Machine learning

MLT | Week-2 | Session-2

MLT | Week-2 | Session-2

Physics-Constrained Agentic Training of Entropy-Stable PINNs || June 26, 2026

Las leyes de escala de Amodei

Amodei’s Scaling Laws

Voice Cloning: LoRA Fine-Tuning for Custom TTS

MLT | Week-2 | Session-1

MLT | Week-2 | Session-1

AI Engineering -- Kickoff Session

Machines, Learning, and Machine Learning - Dylan Beattie - NDC Copenhagen 2026

He won a Nobel here for AlphaFold. Then he left. - John Jumper

MLT | Week-1 | Session-2

MLT | Week-1 | Session-2

Thibaut Germain: Geometric Dictionary Learning of Dynamical Systems with Optimal Transport

MLT | Week-1 | Summary Session

MLT | Week-1 | Summary Session

Every Level of a Claude Second Brain Explained

Claude Code dans le terminal : ce que tout le monde rate

Claude Code in the Terminal: What Everyone Is Missing

The Future of Document Parsing

Systems A/B/M : Lessons on Autonomous Learning from Cognitive Science

Student/Postdoc lightning talks

[ИАД, 2026] Предзащита магистерских работ

[IAD, 2026] Pre-defense of master's theses

World Modeling: Evaluation and State Computation

Surface Data vs. Deep Data

From "Umwelt" to "World" models

Edward Lockhart - Why AI Needs Formal Mathematics

Daniel Barzilai - Some Very Old and Very New Problems in Learning Theory

Bogdan Georgiev - Agents and ML Algorithms in Mathematics

BEYOND CLASSICAL AI Quantum Machine Learning for Anomaly Detection Across Industries

AI is solving science's biggest problems — but has no idea why it's right | with Claire Malone

Tolga Birdal: Generalization at the Edge of Stability

I Made Opus 4.8 and Fable 5 Build the Same App (RAW RESULTS)

Bridging the gap between Minds & Machines

Talk by Alison Gopnik (UC Berkeley)

[Machine Learning in Urdu/Hindi] 001- Introduction to Machine Learning -W1L2-HQ

[Machine Learning in Urdu/Hindi] 001- Introduction to Machine Learning -W1L2-HQ

Agentic AI: L4 Part 2, Adjusting model parameters

Agentic AI: L4 Part 2, Adjusting model parameters

Noam Razin - What Makes a Good Proxy Reward Function for Language Model Post-Training? (Eng)

China Just Built A Two Brain AI Robot: One Body, Two Minds

Más emergencia por escala, Training de transformers por difusión, Los datos no se agotan

More emergency by scale, Training of transformers by diffusion, Data does not run out

Self-Evolving Hermes Agents: Enterprise AI That Gets Better With Use | Nemotron Labs

Small Language Model Alignment - Finetune SLMs to ALWAYS pick the best answer (Unsloth DPO)

Talk by Pranjal Awasthi (Google)

Multi-objective Learning: An Algorithmic Toolbox for Optimal Predictions Anytime Anywhere!

Efficient Algorithms for Reliable Machine Learning

Computational Thinking on Learning Models