Stanford CS25: Transformers United V6 I From Next-Token Prediction to Next-Generation Intelligence

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-... April 30, 2026 This seminar covers: • Recent progress in pretraining algorithm design for large language models (LLMs), emphasizing the role of data ordering, reasoning-centric data integration, and reinforcement-based objectives in shaping model capability. • The introduction of a two-phase pretraining framework that formalizes strategies for data selection, blending, and sequencing • A demonstration that front-loading reasoning-rich data during pretraining yields persistent gains in reasoning accuracy that post-training alone cannot reproduce Follow along with the seminar schedule. Visit: https://web.stanford.edu/class/cs25/ Guest Speaker: Shrimai Prabhumoye (Mistral AI, prev. NVIDIA) Instructors: • Steven Feng, Stanford Computer Science PhD student and NSERC PGS-D scholar • Karan P. Singh, Electrical Engineering PhD student and NSF Graduate Research Fellow in the Stanford Translational AI Lab • Michael C. Frank, Benjamin Scott Crocker Professor of Human Biology Director, Symbolic Systems Program • Christopher Manning, Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science, Co-Founder and Senior Fellow of the Stanford Institute for Human-Centered Artificial Intelligence (HAI)

Stanford CS153 Frontier Systems | Jensen Huang from NVIDIA on the Compute Behind Intelligence
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Stanford CS153 Frontier Systems | Jensen Huang from NVIDIA on the Compute Behind Intelligence

Stanford CS25: Transformers United V6 I Overview of Transformers
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Stanford CS25: Transformers United V6 I Overview of Transformers

Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
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Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026

FULL DISCUSSION: Google's Demis Hassabis, Anthropic's Dario Amodei Debate the World After AGI | AI1G
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FULL DISCUSSION: Google's Demis Hassabis, Anthropic's Dario Amodei Debate the World After AGI | AI1G

RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source
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RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, Coding AI
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Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, Coding AI

Yann LeCun: World Models: Enabling the next AI revolution
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Yann LeCun: World Models: Enabling the next AI revolution

Andrew Ng: Building Faster with AI
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Andrew Ng: Building Faster with AI

Stanford CS25: Transformers United V6 I From Language Models to Native Multimodal Intelligence
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Stanford CS25: Transformers United V6 I From Language Models to Native Multimodal Intelligence

Yann LeCun's $1B Bet Against LLMs [Part 1]
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Yann LeCun's $1B Bet Against LLMs [Part 1]

Introduction to Generative AI
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Introduction to Generative AI

Creator of C++: Bell Labs, Negative Overhead Abstraction, Mistakes | Bjarne Stroustrup
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Creator of C++: Bell Labs, Negative Overhead Abstraction, Mistakes | Bjarne Stroustrup

Stanford AI Club: Jeff Dean on Important AI Trends
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Stanford AI Club: Jeff Dean on Important AI Trends

Visualizing transformers and attention | Talk for TNG Big Tech Day '24
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Visualizing transformers and attention | Talk for TNG Big Tech Day '24

How Proctor’s texts in Karen Read lawsuit could free dangerous criminals
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How Proctor’s texts in Karen Read lawsuit could free dangerous criminals

1: Introduction to Neural Networks and Deep Learning; Training Deep NNs
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1: Introduction to Neural Networks and Deep Learning; Training Deep NNs

Class #3 | MS&E435: Economics of the AI Supercycle Stanford University Spring '26 Apoorv Agrawal
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Class #3 | MS&E435: Economics of the AI Supercycle Stanford University Spring '26 Apoorv Agrawal

Yi Ma - Pursuing the Nature of Intelligence
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Yi Ma - Pursuing the Nature of Intelligence

Anthropic Workshop: Build Agents That Run for Hours — Ash Prabaker & Andrew Wilson
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Anthropic Workshop: Build Agents That Run for Hours — Ash Prabaker & Andrew Wilson

Demis Hassabis: Agents, AGI & The Next Big Scientific Breakthrough
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Demis Hassabis: Agents, AGI & The Next Big Scientific Breakthrough