Embeddings, Transformers, RLHF: Three key ideas to understand ChatGPT - Luca Baggi

Tricking Neural Networks : Explore Adversarial Attacks - Bernice Waweru

🧼 From GPU-poor to data-rich: data quality practices for LLM fine-tuning - David Berenstein

Transformers (how LLMs work) explained visually | DL5

Zero waste: trucchi per riciclare (la memoria) meglio - Francesco Panico, Carlo Bertini

Kacper Łodzikowski: Challenges of implicit bias in AI: Towards awareness and mitigation

Lightning Talks - PyCon Italia 2024

AI, SQL, and GraphQL Walk into a Fertility Clinic… LLM-based Medical feature development

PEP 683: Immortal Objects - A new approach for memory managing - Vinícius Gubiani Ferreira

Attention in transformers, visually explained | DL6

The European AI Act: a data scientist’s perspective - Luca Gilli

Designing a Human-Friendly CLI for API-Driven Infrastructure - Oliver Rew

State of GPT | BRK216HFS

Nico Verwer and Pieter Lamers - Syntax highlighting for code blocks using ixml

PyCon PT 24 | Esmerald and Lilya - How to speed up the development process

11. Introduction to Machine Learning

Stay Close to the Metal - Vicki Boykis

Code More, Draw Less, and Debug Just a Little! - Yash Saboo

SAS 2024 talk: "Fixing Latent Unsound Abstract Operators in the eBPF Verifier of the Linux Kernel

Reinforcement Learning from Human Feedback: From Zero to chatGPT

Think Fast, Talk Smart: Communication Techniques