# 108. Last Week In AI — 2021: The (full) year in review

Page: https://stenobird.com/podcast/towards-data-science/108-last-week-in-ai-2021-the-full-year-in-review
Text version: https://stenobird.com/podcast/towards-data-science/108-last-week-in-ai-2021-the-full-year-in-review.md
Podcast: [Towards Data Science](https://stenobird.com/podcast/towards-data-science)
Published: 2022-01-05T15:21:52+00:00
Episode link: https://podcasters.spotify.com/pod/show/towardsdatascience/episodes/108--Last-Week-In-AI--2021-The-full-year-in-review-e1ch7nn
Audio file: https://anchor.fm/s/36b4844/podcast/play/45702327/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2022-0-4%2Fd2caa60d-f61a-a69a-9e68-b254fac5ff12.m4a
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JSON: https://stenobird.com/v1/public/podcasts/towards-data-science/episodes/108-last-week-in-ai-2021-the-full-year-in-review
Duration seconds: 3021

## Resource

2021 has been a wild ride in many ways, but its wildest features might actually be AI-related. We’ve seen major advances in everything from language modeling to multi-modal learning, open-ended learning and even AI alignment. So, we thought, what better way to take stock of the big AI-related milestones we’ve reached in 2021 than a cross-over episode with our friends over at the Last Week In AI podcast. *** Intro music : - Artist: Ron Gelinas - Track Title: Daybreak Chill Blend (original mix) - Link to Track: https://youtu.be/d8Y2sKIgFWc *** Chapters : 0:00 Intro 2:15 Rise of multi-modal models 7:40 Growth of hardware and compute 13:20 Reinforcement learning 20:45 Open-ended learning 26:15 Power seeking paper 32:30 Safety and assumptions 35:20 Intrinsic vs. extrinsic motivation 42:00 Mapping natural language 46:20 Timnit Gebru’s research institute 49:20 Wrap-up

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## Transcript

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