· ai
Why AI safety should be enforced structurally, not trained in
Most current AI safety work assumes an unsafe system and tries to train better behavior into it. - We add more data. - We add more constraints. - We add more fi...
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- · ai
LLM Year in Review
19 Dec, 2025 !unnamedhttps://bear-images.sfo2.cdn.digitaloceanspaces.com/karpathy/unnamed.webp 2025 has been a strong and eventful year of progress in LLMs. The...
- · ai
OpenAI Gym
Overview OpenAI Gym is a simple playground for teaching computers through trial and error. You drop a task in, the program tries actions, learns from mistakes,...
- · ai
AI agents fail 63% of the time on complex tasks. Patronus AI says its new 'living' training worlds can fix that.
Patronus AI, the artificial intelligence evaluation startup backed by $20 million from investors including Lightspeed Venture Partners and Datadog, unveiled a n...
- · software
Evolutionary Algorithms, Rendered Live in Node.js
Reinforcement Learning, Evolutionary Algorithms, and Visual Computing Reinforcement learning, evolutionary algorithms, and anything that lets computers see are...
- · ai
**Temporal Contextual Attention in Hierarchical Multi-Agent
Temporal Contextual Attention in Hierarchical Multi-Agent Systems with Non-Stationary Reward Functions Challenge Overview Consider a scenario with N hierarchic...
- · ai
Reinforcement Learning Environments: How AI Agents Learn Through Experience
Artificial intelligence agents improve through interaction and feedback, a process known as reinforcement learning RL. In this learning paradigm, an agent opera...
- · ai
Ai2's new Olmo 3.1 extends reinforcement learning training for stronger reasoning benchmarks
The Allen Institute for AI Ai2 recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, exp...
- · ai
**The Tactical Tango: An In-Depth Comparison of Reinforcemen
Reinforcement Learning: The Pragmatic Pioneer Reinforcement Learning RL has achieved success in game playing, robotics, and sports. The core idea is to give an...
- · ai
[Paper] Escaping the Verifier: Learning to Reason via Demonstrations
Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-world reasoning-int...
- · ai
[Paper] Aligning LLMs Toward Multi-Turn Conversational Outcomes Using Iterative PPO
Optimizing large language models (LLMs) for multi-turn conversational outcomes remains a significant challenge, especially in goal-oriented settings like AI mar...
- · ai
[Paper] BAMAS: Structuring Budget-Aware Multi-Agent Systems
Large language model (LLM)-based multi-agent systems have emerged as a powerful paradigm for enabling autonomous agents to solve complex tasks. As these systems...