Geeky Gadgets

Reinforcement Learning for LLMs in 2025

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.
NextBigFuture

Reinforcement Learning Does NOT Fundamentally Improve AI Models

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...
VentureBeat

DeepSeek-R1’s bold bet on reinforcement learning: How it outpaced OpenAI at 3% of the cost

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...
i-SCOOP

Experiential Reinforcement Learning

Discover Experiential Reinforcement Learning (ERL), a revolutionary AI training paradigm that allows language models to learn from their own reflections, turning failure into structured wisdom without ...

Leadership Amid Uncertainty: CEOs Can Learn Effective Decision Making From Reinforcement Learning

Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...
Devdiscourse

Adaptive AI system enhances zero-day attack resilience in blockchain networks

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.
SiliconANGLE

AWS simplifies AI agent customization with automated reinforcement learning

Amazon Web Services Inc. wants to solve the efficiency challenges of artificial intelligence agents and reduce their overall inference demands, and it’s tackling the problem with more advanced model ...
AZoLifeSciences on MSN

How the Brain Uses Reinforcement Learning Beyond Just Mean Rewards

What if our brains learned from rewards not just by averaging them but by considering their full range of possibilities? A ...
EurekAlert!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
EurekAlert!

Offline model-based reinforcement learning with causal structured world models

The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...