# \#stanford-online **URL:** https://www.artofsm.art/tag/stanford-online/331.md [Latest](https://www.artofsm.art/latest.md) · [Categories](https://www.artofsm.art/categories.md) · [Tags](https://www.artofsm.art/tags.md) --- ## [RAG Explained: From BM25 to Agentic RAG | Stanford CS329Z Lecture 3 with Diyi Yang](https://www.artofsm.art/t/rag-explained-from-bm25-to-agentic-rag-stanford-cs329z-lecture-3-with-diyi-yang/28193)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [11 November 2026 21:25 UTC](https://www.artofsm.art/t/rag-explained-from-bm25-to-agentic-rag-stanford-cs329z-lecture-3-with-diyi-yang/28193 "2026-11-11T21:25:06Z")
The lecture provides a comprehensive overview of Retrieval-Augmented Generation (RAG), detailing its integration of retrieval and generation models to enhance open-domain question answering with up-to-date,… --- ## [Stanford CS193T Thinking with AI | Autumn 2026 | Managing Sources](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-managing-sources/28175)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [11 November 2026 18:21 UTC](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-managing-sources/28175 "2026-11-11T18:21:48Z")
The lecture explores managing sources within AI context windows, highlighting personalization, memory transfer, Retrieval Augmented Generation (RAG), and the use of reusable “skills” or “gems” to enhance AI… --- ## [LLMs for Agent Builders: Context Engineering | Stanford CS329Z Lecture 2 with Michael Ryan](https://www.artofsm.art/t/llms-for-agent-builders-context-engineering-stanford-cs329z-lecture-2-with-michael-ryan/28099)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [10 November 2026 21:24 UTC](https://www.artofsm.art/t/llms-for-agent-builders-context-engineering-stanford-cs329z-lecture-2-with-michael-ryan/28099 "2026-11-10T21:24:28Z")
In this lecture, Michael Ryan explores the foundational concepts of large language models (LLMs), focusing on their architecture, training processes, and inference techniques, with an emphasis on applying p… --- ## [Stanford CS193T Thinking with AI | Autumn 2026 | Core Prompting](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-core-prompting/28081)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [10 November 2026 18:24 UTC](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-core-prompting/28081 "2026-11-10T18:24:13Z")
The Stanford CS193T lecture on core prompting emphasizes starting with clear goals, using detailed and natural prompts, and employing managerial techniques like clear delegation and iterative clarification … --- ## [What Are AI Agents? Agentic Systems Explained | Stanford CS329Z Lecture 1 with Diyi Yang](https://www.artofsm.art/t/what-are-ai-agents-agentic-systems-explained-stanford-cs329z-lecture-1-with-diyi-yang/28020)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [9 November 2026 21:24 UTC](https://www.artofsm.art/t/what-are-ai-agents-agentic-systems-explained-stanford-cs329z-lecture-1-with-diyi-yang/28020 "2026-11-09T21:24:37Z")
The lecture introduces the CS 329Z course on engineering AI agents, covering the history, architecture, and key components of agentic systems, including large language models, planning, memory, tool use, an… --- ## [Stanford CS193T Thinking with AI | Autumn 2026 | Introduction to AI](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-introduction-to-ai/27984)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [9 November 2026 18:24 UTC](https://www.artofsm.art/t/stanford-cs193t-thinking-with-ai-autumn-2026-introduction-to-ai/27984 "2026-11-09T18:24:30Z")
The lecture introduces the Stanford CS193T course on AI, focusing on the critical role of context in AI systems, the evolution and functioning of large language models and neural networks, and the importanc… --- ## [Stanford CME295 Transformers & LLMs | Autumn 2026 | Lecture 5 - LLM Systems](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-5-llm-systems/27537)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [5 November 2026 17:24 UTC](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-5-llm-systems/27537 "2026-11-05T17:24:43Z")
