AI Safety Fundamentals: Alignment

Visualizing the Deep Learning Revolution

May 13, 2023

The podcast explores the rapid progress of AI fueled by deep learning techniques, highlighting advancements in vision, games, language tasks, and science. It discusses the evolution of AI image and text generation, the split in the United Methodist Church, advancements in large language models like ChatGPT, and challenges in AI progress including concerns about AI algorithms for generating chemical weapons.

41:31

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Quick takeaways

AIs have advanced rapidly in various tasks, challenging conventional limitations.

Progress in AI is primarily due to scaling simple algorithms, not deep scientific understanding.

Deep dives

Evolution of AI Capabilities

Over the past decade, the field of AI has witnessed substantial advancements due to the success of deep learning methods. The progress in AI capabilities has outpaced expectations, with AIs now excelling in various tasks, making it challenging to find tasks they can't master. This progress has largely been driven by scaling up simple algorithms rather than through a principled understanding of deep learning.

Intro

4min

Evolution of AI Image and Text Generation

14min

Historic Split in the United Methodist Church

2min

Advancements in Large Language Models and AI Technology

14min

Advancements and Challenges in AI Progress

8min

The field of AI has undergone a revolution over the last decade, driven by the success of deep learning techniques. This post aims to convey three ideas using a series of illustrative examples:

There have been huge jumps in the capabilities of AIs over the last decade, to the point where it’s becoming hard to specify tasks that AIs can’t do.
This progress has been primarily driven by scaling up a handful of relatively simple algorithms (rather than by developing a more principled or scientific understanding of deep learning).
Very few people predicted that progress would be anywhere near this fast; but many of those who did also predict that we might face existential risk from AGI in the coming decades.

I’ll focus on four domains: vision, games, language-based tasks, and science. The first two have more limited real-world applications, but provide particularly graphic and intuitive examples of the pace of progress.

Original article:
https://medium.com/@richardcngo/visualizing-the-deep-learning-revolution-722098eb9c5

Author:
Richard Ngo

A podcast by BlueDot Impact.

Learn more on the AI Safety Fundamentals website.