇨🇳 “DeepSeek 时刻”：国产开源模型的全球突围DeepSeek R1 的发布被视为 AI 领域的里程碑。嘉宾们探讨了中国公司如何通过更高效的架构（如 MLA 潜在注意力机制）和更低的算力成本，实现了比肩甚至超越美国顶尖闭源模型的性能。这标志着 AI 竞赛从单纯的“堆算力”转向了更精巧的架构创新。📈 Scaling Laws 还在起作用吗？尽管有传言称预训练的收益正在递减，但嘉宾们依然看好扩展定律。除了传统的预训练规模，现在的重心已转向“推理时缩放”（Inference-time Scaling）——即让模型在回答前进行更长时间的“思考”。这种范式转移正在解锁 AI 在复杂数学、编程和逻辑推理上的新高度。💻 AI 编程的进化：从辅助到代理对话深入探讨了 Cursor、Claude Code 等工具如何改变开发者工作流。Sebastian 分享了他在紧急时刻利用 AI 瞬间生成 Bash 脚本的经历。专家们认为，未来的编程将更多是“用英语编程”，开发者将从微观的代码编写者转变为宏观的系统架构师。🤖 AGI 的时间线与终局面对动辄数千亿美金的算力投入，AGI（通用人工智能）是否只是一个昂贵的幻梦？嘉宾们讨论了 AI 商业化的路径、硅谷的泡沫现状，以及 AI 代理（Agents）如何在 2026 年真正进入生产力环节，解决现实世界中的复杂任务。🌐 播客信息补充翻译克隆自：#490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI本播客由 AI 进行音频制作，你可以在 Bayt 播客上收听任何播客的中文翻译，并查看双语字幕。人工智能, DeepSeek, Scaling Laws, LLM, AGI, Transformer, RLHF, 推理模型, 中美AI竞赛, 开源模型, 编程AI, GPU, 算力, AI代理, Lex Fridman
2026-02-034h 30Build Wiz AI Show
Build Wiz AI ShowAI 2026: Scaling Laws, China, and the Race for AGIIs the global AI landscape shifting toward a "DeepSeek moment" where cheaper, open-weight models from China challenge the dominance of US frontier labs? Join machine learning experts Sebastian Raschka and Nathan Lambert as they dissect the technical breakthroughs of 2025, from the evolving physics of inference-time scaling to the intensifying competition between organizations like OpenAI, Anthropic, and their international counterparts. Listeners will discover how these advancements are fundamentally transforming the future of software engineering and explore the realistic, often "jagged" roadmap toward AGI.
2026-02-0217 minInsight Distillery (Deutsch)
Insight Distillery (Deutsch)Der Stand der KI 2026: Von Skalierungsgrenzen zu Agent WarsEine Synthese des Lex Fridman Podcasts mit Sebastian Raschka und Nathan Lambert zum aktuellen Stand der KI, mit Untersuchung des DeepSeek-Moments, der Skalierungsgesetze-Debatte und dem Aufstieg autonomer Agenten.
2026-02-0210 minInsight Distillery
Insight DistilleryThe State of AI in 2026: From Scaling Walls to Agent WarsA synthesis of the Lex Fridman Podcast with Sebastian Raschka and Nathan Lambert on the current state of AI, examining the DeepSeek moment, scaling laws debate, and the rise of autonomous agents.
2026-02-0209 minLex Fridman Podcast
Lex Fridman Podcast#490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGINathan Lambert and Sebastian Raschka are machine learning researchers, engineers, and educators. Nathan is the post-training lead at the Allen Institute for AI (Ai2) and the author of The RLHF Book. Sebastian Raschka is the author of Build a Large Language Model (From Scratch) and Build a Reasoning Model (From Scratch). Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep490-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/ai-sota-2026-transcript CONTACT LEX: ...
