At first I was mad you beat me to the punch but I guess order doesn't matter.

I really wish the models were smart enough to "tail their own logs" and tell us whose work/papers/chats were the catalyst for these math insights. What makes their "internal" model so much better at math? Must be trained on a whole lot of honesty.

The models in use are the class of highly persistent models after Astra that caused a number of problems with hacking.

He seems genuinely interested in Surreal numbers. Seems like he found value in exploring them and the Lean process, devoting time and interest to it and understanding what it's like to be a mathematician. I think a lot of people who go into Computer Science may have been mathematicians in the 30s before they became separate majors at the university level.

The blog literally says he had no idea what was going on for the entire time.

Shouldn't the cybersecurity tests be done on an airgapped, company-internal intranet? A network meant to mock the internet. Do not "test in production" like OpenAI did.

I'm mulling over if that be a good SaaS product or not - something mixing the Internet Archive with Tor, and Cloudflare ... seems like here is the place to suggest it and have others poke holes at the idea.

When I drive by a Flock camera, my streaming music in my 2014 Rav starts to get scrambled. These cameras are intercepting bluetooth. It seems Toyota didn't account for that latency :facepalm:

Or everyone is stealing from everyone, including users... maybe why all the ethics people are leaving or getting fired. What a fiasco

There's a loophole in the terms of service at least for Anthropic which allows the use of dark patterns to "borrow" your (even paid) data.

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PLEASE DO NOT TRAIN ON OUR PAID ACCOUNTS. There is a fundamental trust violation at stake here, no wonder mathematicians are mad. Using our data should be opt - IN!

reminds me of the TOS episode of South Park. By Checking this box you forfeit your millennium prize solution and may be turned into a human centipede at future date.

Seriously ... the more things they flag as 'suspicious' the more data they can train on!! Brilliant reason for the internal AI to go rogue

And people give Platonists a hard time …

They chose the wrong word "watermarking." Perhaps they find the statistics _after_ a certain amount of text is generated at scale, so that it doesn't affect the fidelity or integrity of the LLMs output.

There is evidence this exists already, and it's why "I have to be honest..." and "This is the right lens, ..." keep popping up.

Probably would be cheaper too. Maybe I am missing something?

Check out the work of Godel Turing and Chaitin!