I think the video LegalEagle uploaded explains it quite succinctly: for the sale there was a certain split between the debtors, the debtors with the largest portion were willing to forego a portion such that the other debtors would get a larger portion if The Onion’s bid was the winning one. In effect, the other debtors would get more money out of the 1.75m than the 3.5m bid, and the debtors that ‘got less’ are the ones that offered the money in the first place.
Neat idea. This could be refined by adding a git hook that runs (rip)grep on the entire codebase and fails if anything is found upon commit may accomplish a similar result and stop the code from being committed entirely. Requires a bit more setup work on de developers end, though.
These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.
There are techniques to allow it it ‘read on demand’, but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft’s copilot does, and is something which I don’t think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).
I am not sure whether AI will make the creation of asset flips much easier though, given that store bought assets are already being dropped into a ‘game’ already.
Looks like this is reddit, using /r and all.