2026-02-0100 min今日深度AI
今日深度AI2026年AI现状：架构、竞争与人类未来本期播客来自《Lex Fridman Podcast》与机器学习专家 Sebastian Raschka 和 Nathan Lambert 对 2025 至 2026 年 人工智能发展态势 的深度对话。内容核心聚焦于 DeepSeek 等中国开源模型对全球竞争格局的冲击，并详细对比了 OpenAI、Anthropic 和 Google 等巨头在代码能力与推理模型上的差异。探讨了 比例定律 (Scaling Laws) 在预训练与推理端的持续演进，同时分析了 数据质量、合成数据以及版权争议 对未来技术路径的影响。文中还分享了关于 智能体、机器人学以及 AGI 路线图 的专业见解，强调了“从零开始构建”对技术理解的重要性。此外，访谈深入触及了 AI 时代下的 人类职业意义、教育变革以及社交媒体中的“内容废料”问题。最后，作者们对 开源精神与地缘政治 下的算力分配进行了展望，试图勾勒出 AI 深度融入人类社会后的复杂图景。
2026-02-0115 minThe MAD Podcast with Matt Turck
The MAD Podcast with Matt TurckState of LLMs 2026: RLVR, GRPO, Inference Scaling — Sebastian RaschkaSebastian Raschka joins the MAD Podcast for a deep, educational tour of what actually changed in LLMs in 2025 — and what matters heading into 2026.We start with the big architecture question: are transformers still the winning design, and what should we make of world models, small “recursive” reasoning models and text diffusion approaches? Then we get into the real story of the last 12 months: post-training and reasoning. Sebastian breaks down RLVR (reinforcement learning with verifiable rewards) and GRPO, why they pair so well, what makes them cheaper to scale than classic RLHF, and how they “unlock”...
2026-01-291h 08Build Wiz AI Show
Build Wiz AI ShowUnderstanding the 4 Main Approaches to LLM Evaluation - from Sebastian RaschkaDemystify Large Language Model (LLM) evaluation, breaking down the four main methods used to compare models: multiple-choice benchmarks, verifiers, leaderboards, and LLM judges. We offer a clear mental map of these techniques, distinguishing between benchmark-based and judgment-based approaches to help you interpret performance scores and measure progress in your own AI development. Discover the pros and cons of each method—from MMLU accuracy checks to the dynamic Elo ranking system—and learn why combining them is key to holistic model assessment.Original blog post: https://magazine.sebastianraschka.com/p/llm-evaluation-4-approaches
2025-10-0815 minGenerative AI Group Podcast
Generative AI Group PodcastWeek of 2025-09-14Alex: Hello and welcome to The Generative AI Group Digest for the week of 14 Sep 2025! Maya: We're Alex and Maya. Alex: First up, we’re talking about hallucinations in large language models. Shapath shared a paper from OpenAI explaining hallucinations as a feature designed through the reward function. Maya: Hallucinations as a feature? That sounds counterintuitive. Why would anyone want their AI to “hallucinate”? Alex: Good question! Shalabh pointed out that current evaluation methods push LLMs to guess answers even when unsure, instead of admitting uncertainty. So, hallucinations often stem from the training incentives. Maya: So it's not just a bug, b...
2025-09-1400 minThe UpstreamLife
The UpstreamLifeWar to deploy LLMs in enterprises is wide open, adoption of GPTs require experts - Arun of Articul8In this episode we talk to Arun, the founder of Articul8, an LLM company that focuses on building models specifically trained for enterprise scale and security. Learn a lot more about the AI wars in this episode, which is similar to the cloud wars that began more than a decade ago between AWS, Google Cloud and Microsoft Azure. This time around startups like Articul8 have the ability to scale in a niche market. Let us find out Arun's strategy to scale the company. 00:00 - Introduction.04:26 - Training the AI models.11:40 - AI stack and how w...
