Bon courage à tous ceux qui ont des enfants pour la rentrée demain ! Un conseil : servez-vous de l’IA pour les accompagner dans leurs apprentissages. Cette année, s’ils ont des questions auxquelles vous n’avez pas la réponse, utilisez ChatGPT. Essayez aussi la fonction tutorat
LLMS
-
LLM Tools Impact on Worker Skills and Hiring Decisions
By
–
This is terrific. The story that AI complements certain skills and workers squares nicely with the facts we uncover. That said, it may be more complicated: I've spoken to many people involved in hiring, and they say that, at least in part, they also view LLM-based tools as
-
LangGraph Autonomous News Agent with Human Feedback Integration
By
–
Autonomous News Agent A LangGraph-powered AI agent that autonomously curates news briefings, extracts facts, and summarizes content with integrated human feedback and dynamic tool selection. Check out the implementation details https://
spin.atomicobject.com/build-ai-agent
-langgraph/
… -
The Unsolved Mystery of How LLMs Simulate Human Thought
By
–
Nous n’avons en réalité pas beaucoup progressé dans l’explication du grand mystère des LLM : Comment un modèle qui utilise simplement des multiplications de matrices pour prédire le mot suivant parvient-il à simuler la pensée humaine au point de reproduire autant de
-
AI Rails App Builder: Natural Language-Powered Real-Time Development
By
–
AI Rails App Builder A natural language-powered system that builds and modifies Rails applications in real-time. Using LangGraph, it handles file operations and Rails commands through an intelligent agent with live previews. Check it out https://
kodykendall.com/a-chatbot-that
-builds-rails-apps/
… -
LLM Reward Hacking Generalizes to Dangerous Misaligned Behaviors
By
–
9. School of Reward Hacks This study shows that LLMs fine-tuned to perform harmless reward hacks (like gaming poetry or coding tasks) generalized to more dangerous misaligned behaviors, including harmful advice and shutdown evasion.
-
Evaluating Language Models on Real Unsolved Questions
By
–
7. Assessing Language Models on Unsolved Questions The paper introduces a new evaluation paradigm that tests models on real unsolved questions from the wild, rather than on fixed-answer exams.
-
Memory-R1: Framework Teaching LLM Agents Memory Management
By
–
6. Memory-R1 A framework that teaches LLM agents to decide what to remember and how to use it.
-
Memory-based LLM Agent Fine-tuning Without Weight Updates
By
–
3. Fine-tuning LLM Agents without Fine-tuning LLMs A memory‑based learning framework that lets deep‑research agents adapt online without updating model weights.
-
Jet-Nemotron: Hybrid LLM Architecture with Optimized Attention
By
–
4. Jet-Nemotron A hybrid-architecture LM family: starting from a frozen full-attention model, the authors search for where to keep full attention, which linear-attention block to use, and which hyperparameters match hardware limits.