The better models do require using the chat endpoint instead of the completion endpoint. They are also, as you might infer, much more strongly RL trained for instruction following and the chat format specifically.
I definitely think it's worth the effort to try upgrading to gpt-3.5-turbo, and I would say even gpt-4, but the cost is significantly higher for the latter. (I think 3.5 is actually cheaper than davinci.)
If you're using the library you need to switch from Completion to ChatCompletion, and the API is slightly different -- I'm happy to provide sample code if it would help, since I've been playing with it myself, but to be honest it all came from GPT-4 itself (using ChatGPT Plus.) If you just describe what you want (at least for fairly small snippets), and ask GPT-4 to code it for you, directly in ChatGPT, you may be pleasantly surprised.
(As far as how to structure the query, I would suggest something akin to starting with a "user" chat message of the form "please complete the following:" followed by whatever completion prompt you were using before. Better instructions will probably get better results, but that will probably get something workable immediately.)
Have you considered switching to GPT-3.5 or -4? You can get much better results out of much less prompt engineering. GPT-4 is expensive but it's worth it.
Oh, I recognize that last document -- it's a userpage from the bitcoin-otc web of trust. See: https://bitcoin-otc.com/viewratings.php
I expect you'll also find petertodd in there. (You might find me in there as well -- now I'm curious!)
EDIT: According to https://platform.openai.com/tokenizer I don't have a token of my own. Sad. :-(
If that is true, and the marginal car does not much change the traffic situation, why isn’t there boundless demand for the road with slightly worse traffic, increasing congestion now?
Other people have gestured towards explanations that involve changing the timing or length of trips, but let me make an analogy that I think makes sense, but abstracts those things away.
When current is going through a diode, the marginal increment of current changes the voltage so little that we model it as constant-voltage for many purposes. Despite that, the change must be nonzero, or the feedback mechanism wouldn't work at all. It's just so small we can often ignore it.
One might similarly imagine that an enormous increase in traffic volume creates a tiny increase in congestion, or vice versa that a tiny increase in congestion discourages an enormous amount of traffic. Then one could say that there is more or less unlimited demand for travel at approximately the current level of congestion -- the freeway is a constant-congestion device much as a diode is a constant-voltage device.
(The analogy breaks down at a certain point -- if you keep adding cars to the freeway you will eventually get congestion collapse, and the flow of cars per unit time will be reduced rather than increased; whereas if you keep adding voltage to a diode you will rapidly set your diode on fire. I suppose that does reduce the flow of current.)
Beyond the analogy, I wonder what your question is really getting at -- it sounds like a general argument that looks at the current equilibrium of congestion vs trips, and asks why the equilibrium isn't higher, without specific reference to what the current level is. Obviously demand isn't truly boundless. At some point people must decide the traffic is too bad and stay home. I am reluctant to take a trip that Google Maps colors red, which can mean an estimated travel time more than twice the traffic-free time.
Yesss, this is an awesome development. I would happily sling some money at this project if it would help.
This makes sense, but my instinctive response is to point out that humans are only approximate reasoners (sometimes very approximate). So I think there can still be a meaningful conceptual difference between common knowledge and shared knowledge, even if you can prove that every inference of true common knowledge is technically invalid. That doesn't mean we're not still in some sense making them. .... And if everybody is doing the same thing, kind of paradoxically, it seems like we sometimes can correctly conclude we have common knowledge, even though this is impossible to determine with certainty. The cost is that we can be certain to sometimes conclude it falsely.
EDIT: This is not actually that different from p-common knowledge, I think. It's just giving a slightly different account of how you get to a similar place.
I am a little concerned that this would be totally unsingable for anybody who actually knows the original well (which is maybe not many people in the scheme of things, but the Bayesian Choir out here has done the original song before.)
I mostly agree, but I'm particularly surprised at the results for the Hershey's 45%. That's not all that dark (i.e. children might want to eat it), and 2 oz is not all that much chocolate for a child to eat, and it looks like 2 oz would be enough to rise above the less stringent FDA limit for children.
Thanks for explaining! I feel like that call makes sense.
https://github.com/gwern/gwern.net/pull/6
It would be exaggerating to say I patched it; I would say that GPT-4 patched it at my request, and I helped a bit. (I've been doing a lot of that in the past ~week.)