2025-09-1358 minAhmad Hardyoni
Ahmad HardyoniDownload [ePub]’ Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python By Sebastian Raschka on Textbook Full FormatLink To Download : https://topweeklybook.blogspot.com/id/1801819319 Available versions: EPUB, PDF, MOBI, DOC, Kindle, Audiobook, etc. Reading Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Download Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python PDF/EBooks Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python You Can Download Or Read Free Books
2025-09-0300 min北雍ECC｜中国视野趣谈世界
北雍ECC｜中国视野趣谈世界【北雍读书】大语言模型架构对比本期为英文。自最初的GPT架构开发以来，已经过去七年。回顾GPT-2（2019年），并再看DeepSeek-V3和Llama 4（2024-2025年），人们可能会惊讶于这些模型在结构上仍然如此相似。位置嵌入（positional embeddings）已经从绝对位置编码演进到旋转位置编码（RoPE），多头注意力机制（Multi-Head Attention）很大程度上已经让位给分组查询注意力机制（Grouped-Query Attention），更高效的SwiGLU也取代了GELU等激活函数。但在这些细微改进之下，真的有突破性的变化吗？还是只是在打磨相同的架构基础？比较大语言模型以确定促成其某些好的或是不好的性能的关键要素非常困难：数据集、训练技术和超参数差异很大，而且往往没有很好的文档记录。然而，检查架构本身的结构性变化仍然很有价值，可以了解2025年大语言模型开发者们在做什么。在这期内容所分析的文章中，作者没有讨论基准性能或训练算法，而是专注于定义当今旗舰开源模型的架构发展。参考文章：The Big LLM Architecture Comparison作者：Sebastian Raschka
2025-08-2819 min北雍ECC｜中国视野趣谈世界
北雍ECC｜中国视野趣谈世界【北雍读书】从 GPT-2 到 GPT-OSS：架构演进深度解析本期为英文。DeepSeek 于上周8月21日底低调放出了v3.1，采用了混合推理架构，允许模型在同一架构下支持思考模式（Reasoning Mode）和非思考模式（Non-Reasoning Mode），其中思考模式优化了多步推理能力，在复杂任务（如数学、编程、知识问答）中表现更强，同时 推理速度比 DeepSeek-R1-0528 更快，思维链压缩训练使输出 token 减少了 20%-50%，效率大幅提升。在工具使用和智能体任务、多语言优化方面有了显著提升，并进行128K 长上下文支持。DeepSeek-V3.1 的 Base 模型 和 后训练模型 已在 Hugging Face 和 魔搭（ModelScope） 平台开源。“知己知彼，百战不殆”，我们暂且把目光移到 OpenAI8月5日刚开源的 GPT-OSS，一起梳理它从GPT-2 一路走来的架构演进。参考文章：From GPT-2 to gpt-oss: Analyzing the Architectural Advances，作者：Sebastian Raschka
2025-08-2721 minSmart Enterprises: AI Frontiers
Smart Enterprises: AI FrontiersMastering Reasoning LLMs: Decoding AI's Complex Problem-Solving StrategiesJoin us for an insightful exploration into the world of Reasoning LLMs, drawing on the expertise of Sebastian Raschka, PhD. This episode demystifies how Large Language Models (LLMs) are being refined to excel at complex tasks that require intermediate steps, such as solving puzzles, advanced mathematics, and challenging coding problems, moving beyond simple factual question-answering.We'll uncover the four main approaches currently used to build and improve these specialised reasoning capabilities:Inference-time scaling: Discover how techniques like Chain-of-Thought (CoT) prompting encourage LLMs to generate intermediate reasoning steps, mimicking a 'thought process' and often leading to more...
2025-07-3033 minL\'IA aujourd\'hui !
L'IA aujourd'hui !L'IA aujourd'hui épisode du 2025-07-08Bonjour et bienvenue dans le podcast de l'IA par l’IA qui vous permet de rester à la page ! Aujourd’hui : l'impact de l'IA sur la création de contenu, les avancées technologiques de Google, et les défis éthiques des modèles de langage.Commençons par l'évolution de l'IA dans la création de contenu. L'utilisation de l'intelligence artificielle pour générer des œuvres érotiques ou des contenus intimes suscite des débats. Bien que certains robots soient capables de produire des textes suggestifs, ils manquent de la profondeur émotionnelle et de l'unicité humaine. Les entreprises d'IA proposent des p...
2025-07-0803 minFwdays Tech Talks
Fwdays Tech TalksАнатомія ШІ: дизайн концепти та процес розробки з нуляЗустрічайте восьмий випуск Fwdays Architecture Talks! Наші постійні спікери — Олександр Савченко, Йожеф Гісем та гість випуску Дмитро Овчаренко, AI CTO of Ministry of Digital Transformation, обговорять теми: — Reference Architecture(s), Patterns, Styles для AI — Процес створення кастомної LLM - Тренування моделей - Основні quality attributes (performance, caching, availability, security, ethical aspects) — Як з'являються AI/GenAI інженери та де їх шукати? Запрошуємо вас на конференцію Highload fwdays'25: https://bit.ly/3DitOVr Корисні посилання: — AI Enterprise Architecture: - https://opea-project.github.io/latest/framework/framework.html - https://www.nvidia.com/en-us/data-center/products/ai-enterprise/ - FTI - https://learning.oreilly.com/library/view/llm-engineers-handbook/9781836200079/ — What are Large Language Models (LLMs)? by Databricks - https://www.databricks.com/glossary/large-language-models-llm — Continius pre-training vs finetuning - https://www.linkedin.com/pulse/teaching-old-dog-new-tricks-difference-between-lewis-ms-ccrp-ches-3abqc/ — Inference high-load and LLM in production - https://www.youtube.com/watch?v=NJ1jAfWR84k&list=WL&index=11&t=134s, — Recommended Book by O.Savchenko: Build a Large Language Model (From Scratch) by Sebastian Raschka - https://www.amazon.com/Build-Large-Language-Model-Scratch/dp/1633437167 - Code f...
