Episode 22: LLMs, OpenAI, and the Existential Crisis for Machine Learning Engineering episode artwork

EPISODE · Nov 27, 2023 · 1H 20M

Episode 22: LLMs, OpenAI, and the Existential Crisis for Machine Learning Engineering

from Vanishing Gradients · host Hugo Bowne-Anderson

Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs) join Hugo Bowne-Anderson to talk about how LLMs and OpenAI are changing the worlds of data science, machine learning, and machine learning engineering.Jeremy Howard (https://twitter.com/jeremyphoward) is co-founder of fast.ai, an ex-Chief Scientist at Kaggle, and creator of the ULMFiT approach on which all modern language models are based. Shreya Shankar (https://twitter.com/sh_reya) is at UC Berkeley, ex Google brain, Facebook, and Viaduct. Hamel Husain (https://twitter.com/HamelHusain) has his own generative AI and LLM consultancy Parlance Labs (https://parlance-labs.com/) and was previously at Outerbounds, Github, and Airbnb.They talk aboutHow LLMs shift the nature of the work we do in DS and ML,How they change the tools we use,The ways in which they could displace the role of traditional ML (e.g. will we stop using xgboost any time soon?),How to navigate all the new tools and techniques,The trade-offs between open and closed models,Reactions to the recent Open Developer Day and the increasing existential crisis for ML.LINKSThe panel on YouTube (https://youtube.com/live/MTJHvgJtynU?feature=share)Hugo and Jeremy's upcoming livestream on what the hell happened recently at OpenAI, among many other things (https://lu.ma/byxyzfrr?utm_source=vg)Vanishing Gradients on YouTube (https://www.youtube.com/channel/UC_NafIo-Ku2loOLrzm45ABA)Vanishing Gradients on twitter (https://twitter.com/VanishingData) Get full access to Vanishing Gradients at hugobowne.substack.com/subscribe

Episode metadata supplied by the publisher feed · Published Nov 27, 2023

Embed this episode

NOW PLAYING

Episode 22: LLMs, OpenAI, and the Existential Crisis for Machine Learning Engineering

0:00 1:20:08

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Vanishing Gradients?

This episode is 1 hour and 20 minutes long.

When was this Vanishing Gradients episode published?

This episode was published on November 27, 2023.

Can I download this Vanishing Gradients episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!