Artificial Intelligence 101: Home

"[ChatGPT] retains much of the information on the Web, in the same way that a jpeg retains much of the information of a higher-resolution image, but, if you’re looking for an exact sequence of bits, you won’t find it; all you will ever get is an approximation. But, because the approximation is presented in the form of grammatical text, which ChatGPT excels at creating, it’s usually acceptable. You’re still looking at a blurry jpeg, but the blurriness occurs in a way that doesn’t make the picture as a whole look less sharp."

A YouTube recording of the episode "A.I. and Stochastic Parrots with Emily Bender and Timnit Gebru"
*GRAPHIC LANGUAGE WARNING - US ONLY

A podcast episode "Don’t Fall for the AI Hype w/ Timnit Gebru"

On the risks of LLMs and what generative AI is actually capable of.

"In this episode, we're looking at how AI and race bias intersect. Safiya Noble, a professor at UCLA and the author of the book Algorithms of Oppression talks us through some of the messy issues that arise when algorithms and tech are used as substitutes for good old-fashioned human brains. And she says when it comes to understanding Artificial Intelligence, we should emphasize the "A" - and take the "I" with a grain of salt."

A breakdown of the boom-and-bust cycles of AI hype.

"We provide recommendations including weighing the environmental and financial costs first, investing resources into curating and carefully documenting datasets rather than ingesting everything on the web, carrying out pre-development exercises evaluating how the planned approach fits into research and development goals and supports stakeholder values, and encouraging research directions beyond ever larger language models."