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 ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...
Recently, model-based reinforcement learning has been considered a crucial approach to applying reinforcement learning in the physical world, primarily due to its efficient utilization of samples.
“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...
Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of acquiring new skills or adjusting behaviors in response to positive outcomes ...
Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...
Manulife announced today that it has chosen Adaptive ML to provide model fine-tuning technology as part of its enterprise AI platform.
This agreement is expected to support Manulife in automating underwriting quotes, handling complex processes, and providing guidance to sales professionals.
No matter how much data they learn, why do artificial intelligence (AI) models often miss the mark on human intent?
Meta’s most popular LLM series is Llama. Llama stands for Large Language Model Meta AI. They are open-source models. Llama 3 was trained with fifteen trillion tokens. It has a context window size of ...