2025-05-021h 34AI Ketchup 🍅 | Your Business\'s Secret Sauce
AI Ketchup 🍅 | Your Business's Secret SauceState of Reasoning Models, Building LLMs from Scratch and 7 Years of Scaling GPT | Sebastian RaschkaJoin us for an insightful conversation with Sebastian Raschka, a renowned machine learning expert and author who has significantly contributed to AI education through his book "Build a Large Language Model from Scratch." Sebastian shares his journey in machine learning, offers advice for newcomers to the field, discusses the latest advancements in reasoning models, and explores the future of model architectures.TOPICS DISCUSSED:1. Learning AI from ScratchSebastian discusses effective approaches to learning AI today, emphasizing the importance of finding balance between theory and practical projects, and maintaining focus despite the overwhelming amount...
2025-03-2756 minAccidental Tech Podcast
Accidental Tech PodcastNo Longer ery Good Follow-up: Flighty has other perks (via Stephen Klinck) First reports of Invites use in the wild (via Jim Weinert) You can use a cable with Sidecar (via Matt West) Why not use a Wi-Fi hotspot for “cellar Macs”? Tailgate Tub Why not AirPlay to Sonos speakers? (via Ryan Powers) DeepSeek censorship across models (via Sebastian Raschka) Technical report Has Apple ever… used… Screen Time? (via Jonathan) macOS UNIX certification (via Paulo Pinto) Thom at OSnews Migrate purchases from one Apple Account to another The new JoyCons do act as a mouse An alternative for Apple TV audio (via Nicholas Correnti) /r/TVTooHi...
2025-02-131h 572B Bolder Podcast : Career Growth and Insights from Women in Business, Tech & Sports
2B Bolder Podcast : Career Growth and Insights from Women in Business, Tech & Sports#122 Ria Cheruvu AI Architect, ML Engineer and Data Scientist, Industry Speaker, and InstructorIn episode #122, discover the inspiring journey of Ria Cheruvu, a prodigious AI architect at Intel, who challenges the status quo with her groundbreaking work from a young age. Ria's incredible story takes us through her accelerated academic achievements and dedication to security, privacy, and fairness in AI systems. We explore her passion for the convergence of neuroscience and cognitive computing and her advocacy for women in STEM, showcasing how she is shaping the future of technology with her innovative mindset.Ria shares her inspiring journey as a young AI architect at Intel. She offers insights into her...
2025-01-0939 minAI Stories
AI StoriesBuild LLMs From Scratch with Sebastian Raschka #52Our guest today is Sebastian Raschka, Senior Staff Research Engineer at Lightning AI and bestselling book author.In our conversation, we first talk about Sebastian's role at Lightning AI and what the platform provides. We also dive into two great open source libraries that they've built to train, finetune, deploy and scale LLMs.: pytorch lightning and litgpt. In the second part of our conversation,  we dig into Sebastian's new book: "Build and LLM from Scratch". We discuss the key steps needed to train LLMs, the differences between GPT-2 and more recent models like Llama 3.1, multimodal L...
