The Landscape of Reinforcement Learning

This chapter explores the nuances of reinforcement learning, comparing it to other learning paradigms and discussing its foundational principles like delayed rewards. It also critiques the current hype around reinforcement learning in AI, addressing the challenges it faces and the need for diverse research approaches to avoid stagnation.

Transcript

chevron_right

Play full episode

chevron_right

Transcript

Episode notes

This episode is sponsored by Indeed.

Stop struggling to get your job post seen on other job sites. Indeed's Sponsored Jobs help you stand out and hire fast. With Sponsored Jobs your post jumps to the top of the page for your relevant candidates, so you can reach the people you want faster.

Get a $75 Sponsored Job Credit to boost your job’s visibility! Claim your offer now: https://www.indeed.com/EYEONAI

In this episode, renowned AI researcher Pedro Domingos, author of The Master Algorithm, takes us deep into the world of Connectionism—the AI tribe behind neural networks and the deep learning revolution.

From the birth of neural networks in the 1940s to the explosive rise of transformers and ChatGPT, Pedro unpacks the history, breakthroughs, and limitations of connectionist AI. Along the way, he explores how supervised learning continues to quietly power today’s most impressive AI systems—and why reinforcement learning and unsupervised learning are still lagging behind.

We also dive into:

The tribal war between Connectionists and Symbolists
The surprising origins of Backpropagation
How transformers redefined machine translation
Why GANs and generative models exploded (and then faded)
The myth of modern reinforcement learning (DeepSeek, RLHF, etc.)
The danger of AI research narrowing too soon around one dominant approach

Whether you're an AI enthusiast, a machine learning practitioner, or just curious about where intelligence is headed, this episode offers a rare deep dive into the ideological foundations of AI—and what’s coming next.

Don’t forget to subscribe for more episodes on AI, data, and the future of tech.

Stay Updated:

Craig Smith on X:https://x.com/craigss

Eye on A.I. on X: https://x.com/EyeOn_AI

(00:00) What Are Generative Models?

(03:02) AI Progress and the Local Optimum Trap

(06:30) The Five Tribes of AI and Why They Matter

(09:07) The Rise of Connectionism

(11:14) Rosenblatt’s Perceptron and the First AI Hype Cycle

(13:35) Backpropagation: The Algorithm That Changed Everything

(19:39) How Backpropagation Actually Works

(21:22) AlexNet and the Deep Learning Boom