> The industry is much closer to self-improving AI than previously expected, they warn.

  > So tech companies should consider slowing or pausing frontier AI development to allow time for researchers to gain a better understanding of the potential societal harms self-improving AI could unleash.

There's an unsubscribe link, but it directs me to login to my account to manage my e-mail preferences -- I don't have an account. They have a separate, hard to find, "remove me from your invitations" form, but they seem to ignore that. I finally sent a CCPA request (very hard to find the link), which went unacknowledged, but the e-mails seemed to stop until recently, when they started again.

The kicker is that they think I'm someone else (a relative), so it's all completely ridiculous.

  > The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language.

  > The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it...

  > The third warning was about environmental cost.

  > The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit.

  > The fifth warning was the one Google cared about most. Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them.

  “This idea of wealth taxes on the super-rich has a clear connotation of envy,” Milei told Neura. “We consider taxes to be theft.”