2024-11-211h 06AIContext | AI每日播报
AIContext | AI每日播报2024.09.29 | AI 新闻速递🧠 GPT风格文本分类器教程：从零到英雄机器学习专家Sebastian Raschka发布详细教程，教你如何构建GPT风格的文本分类器，并开源代码，助力商业应用。🔄 OpenAI高层震荡：权力斗争与市场担忧OpenAI三位高层辞职，苹果退出65亿美元融资，公司转型盈利之路面临内部管理与文化挑战。🌐 Oryx多模态模型：视觉与3D的新纪元清华大学等团队推出Oryx模型，高效处理图像、视频和3D场景，成为多模态领域的开源新标杆。🔍 数据增强：视觉强化学习的效率革命最新研究揭示数据增强在视觉强化学习中的关键作用，提升样本利用效率，为算法优化指明新方向。
2024-09-2902 minInterconnects
InterconnectsInterviewing Sebastian Raschka on the state of open LLMs, Llama 3.1, and AI educationThis week, I had the pleasure of chatting with Sebastian Raschka. Sebastian is doing a ton of work on the open language model ecosystem and AI research broadly. He’s been writing the great Ahead of AI newsletter (that has the biggest audience overlap with Interconnects, at 26%, so a lot of you know him) and multiple educational books, all on top of being a full time machine learning engineer at Lightning.ai, where he maintains LitGPT, which he described as being like Karpathy’s NanoGPT, with slightly more abstractions.This conversation mostly surrounds keeping up with AI rese...
2024-08-011h 03Interconnects
InterconnectsInterviewing Sebastian Raschka on the state of open LLMs, Llama 3.1, and AI educationThis week, I had the pleasure of chatting with Sebastian Raschka. Sebastian is doing a ton of work on the open language model ecosystem and AI research broadly. He’s been writing the great Ahead of AI newsletter (that has the biggest audience overlap with Interconnects, at 26%, so a lot of you know him) and multiple educational books, all on top of being a full time machine learning engineer at Lightning.ai, where he maintains LitGPT, which he described as being like Karpathy’s NanoGPT, with slightly more abstractions.This conversation mostly surrounds keeping up with AI rese...
2024-08-011h 03Vanishing Gradients
Vanishing GradientsEpisode 26: Developing and Training LLMs From ScratchHugo speaks with Sebastian Raschka, a machine learning & AI researcher, programmer, and author. As Staff Research Engineer at Lightning AI, he focuses on the intersection of AI research, software development, and large language models (LLMs).How do you build LLMs? How can you use them, both in prototype and production settings? What are the building blocks you need to know about?​In this episode, we’ll tell you everything you need to know about LLMs, but were too afraid to ask: from covering the entire LLM lifecycle, what type of skills you need to work with them, what type...
2024-05-151h 51Super Data Science: ML & AI Podcast with Jon Krohn
Super Data Science: ML & AI Podcast with Jon Krohn767: Open-Source LLM Libraries and Techniques, with Dr. Sebastian RaschkaJon Krohn sits down with Sebastian Raschka to discuss his latest book, Machine Learning Q and AI, the open-source libraries developed by Lightning AI, how to exploit the greatest opportunities for LLM development, and what’s on the horizon for LLMs.This episode is brought to you by the DataConnect Conference, and by Data Universe, the out-of-this-world data conference. Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.In this episode you will learn:• All about Machine Learning Q and AI [04:13]• Sebastian Raschka’s role as Staff Research Engineer...
2024-03-191h 48The Python Show
The Python Show34 - LLMs and Python with Sebastian RaschkaThis week, we welcome Sebastian Raschka as our guest on The Python Show.Sebastian works for Lightning AI and writes the popular Ahead of AI newsletter. He is also the author of the following books:* Machine Learning Q and AI* Machine Learning with PyTorch and Scikit-learn* Build a Large Language Model (From Scratch)We talked about machine learning, AI, book writing, Python and so much more! Get full access to The Python Show at www.pythonshow.com/subscribe
2024-03-1342 minLeading With Data
Leading With Data#22: Unpacking the Essence of AI Education | Sebastian Raschka, AI Staff Educator @ Lightning AI | Leading With Data Ep 22In this episode of Leading With Data, we interact with Sebastian Raschka, AI Staff Educator at Lightning AI. Sebastian Raschka is a best-selling author of books on AI, Machine Learning, python programming, etc. He has a strong passion for education and wants to make AI and Deep Learning accessible. Watch as he delves into: 👉 How he got hooked on writing books and became an AI Researcher 👉 Explains his role at Lightning AI, where they’re optimizing LLM models by building innovative platforms 👉 Emphasises building models from Scratch 👉 Talks about why cutting-edge tools may not always be the solution for real-world pro...
