Maybe not due to attention, but it is certainly possible for chat content to get leaked into other conversations due to bugs in the stack, and in fact it has happened before.
"We took ChatGPT offline earlier this week due to a bug in an open-source library which allowed some users to see titles from another active user’s chat history. It’s also possible that the first message of a newly-created conversation was visible in someone else’s chat history if both users were active around the same time."
You are probably right about this particular LaTeX issue though.
In my case I had hundreds of invoices in a not-very-consistent PDF format which I had contemporaneously tracked in spreadsheets. After data extraction (pdftotext + OpenAI API), I cross-checked against the spreadsheets, and for any discrepancies I reviewed the original PDFs and old bank statements.
The main issue I had was it was surprisingly hard to get the model to consistently strip commas from dollar values, which broke the csv output I asked for. I gave up on prompt engineering it to perfection, and just looped around it with a regex check.
Otherwise, accuracy was extremely good and it surfaced a few errors in my spreadsheets over the years.
Immunostimulant is a reasonable way to put it: it takes the brakes off one part of the immune system. (Similarly, we call caffeine a central nervous system stimulant and it works by blocking adenosine, which is one of the brakes on brain activity.)
And it's not always specific to tumours. My wife's thyroid got wiped out. The endocrinologist said it was like bombing a paint factory: first a massive spike in thyroid hormones, then a crash as no more were produced.
If you're trying to say that immunostimulant is a term of art distinct from immune checkpoint inhibitor, then fair point.
But what it seems like you're saying is checkpoint inhibitors don't "enrage/activate" the immune system, and they only target tumours, and both points are misleading if not outright wrong.
Yes, it's a different term and entirely separate category of drugs.
Checkpoint inhibitors cut the brakes. This reduces their ability to detect "self," and attack blindly.
What they don't do is poke immune cells with a stick to anger them like chemoattractants and cytokines. This approach can be used to signal, "hey, the tumor is over here." Causing them to attack more intelligently.
If you would like to learn more, I would recommend the books: (a) molecular biology of cancer; mechanisms, targets, and therapeutics, and (b) handbook of therapeutic biomarkers in cancer.
I have very quickly picked up the habit of pasting snippets of my code into GPT-4 and simply asking "Why is this not working?" Almost every time, it succinctly explains the apparent purpose of the code, and how it is subtly wrong.
It's so good that I often do this preemptively to avoid a compile/deploy/test cycle.
I was dying on the GPT-4 API waitlist too. I built a proof-of-concept with GPT-3.5, got some ada embeddings, played around with some common patterns for a couple of weeks, spent less than $20. I then applied to the waitlist again with a few short sentences about what I'd done, how GPT-4 would make it better, and how it would enable something new and valuable for a particular market. Approved that day.
It's not exactly a shortcut, and maybe it was just luck, but I suspect the key is just to start building with what you have and show a trajectory. The best part is that coding with ChatGPT-4 as a "colleague" has made the whole thing super fun.
Same for me. I see it as the combination of 5 things:
1. It lowers the activation energy of getting started; for me motivation tends to come after action, and it gets me to that point.
2. It taps into the intense drive of "someone is wrong on the internet!" as per https://xkcd.com/386/
3. It's a new and different way of working so it doesn't trigger the same mental scar tissue.
4. It's vaguely social and high-status (delegating tasks, correcting and reviewing), as opposed to feeling solitary, so it tickles different reward centres.
5. More gets done for the same effort, so the cost/benefit equation is better and the feedback loop tighter.
I just spent a month doing an E-Business Suite platform migration and it was very similar: follow the step-by-step instructions to apply patches and run commands. Each patch has a README file with dependent patches or commands which need to be completed first. It works mind-numbingly great until you run into the first of many circular dependencies.
That's one problem with treating the implementer as a machine to run code. The whole procedure can't be tested, so when parts are changed they can break the whole. It relies on the human in the loop to resolve the conflicts, which is not repeatable.
The other problem is the "mind-numbing" part. No-one can maintain 100% perfection all of the time. And in the context of presenting to people who don't know what it all means, I can see why mistakes would be made.
As a native speaker of English, I didn't know about mass nouns until I was an adult and I was trying to explain to a non-native speaker that they were using "the" too much.
ProxyJump (or the -J option as a shortcut) plus TCP port forwarding (-L/-R) is ridiculously powerful. You can chain jump hosts with commas, threading a port forward deep into (or out of) multiple server hops with a single command.
https://openai.com/index/march-20-chatgpt-outage/
"We took ChatGPT offline earlier this week due to a bug in an open-source library which allowed some users to see titles from another active user’s chat history. It’s also possible that the first message of a newly-created conversation was visible in someone else’s chat history if both users were active around the same time."
You are probably right about this particular LaTeX issue though.