The lecture covers system-level challenges and optimizations for training and serving large language models, including memory-efficient algorithms like FlashAttention, various parallelism strategies to hand… --- ## [Stanford EE292R AI and Data for Science | Autumn 2026 | Multimodal Modeling for Precision Medicine](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-multimodal-modeling-for-precision-medicine/27410)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 November 2026 21:24 UTC](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-multimodal-modeling-for-precision-medicine/27410 "2026-11-03T21:24:31Z")
The presentation highlights advanced multimodal modeling techniques in precision medicine, integrating diverse data types like multi-omics, histopathology, radiology, and clinical data using neural networks… --- ## [Stanford Robotics Seminar ENGR319 | Autumn 2026 | Bridging Rigorous Methods with Machine Learning](https://www.artofsm.art/t/stanford-robotics-seminar-engr319-autumn-2026-bridging-rigorous-methods-with-machine-learning/27137)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [29 October 2026 23:27 UTC](https://www.artofsm.art/t/stanford-robotics-seminar-engr319-autumn-2026-bridging-rigorous-methods-with-machine-learning/27137 "2026-10-29T23:27:26Z")
The speaker presents research on integrating rigorous classical engineering methods with modern machine learning to develop scalable, safe autonomous systems that strictly enforce safety through techniques … --- ## [Stanford CS547 HCI Seminar | Autumn 2026 | Designing AI for Societal Good](https://www.artofsm.art/t/stanford-cs547-hci-seminar-autumn-2026-designing-ai-for-societal-good/26729)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [23 October 2026 16:24 UTC](https://www.artofsm.art/t/stanford-cs547-hci-seminar-autumn-2026-designing-ai-for-societal-good/26729 "2026-10-23T16:24:42Z")
Chen from Stanford discusses the challenges of designing AI for societal good, emphasizing the importance of measuring and raising awareness of generative AI’s harms to influence public opinion, policy, and… --- ## [Stanford EE292R AI and Data for Science | Autumn 2026 | From World Models to World Agents](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-from-world-models-to-world-agents/26664)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [22 October 2026 22:24 UTC](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-from-world-models-to-world-agents/26664 "2026-10-22T22:24:53Z")
The lecture explores the advancement of physical AI through world models—generative systems that create realistic video environments by learning from data rather than relying on traditional simulators—and d… --- ## [Webinar: Regulating at the Speed of AI with Francis Fukuyama and Nate Persily](https://www.artofsm.art/t/webinar-regulating-at-the-speed-of-ai-with-francis-fukuyama-and-nate-persily/26516)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [20 October 2026 19:48 UTC](https://www.artofsm.art/t/webinar-regulating-at-the-speed-of-ai-with-francis-fukuyama-and-nate-persily/26516 "2026-10-20T19:48:02Z")
In the webinar “Regulating at the Speed of AI,” Francis Fukuyama and Nate Persily discussed the inevitability and complexity of AI regulation, emphasizing the need for specialized regulatory bodies, interna… --- ## [Stanford CME295 Transformers & LLMs | Autumn 2026 | Lecture 4 - Reinforcement Learning with LLMs](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-4-reinforcement-learning-with-llms/26419)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [19 October 2026 23:35 UTC](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-4-reinforcement-learning-with-llms/26419 "2026-10-19T23:35:17Z")
Lecture 4 of Stanford’s CM295 course covers reinforcement learning techniques for fine-tuning large language models, focusing on aligning models with human preferences and verifiable rewards through methods… --- ## [Stanford EE292R AI and Data for Science | Autumn 2026 | Models of Computation in the Retina](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-models-of-computation-in-the-retina/26099)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 0\ **Last updated:** [17 October 2026 00:01 UTC](https://www.artofsm.art/t/stanford-ee292r-ai-and-data-for-science-autumn-2026-models-of-computation-in-the-retina/26099 "2026-10-17T00:01:31Z")
--- ## [Stanford CME 295 Transformers & LLMs | Fall 2026 | Lecture 3 - LLM training](https://www.artofsm.art/t/stanford-cme-295-transformers-llms-fall-2026-lecture-3-llm-training/26020)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [15 October 2026 23:27 UTC](https://www.artofsm.art/t/stanford-cme-295-transformers-llms-fall-2026-lecture-3-llm-training/26020 "2026-10-15T23:27:27Z")
