Emerging reasoning with reinforcement learning | Hacker News
news.ycombinator.com
Emerging reasoning with reinforcement learning | Hacker News
A key advantage of these RL advancements is their universal applicability across any open-source model. This flexibility allows organizations to future-proof their AI investments by using the best current models, and reusing the data and workflow to retrain when a better model comes up. For instance, a customer support AI could adopt newer foundati
... See moreEvan Armstrong • What Actually Matters (And What Doesn’t) for DeepSeek
This leap from pre-trained instinctual responses (”System 1”) to deeper, deliberate reasoning (“System 2”) is the next frontier for AI. It’s not enough for models to simply know things—they need to pause, evaluate and reason through decisions in real time.
Sonya Huang • Generative AI’s Act O1
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
arxiv.org
LeCun points to four essential characteristics of human intelligence that current AI systems, including LLMs, can’t replicate: reasoning, planning, persistent memory, and understanding the physical world. He stresses that LLMs’ reliance on textual data severely limits their understanding of reality: “We’re easily fooled into thinking they are intel... See more
Azeem Azhar • 🧠 AI’s $100bn question: The scaling ceiling
Over the past 2 and half years we’ve seen the rise of the LLM’s but one of the great contributers to LLM’s Yann LeCun believes that LLM’s are actually old news and that we’re now just making them marginally better and he’s much more focused on other things.
Firstly he thinks these models need to understand the physical world. Right now, LLMs are gr
A rough analogy to the current LLM process is that making a new model is like baking a cake. You figure out your data and algorithms—like mixing the batter—and then you pretrain the model, that is, run it on a large number of computers for several months—like putting it in the oven—and then at the end you do some “post training”—like frosting and d... See more