If I were her attorney I’d push to have her sentence commuted to life without parol …

That’s exactly what her attorney is asking for.

The thing is, AI companies are terrified of model collapse because if they train AI systems on AI output, the model becomes useless.

That’s actually not a fact, more of a possibility. As far as am I aware, reinforcement learning from AI feedback (RLAIF) is currently employed by some of the most capable frontier AI companies; Anthropic openly admits to it, and their models are arguably the best.

A term that is often thrown around nowadays is recursive self-improvement (RSI), and it seems that there are at this time more knowledgeable proponents of RSI for intelligence development than opponents who raise the risk of model collapse.

But yes, training on today’s sloppified public internet would probably only have downsides.

Google is not at fault for search becoming so terrible. Everyone who engaged in SEO is. The internet would have sloppified much sooner if Google and other search engines had not relentlessly pushed back against SEO and continuously modified their algorithms. Lots of people definitely underestimate the extreme negative impact of SEO, and the lengths that search engine operators have to go to to have their service be at least somewhat useful. As soon as you have a search algorithm, people will attempt to manipulate it.

This overstates the findings by a lot, and borders on misinformation.

How AI use relates to student performance is complex, varying with how students use it and what for. PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI. In these scenarios, students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers. However, weekly users of AI for general purposes have similar performance outcomes to non-users. Students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science. However, these opportunities are more common among socio-economically advantaged students, risking a growing AI divide.

URL to OECD Summary

Edit: I concede that “heavily use” exonerates you, but your comment still feels a little disingenuous to me.

That is simply counter-factual. LLMs can absolutely do things that have not been published before, and they can access knowledge that is not in their training data through RAG. Intelligence is debatable, but reasoning models can reliably imitate “thinking” to a degree, and recursive self-improvement might lead to an autonomous advancement of intelligence. That LLMs allegedly “only regurgitate information” is simply wrong.

You lost all reasonable people at “acab’s”. No one will ever meaningfully rally behind your movement as long as you spread braindead takes like these. It’s poisonous for the left to be affiliated with you.