Lecture 3 of Stanford’s CME 295 course comprehensively covers the training pipeline of large language models, from foundational pre-training on diverse datasets to supervised fine-tuning and advanced alignm… --- ## [Stanford CME295 Transformers & LLMs | Autumn 2026 | Lecture 2 - Large Language Models](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-2-large-language-models/25396)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [9 October 2026 21:56 UTC](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-2-large-language-models/25396 "2026-10-09T21:56:13Z")
The lecture reviews transformer architectures and large language models, covering encoder-only models like BERT, decoder-only models like GPT, scaling laws, and efficient techniques such as mixture of exper… --- ## [Webinar: What AI Can and Cannot Do: Intelligence Augmentation in Practice with Michael Bernstein](https://www.artofsm.art/t/webinar-what-ai-can-and-cannot-do-intelligence-augmentation-in-practice-with-michael-bernstein/24668)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [30 September 2026 15:21 UTC](https://www.artofsm.art/t/webinar-what-ai-can-and-cannot-do-intelligence-augmentation-in-practice-with-michael-bernstein/24668 "2026-09-30T15:21:45Z")
In the webinar, Professor Michael Bernstein highlighted the distinction between sharp-edged problems requiring high accuracy and blunt-edged problems allowing approximate solutions, explaining that AI is mo… --- ## [Stanford CS153 Frontier Systems | Teaching AI to Touch Atoms](https://www.artofsm.art/t/stanford-cs153-frontier-systems-teaching-ai-to-touch-atoms/24619)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [29 September 2026 23:26 UTC](https://www.artofsm.art/t/stanford-cs153-frontier-systems-teaching-ai-to-touch-atoms/24619 "2026-09-29T23:26:48Z")
Liam Ferriss and Dorje Chubak of Periodic Labs discuss their development of AI-driven semi-autonomous labs that accelerate materials science discovery, particularly in superconductors and semiconductors, by… --- ## [Webinar: AI Agent Simulation of Human Behavior with Michael Bernstein](https://www.artofsm.art/t/webinar-ai-agent-simulation-of-human-behavior-with-michael-bernstein/24615)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [29 September 2026 22:31 UTC](https://www.artofsm.art/t/webinar-ai-agent-simulation-of-human-behavior-with-michael-bernstein/24615 "2026-09-29T22:31:33Z")
Professor Michael Bernstein presented how AI-driven generative agents, powered by large language models, can simulate realistic human behaviors and social interactions to improve organizational decision-mak… --- ## [Stanford CME295 Transformers & LLMs | Autumn 2026 | Lecture 1 - Transformers](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-1-transformers/24529)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [28 September 2026 20:28 UTC](https://www.artofsm.art/t/stanford-cme295-transformers-llms-autumn-2026-lecture-1-transformers/24529 "2026-09-28T20:28:02Z")
The lecture introduces the Stanford CME295 course on Transformers and Large Language Models, covering foundational concepts such as tokenization, embeddings, and the transformer architecture with self-atten… --- ## [AI in Healthcare Series: Have We Already Bent the Healthcare Cost Curve?](https://www.artofsm.art/t/ai-in-healthcare-series-have-we-already-bent-the-healthcare-cost-curve/24293)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [25 September 2026 17:28 UTC](https://www.artofsm.art/t/ai-in-healthcare-series-have-we-already-bent-the-healthcare-cost-curve/24293 "2026-09-25T17:28:21Z")
The Stanford Healthcare AI podcast features a discussion on how autonomous AI is poised to transform healthcare by democratizing medical expertise, potentially disrupting traditional institutions and reduci… --- ## [Agentic AI Program Overview](https://www.artofsm.art/t/agentic-ai-program-overview/23507)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [2 September 2026 22:26 UTC](https://www.artofsm.art/t/agentic-ai-program-overview/23507 "2026-09-02T22:26:49Z")
