Machine learning

Claude Fable 5.1 is savage

Strange Geometric Shapes Found Inside AIs — Tom McGrath

Lec 34: Learning Rate Scaling & Training Dynamics

ANN & LEARNING | DATA ANALYTICS | LECTURE 02 BY MR. MUKULIT GOEL | AKGEC

Efficient Deep Learning for Brain Tumor Segmentation

Dhruv Rohatgi: Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier

Ep. 234: How HubSpot Is Reimagining the Entire Customer Journey With AI Agents

The mathematics of AI uncertainty

My PhD Oral Defense Presentation: From Numerical Simulators to Neural Emulators and Back

Redefining Roles For Edge And Cloud AI

Lec 23: Auto - Regressive Generative Models

ICM 2026 Panel - AI for Mathematics

MLT | Week-10 | Live Session

Lec 32: Scaling, Horovod, and Picking the Right Tool

Lec 31: NCCL, All-reduce, and Multi-node

78. Sonnet 5, Meta Cloud y la guerra de infraestructura

78. Sonnet 5, Meta Cloud and the infrastructure war

On Policy Distillation - How the big AI labs actually train their LLMs

Charla “Minería en Quimio-informática: Cómo extraer compuestos valiosos de bases de datos”

Talk: "Chemoinformatics Mining: How to Extract Valuable Compounds from Databases"

Dr. Boumediene Hamzi | When Compressibility Replaces Smoothness: Bridging Machine Learning, Dynam...

La Chine dévoile Superman, son robot IA aux pouvoirs surhumains : une vraie révolution ?

China unveils Superman, its AI robot with superhuman powers: a real revolution?

Code a Reinforcement Learning Library in C from Scratch (Full Course)

A Week of Grok Bot Lessons in 10 Mins

I trained a Reasoning Language Model with RL on an unverifiable task

MLT | Week-7 & 8 | Revision Session

China Finally Beats MYTHOS 5 With New GLM 5.3 (Plus Anthropic's New Model 2)

Lec 28: Efficient LLM fine-tuning using peft and LoRA

Lec 27: Transfer learning for large models

Dr. Gareth Conduit | Unveil the unseen: uncover hidden information in concrete with machine learning

Why Great Models Fail: Lessons From 9 Years of Deploying ML Models - Megan Robertson

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 19: Model-Based RL

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 18: RL Policy Optimization

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 17: RL Value-Based Methods

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 16: Fundamentals of RL

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 15: Imitation Learning

Prof. John Harlim | Learning solution operator of dynamical systems with diffusion maps kernel ri...

Prof. Gitta Kutyniok | Beyond Scaling: Optimization and Learning for Sustainable AI

Andrew Lee: Decomposing Query-Key Feature Interactions Using Contrastive Covariances (2026-05-13)

Fine-Tuning LLMs for Real-World Tool Calling: Lessons from tau2-bench

Expanding the Capabilities of Tabular Foundation Models

Enhancing Training Data Pipelines with Lance and the Multimodal Lakehouse