AI’s Walking Dog: ‘AI itself has much to offer, but it has not lived up to its potential to serve the public good, and the context of AI’s development explains why’

The Race For the Best Stock Footage: Joe’s (skeptical) thoughts on the utility of AI video generators.

Artificial Irony: Misinformation Expert’s Testimony Has Fake Citations: Via unchecked ChatGPT usage.

Murdered Insurance CEO Had Deployed an AI to Automatically Deny Benefits for Sick People: Not to justify murder, but I’m sure there were a lot of desperate people very unhappy with Brian Thompson’s company.

OpenAI’s new model tried to avoid being shut down: By disabling its oversight mechanism and copying itself elsewhere, tho the context is important.

Introducing ChatGPT search: OpenAI releases its search engine.

Google CEO says over 25% of new Google code is generated by AI: Their computer programmers are turning into code reviewers.

The AI-nuclear weapons analogy, explained : Vox catalogues some similarities and differences between the two technologies.

The AI-Generated Product Reviews Choking the Internet Are Now Illegal: The FTC makes certain types of fake reviews illegal, whether human or robots wrote them, in the US.

Ban LLMs Using First-Person Pronouns: Maybe we shouldn’t allow AI chatbots to refer to themselves as ‘I’.

Ed Newton-Rex, who organised the recent anti AI ingesting everyone’s work for free statement that artists of all sorts of fame levels are signing makes a good point.

There are three key resources that generative AI companies need to build AI models: people, compute, and data. They spend vast sums on the first two - sometimes a million dollars per engineer, and up to a billion dollars per model. But they expect to take the third - training data - for free.

Big tech AI companies aren’t stingy with their money for everything. That’s one reason why they’re so unprofitable. It’s just that magic third ingredient that often attracts the $0 compensation rate.

Thom Yorke and Julianne Moore join thousands of creatives in AI warning: Even superstars are concerned about AI companies shovelling up the artistic output of humanity without constraint or compensation.

All What Is Delicious to Man: Today’s implausible vision of superabundance is a lot grimmer than the one that they were promised in the 1830s.

The Subprime AI Crisis: Ed Zitron worries about what happens when the unprofitability of the current generative AI business becomes unsustainable.

A Personal Take on Using LLMs: Eleanor Konik’s view on when she finds it reasonable to use large language models.