The video introduces agentic AI systems—autonomous, self-improving models capable of taking actions and learning from feedback—that are poised to revolutionize knowledge work across various fields. It outli… --- ## [AI in Healthcare Series: When AI Stops Being a Project](https://www.artofsm.art/t/ai-in-healthcare-series-when-ai-stops-being-a-project/24294)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [29 August 2026 17:27 UTC](https://www.artofsm.art/t/ai-in-healthcare-series-when-ai-stops-being-a-project/24294 "2026-08-29T17:27:39Z")
The Stanford Healthcare AI podcast features Sandeep Dadlani discussing the transition of AI in healthcare from isolated projects to integral business operations, emphasizing the need for reimagined workflow… --- ## [OpenJarvis: Personal AI, on Personal Devices](https://www.artofsm.art/t/openjarvis-personal-ai-on-personal-devices/22859)
**Author:** [@merefield](https://www.artofsm.art/u/merefield)\ **Replies:** 1\ **Last updated:** [18 August 2026 15:46 UTC](https://www.artofsm.art/t/openjarvis-personal-ai-on-personal-devices/22859 "2026-08-18T15:46:37Z")
Open Jarvis is an open-source framework developed by Stanford PhD students that enables personal AI to run entirely on local devices, addressing privacy, cost, and connectivity issues associated with cloud-… --- ## [Stanford CS329A Self-Improving AI Agents | Part 4 | Learning from Feedback with Tools/Code](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-4-learning-from-feedback-with-tools-code/22059)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-4-learning-from-feedback-with-tools-code/22059 "2026-08-03T16:10:59Z")
The lecture explores how large language models can enhance their capabilities beyond text generation by interacting with real-world tools, code, and APIs to learn from feedback and improve over time. It bui… --- ## [Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-1-course-overview/22058)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-1-course-overview/22058 "2026-08-03T16:10:58Z")
The Stanford CS329A course provides an in-depth overview of the evolution, training, and capabilities of large language models, emphasizing techniques like reinforcement learning from human feedback and inf… --- ## [Stanford CS329A Self-Improving AI Agents | Part 7 | Self-Improvement and Deep Research Agents](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-7-self-improvement-and-deep-research-agents/22066)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-7-self-improvement-and-deep-research-agents/22066 "2026-08-03T16:10:56Z")
The lecture explores advancements in AI problem-solving through improved search and sampling techniques, highlighting systems like AlphaCode and Search-o1 that enhance code generation and deep research capa… --- ## [Stanford CS329A Self-Improving AI Agents | Part 5 | Planning and Multi-Step Reasoning](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-5-planning-and-multi-step-reasoning/22054)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-5-planning-and-multi-step-reasoning/22054 "2026-08-03T16:10:54Z")
The lecture reviews three recent papers—LATs, SPRINT, and SWiRL—that advance multi-step reasoning and planning in AI agents by integrating techniques like tree search, parallel execution, and reinforcement … --- ## [Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-6-train-time-scaling-scaling-rl/22057)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-6-train-time-scaling-scaling-rl/22057 "2026-08-03T16:10:53Z")
The lecture explored train time scaling and reinforcement learning techniques from three key papers—STaR, DeepSeekMath, and DAPO—that enhance AI agents’ mathematical reasoning by iteratively fine-tuning mod… --- ## [Stanford CS329A Self-Improving AI Agents | Part 3 | Robust Verification](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-3-robust-verification/22055)
**Author:** [@artesia](https://www.artofsm.art/u/artesia)\ **Replies:** 1\ **Last updated:** [3 August 2026 16:10 UTC](https://www.artofsm.art/t/stanford-cs329a-self-improving-ai-agents-part-3-robust-verification/22055 "2026-08-03T16:10:50Z")
The lecture reviews advancements in verification techniques for self-improving AI agents solving complex reasoning tasks, highlighting the progression from single verifier models trained on human-labeled da… [Next page](https://www.artofsm.art/tag/stanford-online/331.md?match_all_tags=true&page=1&tags%5B%5D=stanford-online)