2024-02-0755 minLatent Space: The AI Engineer Podcast
Latent Space: The AI Engineer PodcastNeurIPS 2023 Recap — Best PapersWe are running an end of year listener survey! Please let us know any feedback you have, what episodes resonated with you, and guest requests for 2024! Survey link here.NeurIPS 2023 took place from Dec 10–16 in New Orleans. The Latent Space crew was onsite for as many of the talks and workshops as we could attend (and more importantly, hosted cocktails and parties after hours)!Picking from the 3586 papers accepted to the conference (available online, full schedule here) is an impossible task, but we did our best to present an audio guide with brief co...
2023-12-243h 20tasitigerbook
tasitigerbookPDF READ FREE Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 Read *book $ePub**Download Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 Full Edition,Full Version,Full Book** by Sebastian Raschka Reading Now at : https://happyreadingebook.club/?book=1789955750 OR DOWNLOAD EBOOK NOW! [PDF] Download PDF READ FREE Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 Read *book $ePub Ebook | READ ONLINE Download PDF READ FREE Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 Read *book $ePub read ebook online PDF EPUB...
2023-09-0600 mintuneadmaulbook
tuneadmaulbook{PDF EBOOK EPUB KINDLE} Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python PDF EBOOK DOWNLOAD**Download Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Full Edition,Full Version,Full Book** by Sebastian Raschka Reading Now at : https://happyreadingebook.club/?book=1801819319 OR DOWNLOAD EBOOK NOW! [PDF] Download {PDF EBOOK EPUB KINDLE} Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python PDF EBOOK DOWNLOAD Ebook | READ ONLINE Download {PDF EBOOK EPUB KINDLE} Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python...
2023-09-0400 minsymanrmysbook
symanrmysbookEbook Reader Reviews Machine Learning with PyTorch and Scikit-Learn Develop machine learning and deep learning models with Python Free eBook Downloads**Download Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Full Edition,Full Version,Full Book** by Sebastian Raschka Reading Now at : https://happyreadingebook.club/?book=1801819319 OR DOWNLOAD EBOOK NOW! [PDF] Download Ebook Reader Reviews Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Free eBook Downloads Ebook | READ ONLINE Download Ebook Reader Reviews Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Free eBook...
2023-08-2900 minlymseiofaren
lymseiofarenREADDOWNLOAD=^ Machine Learning with PyTorch and Scikit-Learn Develop machine learning and deep learning models with Python {epub download}**Download Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python Full Edition,Full Version,Full Book ** by Sebastian Raschka Reading Now at : https://happyreadingebook.club/?book=1801819319 OR DOWNLOAD EBOOK NOW! [PDF] Download READ/DOWNLOAD=^ Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python {epub download} Ebook | READ ONLINE Download READ/DOWNLOAD=^ Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python {epub download} read ebook online...
2023-08-1300 minSoul Searching
Soul Searching#197 Sebastian Raschka | Transformers - Deep learning Research - Open Sourcefeedback @ ryan@soulsearching.in EPISODE LINKS: Website : https://sebastianraschka.com/ Linkedin : https://www.linkedin.com/in/sebastianraschkaTwitter : https://twitter.com/rasbtGitHub : https://github.com/rasbtYouTube : https://www.youtube.com/c/sebastianraschka PODCAST INFO: Podcast website: https://anchor.fm/ryandsouza Apple Podcasts: https://apple.co/3NQhg6S Spotify: https://spoti.fi/3qJ3tWJ Amazon Music: https://amzn.to/3P66j2B Google Podcasts: https://bit.ly/3am7rQc Gaana: https://bit.ly/3ANS4v1 RSS: https://anchor.fm/s/609210d4/podcast/rss
2023-04-131h 02Learning from Machine Learning
Learning from Machine LearningSebastian Raschka: Learning ML, Responsible AI, AGI | Learning from Machine Learning #4This episode we welcome Sebastian Raschka, Lead AI Educator at Lightning and author of Machine Learning with Pytorch and Scikit-Learn to discuss the best ways to learn machine learning, his open source work, how to use chatGPT, AGI, responsible AI and so much more. Sebastian is a fountain of knowledge and it was a pleasure to get his insights on this fast moving industry. Learning from Machine Learning, a podcast that explores more than just algorithms and data: Life lessons from the experts. Resources to learn more about Sebastian Raschka and his work:https://sebastianraschka.com/
2023-03-261h 07Education NewsCast
Education NewsCastENC235 – Wie das Arbeiten mit SAP Software durch Künstliche Intelligenz beeinflusst wird mit Johannes HoffartJohannes Hoffart ist CTO AI bei SAP und wir besprechen mit ihm, wo wir heute mit der Künstlichen Intelligenz (KI) stehen, insbesondere im SAP Ökosystem. Nach einem allgemeinen Blick auf den Stand der Anwendung und Forschung, sowie auf GenerativeAI inclusive ChatGPT schauen wir auf Business Use Cases. Danach stellt Johannes SAPs Ansatz des embedded AI vor und gibt Beispiele nach Geschäftsprozess wie Einkauf, Personalwirtschaft und allgemein über die SAP Business Technology Plattform. Wir besprechen auch Use Cases für Weiterbildung wie das schnelle Einarbeiten oder individuelle Lernen und natürlich auch die Grenzen und Herausforderungen bzgl. Bias und Et...
