To successfully reason in the way it did, ChatGPT would have needed a meta-representation for the word “actually,” in order to understand that its prior answer was incorrect.
What makes this a meta-representation instead of something next-word-weight-y, like merely associating the appearance of “Actually,” with a goal that the following words should be negatively correlated in the corpus with the words that were in the previous message?
Thank you for your integrity, and congratulations on your successful research into the cost-effectiveness of this intervention!
So true! When I read the 80k article, it looks like I’d fit well with ops, but these are two important executive function traits that make me pretty bad at a lot of ops work. I’m great at long-term system organization/evaluation projects (hence a lot of my past ops work on databases), but day-to-day fireman stuff is awful for me.
Was coming here to do the same thing!
You might like these articles:
Deep Report on Hypertension by Joel Tan
Intermediate Report on Hypertension by Joel Tan
Hypertension is Extremely Important, Tractable, and Neglected by Marshall
Unfortunately, I’m not available during the time period specified, but I’m interested in hearing how this goes and whether you open up a cohort later with different timezone availability.
Interesting point about how any extinction timelines less than the length of a human life change the thresholds we should be using for neartermism as well! Thank you, Greg. I’ll read what you linked.
Thank you Vasco! This seems hard to model, but worthwhile. I’ll think on it.
Good to know, thanks! I’ve only been to EAGxNYC and EAGxBerkeley so far, so this is useful to help me calibrate.
I did feel like it was fancier than we needed it to be. I loved it, it was a great experience! But now that I know how great it is to have Listerine at conferences, I feel like I can bring my own for cheap. I’d also be happy enough to see like, instant oatmeal next to a kettle for breakfast. “Bring your own lunch/dinner,” especially if the venue was down the road from a market. I’m a foodie for sure, and there is something important about showing people that vegan catering can be awesome. Good food is a big part of what turned me vegan. But it also makes me feel weird to see the EA community pampering me.
It was, however, important to me that it was in a central location. Living in Canada, any conference that I go to is probably going to be a travel situation. I don’t have a license (in any country), so I wouldn’t be able to rent a car if it was like, in the suburbs.
Having just gone to EAGxNYC, I’d be really alarmed if I walked into an EAG and it had higher production value than that. The chairs were so many different-but-coordinated styles. There was Listerine and contact lens fluid in the bathrooms. The soap was from a perfume house!
Cool, thanks! My bookmarks include AAC and 80k, which you have on there, as well as Tom Wein and EA Opportunity Board mentioned by other commenters. I also have:
https://charityvillage.com/
https://gfi.org/vocation/
https://www.facebook.com/groups/1062957250383195/
https://www.effectivejobsboard.org/
Edit: And to tree out even more in the vegan space, GFI’s alt protein career portal includes links to the Tälist, Alt Protein Careers, and Blue Horizon job boards.
(Can’t say enough how much I appreciate it when people take my words of uncertainty like “could” literally!) Indeed, in most situations I can think of, I’d prefer a quantitative model. Especially by an experienced expert! Would that it were always available. Thanks for your comment!
GiveDirectly is a great option for people who put a high value on beneficiary autonomy and are open to giving anywhere in the world! This post is more about including people in the effective giving conversation who want to give back to their own community—maybe because they already live in one of the communities in the world with extreme poverty, or maybe because they’re not all the way EA and that’s just how they prefer to give.
Amazing. Maybe I’ll see you there!
I’m also wondering if the butcher shop and the grocery store didn’t have different answers because of the name you gave the store. Maybe it was because you gave the quantity in pounds instead of in items?
You previously told ChatGPT “That’s because you’re basically taking (and wasting) the whole item.” ChatGPT might not have an association between “pound” and “item” the way a “calzone” is an “item,” so it might not use your earlier mention of “item” as something that should affect how it predicts the words that come after “pound.”
Or ChatGPT might have a really strong prior association between pounds → mass → [numbers that show up as decimals in texts about shopping] that overrode your earlier lesson.