Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

OpenAI Codex

openai.com

Post reply on HN
Print view View original

81–90 of 181 posts

Re: OpenAI Codex

#81

Post by maxwells-daemon »

6gvONxR4sf7o wrote: post #69
maxwells-daemon wrote: post #45

The "language models don't really understand anything" corner is getting smaller and smaller. In the last few months we've seen pretty definitive evidence that transformers can recombine concepts ([1], [2]) and do simple logical inference using contextual information ([3], "make the score font color visible"). I see no reason that this technology couldn't smoothly scale into human-level intelligence, yet lots of peop…

> The "language models don't really understand anything" corner is getting smaller and smaller. In my mind, understanding a thing means you can justify an answer. Like a student showing their work and being able to defend it. An answer with a proof understands the answer with respect to the proof it provides. E.g. to understand an answer with regards to first order logic, it'll have to be able to defend a logical ded…

Look at the "math test" video.

Given the question: "Jane has 9 balloons. 6 are green and the rest are blue. How many balloons are blue?" The model outputs: "jane_balloons = 9; green_balloons = 6; blue_balloons = jane_balloons - green_balloons; print(blue_balloons)"

That seems like a good justification of a (very simple) step-by-step reasoning process!

Re: OpenAI Codex

#82

Post by mark_l_watson »

z77dj3kl wrote: post #8

I thought OpenAI was originally supposed to be some kind of for-the-good, non-profit institution studying AI and its safe use in particular with an effort to make it more accessible and available to all through more open collaboration. This is cool research, sure; but what happened to making models available for use by others instead of just through some opaque APIs? Maybe I'm just remembering wrong or conflating Ope…

They very transparently transitioned to a for profit company. It doesn't seem like they are aggressively profit oriented though: I am a paying customer of OpenAI beta APIs and the cost to use the service is very low. It also solves several classes of tough NLP problems. I used to sell my own commercial NLP library - glad I gave up on the years ago.

Re: OpenAI Codex

#85

Post by GistNoesis »

mxwsn wrote: post #57
GistNoesis wrote: post #50

Can I use this to write solidity contracts ?

That has got to be one of the worst possible use cases one could imagine. In page 33 of the appendix, the authors note that nearly 40% of RSA encryption keys created by Codex are clearly insecure.

Only if tokens have value.

If codex is able to handle a generic api from reading the doc, it maybe could use a python library for solidity contracts like https://web3py.readthedocs.io/en/stable/contracts.html

As a contract user, I'd probably have more trust in a contract written by an independent AI from a short natural language specification which can't hide intent, than a contract with hidden backdoor, or a subtle bug.

Also the AI will probably improve with usage.

You probably can generate multiple version of your contract, and maybe a high level bug correction scheme like taking the median action between those version can increase bug robustness and find those edge cases when action differ.

Re: OpenAI Codex

#86

Post by 3wolf »

I think integrations like the MS Word example they show off at the end of the live demo have the potential to be even more impactful than just generating code for programmers.

Re: OpenAI Codex

#87

Post by throwaway128327 »

woah wrote: post #77
throwaway128327 wrote: post #19

I don't understand what is going on, why are people even spending time on this? I think this and copilot and etc are solving a non problem of "we will remove the boring part of programming" by generating a bunch of code, so now it's even more boring to read it and check if it actually does what you want. In the same time zero of the developers I interviewed know how a linked list is laid out in memory, or what is the…

You're interviewing programmers for a job in operating systems programming?

Just full stack devs react native + go. Is it too wrong to think they are the same? Programming is programming, most computers work in a similar way no?

But they also don't know how garbage collection works in their language, or how to work with 1 million things in an efficient manner. Or why does the app pause for 100 ms because someone does sort while parsing dates within the sort.

For example, I have seen people that cant imagine what is the cost of a leaked database transaction, just back of the napkin wise, like you would think well, how many changes happened in between, how much we have to unwind when the session disconnects, when will it even disconnect because of the connection pool.. etc etc. Because the sql server is this magic rds thing. As if aws will solve everything with its pixie dust.

Re: OpenAI Codex

#88

Post by parksy »

throwaway128327 wrote: post #79
parksy wrote: post #70

Earlier quoted context omitted.

> do you really think it could lead in that direction? If you asked me 20 years ago, or even 10, I'd have said it was total science fiction. I wouldn't have been able to imagine how to do it. If you asked me 5 years ago, I'd have vaguely said something about AI, half jokingly. At the time I thought perhaps the models could be trained so we can do test-only development and let AI trained on formal test cases generate…

I wonder what will it make when you ask it to make a good bot AI for a game. "make a game with a formidable opponent that plays good enough to win with 51% probability" and of course the inevitable "make a better version of yourself"

From what I've seen the technology can fuse together a remarkable range of outputs, but all of them are essentially fused together from within the training set. If there were enough examples of AI opponents, it conceivably could do it since most game AIs are some form of state machine combined with a degree of statistical analysis and pathfinding (for mobile AI actors). It would "just" be replicating existing patterns.

As I understand it, it would take a dramatic leap from this kind of interpolation to being able to extrapolate and "self improve". So far I haven't seen anything that convinces me we're close to this, but again I'm not close to the wheel on the research side of things.

Re: OpenAI Codex

#89

Post by sbierwagen »

6gvONxR4sf7o wrote: post #69
maxwells-daemon wrote: post #45

The "language models don't really understand anything" corner is getting smaller and smaller. In the last few months we've seen pretty definitive evidence that transformers can recombine concepts ([1], [2]) and do simple logical inference using contextual information ([3], "make the score font color visible"). I see no reason that this technology couldn't smoothly scale into human-level intelligence, yet lots of peop…

> The "language models don't really understand anything" corner is getting smaller and smaller. In my mind, understanding a thing means you can justify an answer. Like a student showing their work and being able to defend it. An answer with a proof understands the answer with respect to the proof it provides. E.g. to understand an answer with regards to first order logic, it'll have to be able to defend a logical ded…

>In my mind, understanding a thing means you can justify an answer.

Sure, but how does that work with superhuman AI? Consider some kind of math bot that proves theorems about formal systems which are just flat out too large to fit into human working memory. Even if it could explain its answers, there would just be too many moving parts to keep in your head at once.

We already see something this in quant funds. The stock trading robot finds a price signal, and trades on it. You can look at it, but it's nonsensical: if rainfall in the Amazon basin is above this amount, and cobalt price is below this amount, then buy municipal bonds in Topeka. The price signal is durable and casual. If you could hold the entire global economy in your head, you could see the chain of actions that produce the effect, but your brain isn't that big.

Or you just take it on faith. Why do bond prices in Topeka go up, but not in Wichita? "It just does." Okay, then what was the point of the explanation? A machine can't justify something you physically don't have enough neurons to comprehend.

Re: OpenAI Codex

#90

Post by sailingparrot »

maxwells-daemon wrote: post #45

The "language models don't really understand anything" corner is getting smaller and smaller. In the last few months we've seen pretty definitive evidence that transformers can recombine concepts ([1], [2]) and do simple logical inference using contextual information ([3], "make the score font color visible"). I see no reason that this technology couldn't smoothly scale into human-level intelligence, yet lots of peop…

The definition of "understanding" behaves just like the definition of "intelligence": The threshold to qualify gets pushed by as much as the technology progresses, so that nothing we create is ever intelligent and nothing ever understands.
Post reply on HN