2023-02-2747 minInfinite Curiosity Pod with Prateek Joshi
Infinite Curiosity Pod with Prateek JoshiState of play in AI research | Sebastian Raschka, Bestselling AI Author and EducatorSebastian Raschka is one of the most well known AI authors in the world. He is an AI researcher with a strong passion for education. As Lead AI Educator at Lightning AI, he is making AI more accessible and teaching people how to utilize AI at scale. He's been an Assistant Professor of Statistics at the University of Wisconsin-Madison, focusing on deep learning research. You can learn more about him on his website. In this episode, we cover a range of topics including: - Framework for writing great books  - State o...
2023-01-3041 minJay Shah Podcast
Jay Shah PodcastMaking Machine Learning more accessible | Sebastian RaschkaSebastian Raschka​ is the lead AI educator at GridAI. He is the author of the book "Machine Learning with PyTorch and Scikit Learn" and also a few other books that cover the fundamentals of #machinelearning and #deeplearning techniques and implementing them with Python. He is also an Assistant Professor of Statistics at the University of Wisconsin-Madison and has been actively involved in making ML more accessible to beginners through his blogs, video tutorials, tweets and of course his books. He also holds a doctorate in Computational and Quantitative Biology from Michigan State University.Time Stamps of the Po...
2022-12-291h 22The Lindahl Letter
The Lindahl LetterWhy is diffusion so popular?Transformers were the thing. They were a big thing in the machine learning field. It was glorious. People talked about them a lot and papers were published. Oh so many papers were published. Now it feels like diffusion might be the thing. You will find that the thing of the moment in the field of machine learning shifts rapidly. I was looking at a GitHub repository based on, “high-Resolution Image Synthesis with Latent Diffusion Models,” and it has over 2,000 stars and has been forked 242 times [1]. I started reading this Tweet from Sebastian Raschka back on January 30, 2022 that asked the ques...
2022-07-3004 minThe Gradient: Perspectives on AI
The Gradient: Perspectives on AISebastian Raschka: AI Education and ResearchIn episode 36 of The Gradient Podcast, Daniel Bashir speaks to Sebastian Raschka.Sebastian is an Assistant Professor of Statistics at the University of Wisconsin-Madison and Lead AI Educator at Lightning AI. He has written two bestselling books: Python Machine Learning and Machine Learning with PyTorch and Scikit-Learn.Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterSections:(00:00) Intro(01:10) Sebastian’s intro to AI(05:15) Sebastian’s process for learning new things(12:15) Learning style varies with purpose(16:10) Ordinal Regression...
2022-07-291h 03The Data Exchange with Ben Lorica
The Data Exchange with Ben LoricaPractical Machine Learning and Deep learningSebastian Raschka is lead author of a new book from Packt entitled “Machine Learning with PyTorch and Scikit-Learn”.  He is also an Assistant Professor of Statistics at the University of Wisconsin (Madison), and serves as the Lead AI Educator at Grid.ai.  Download a FREE copy of our recent NLP Industry Survey Results:  https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
2022-05-1248 minThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Advancing Hands-On Machine Learning Education with Sebastian RaschkaToday we’re joined by Sebastian Raschka, an assistant professor at the University of Wisconsin-Madison and lead AI educator at Grid.ai. In our conversation with Sebastian, we explore his work around AI education, including the “hands-on” philosophy that he takes when building these courses, his recent book Machine Learning with PyTorch and Scikit-Learn, his advise to beginners in the field when they’re trying to choose tools and frameworks, and more. We also discuss his work on Pytorch Lightning, a platform that allows users to organize their code and integrate it into other technologies, before switching gears and...
