Decoding OpenAIs Advanced Reasoning Models: A Gentle Introduction to How They Work 0 like February 27, 2025Share this postLast Updated on February 27, 2025 by Editorial TeamAuthor(s): Saleh Alkhalifa Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium.In todays fast-paced digital landscape, businesses and developers alike are constantly trying to stay ahead of the curve by seeking smarter solutions for complex challenges. This last month, the most popular topics of conversation at work and in online forums have revolved around the latest reasoning models. In particular, OpenAIs reasoning models, o1 and o3, gained considerable traction as they are designed to think before they answer, and have changed the way we think and approach problem solving, coding, and even scientific research within the Language Model domain.Reasoning models are the latest generation of Large Language Models, which incorporate unique internal processes through Chain of Thought reasoning before delivering a final response to a given query. Unlike traditional models that generate a response from a given input, these models break down a prompt into multiple steps and internally generate a detailed sequence of reasoning tokens. This approach allows them to tackle multi-step planning and complex logic more effectively, making them ideal for tasks such as complex problem solving, coding and debugging, and scientific research which often involves multiple steps and trains of thought.Complex Problem Solving: Break down a challenge Read the full blog for free on Medium.Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming asponsor. Published via Towards AITowards AI - Medium Share this post