2022-03-2840 minPython en español
Python en españolPython en español #29: Tertulia 2021-04-20Plataformas centralizadas, GIL, aprendizaje automático, Pydantic y Python 3.10, y hemos renunciado a llevar la cuenta de los gazapos que metemos en cada tertulia https://podcast.jcea.es/python/29 Participantes: Jesús Cea, email: jcea@jcea.es, twitter: @jcea, https://blog.jcea.es/, https://www.jcea.es/. Conectando desde Madrid. Víctor Ramírez, twitter: @virako, programador python y amante de vim, conectando desde Huelva. Felipem, conectando desde Cantabria. Juan José, Nekmo, https://nekmo.com/, https://github.com/Nekmo/. Madrileño conectando desde Málaga. Jesús, conectando desde Fe...
2021-07-122h 00Deep Tech Musings
Deep Tech MusingsE4. Drug Discovery using AI/ML - Dr. Sebastian RaschkaDr. Sebastian (@rasbt) is the Assistant Professor of Statistics at the University of Wisconsin-Madison. He is also a best selling author of the "Python Machine Learning" book and the creator of the popular "mlxtend" python library. On the show he talks about his latest research article highlighting how ML & AI approaches are being used for drug discovery, something quite prevalent in the COVID world today.  Article: https://www.sciencedirect.com/science/article/pii/S1046202319302762 Learn more about Sebastian's work here. https://sebastianraschka.com https://scholar.google.com/citations?user=X4RCC0IAAAAJ
2020-08-0739 minThe Python Podcast.__init__
The Python Podcast.__init__Teaching Python Machine LearningSummary Python has become a major player in the machine learning industry, with a variety of widely used frameworks. In addition to the technical resources that make it easy to build powerful models, there is also a sizable library of educational resources to help you get up to speed. Sebastian Raschka’s contribution of the Python Machine Learning book has come to be widely regarded as one of the best references for newcomers to the field. In this episode he shares his experiences as an author, his views on why Python is the right language for building ma...
2020-04-2849 minSoftware Developers Journey
Software Developers Journey#89 Hadelin de Ponteves is a data scientist and an entrepreneurHadelin first spoke about his entrepreneurship mindset. This was already in his mind early on, and never left him. We spoke about his interest for math, science and technology and how it drove him to one of the best French engineering schools. We talked about him discovering Data Science and how he changed his major at the very last minute. We then talked about his professional life. How he got to work at google, and why he didn't reconduct his contract and chose to create online courses instead. We spoke about his further business ventures, all the way to...
2020-02-2550 minChai Time Data Science
Chai Time Data ScienceInterview with Sebastian Raschka | Statistics, Open Source & ML Research | Python for ML BookVideo Version available here: https://youtu.be/beSLA-wO2T4Subscribe here to the newsletter: https://tinyletter.com/sanyambhutaniIn this episode, Sanyam Bhutani interviews Dr. Sebastian Raschka, currently an assistant professor of Statistics at University of Wisconsin, Madison and the Author of Python for machine learning book.Sebastian has a background in biology and holds a PhD in quantitative biology, biochemistry, and molecular biology.In this interview, they talk all about his journey into the intersection of biology, machine learning, statistics, open source, and machine learning research. Yes, these are all...
2020-02-231h 08Partially Derivative
Partially DerivativeModel Evaluation with Sebastian RaschkaHow to evaluate you models!
2017-01-0300 minData Science at Home
Data Science at HomeEpisode 7: 30 min with data scientist Sebastian RaschkaIn this show I interview Sebastian Raschka, data scientist and author of Python Machine Learning.In addition to the fun we had offline, there are great elements about machine learning, data science, current and future trends, to keep an ear on. Moreover, it is the conversation of two data scientists who contribute and operate in the field, on a daily basis.
2016-02-1534 minData Science at Home
Data Science at HomeEpisode 7: 30 min with data scientist Sebastian RaschkaIn this show I interview Sebastian Raschka, data scientist and author of Python Machine Learning.In addition to the fun we had offline, there are great elements about machine learning, data science, current and future trends, to keep an ear on. Moreover, it is the conversation of two data scientists who contribute and operate in the field, on a daily basis. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceathome.substack.com
2016-02-1534 min