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OpenAI Codex

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Re: OpenAI Codex

#61

Post by MasterScrat »

Vermeulen wrote: post #10

A warning to devs building on OpenAI APIs: We spent months developing a chatbot using GPT3 for our game and released a video showcasing it: https://www.youtube.com/watch?v=nnuSQvoroJo&t=264s Afterwards OpenAI then added GPT3 chatbot guidelines disallowing basically anything like this. We were in communication with them beforehand, but they decided later that any sort of free form chatbot was dangerous. What they allo…

> Afterwards OpenAI then added GPT3 chatbot guidelines disallowing basically anything like this. We were in communication with them beforehand, but they decided later that any sort of free form chatbot was dangerous.

Was this announced anywhere? We applied to deploy an application in this space, and they refused without providing any context, so I'd be really interested if they published details about restrictions in this space somewhere.

Re: OpenAI Codex

#62

Post by Vermeulen »

MasterScrat wrote: post #61
Vermeulen wrote: post #10

A warning to devs building on OpenAI APIs: We spent months developing a chatbot using GPT3 for our game and released a video showcasing it: https://www.youtube.com/watch?v=nnuSQvoroJo&t=264s Afterwards OpenAI then added GPT3 chatbot guidelines disallowing basically anything like this. We were in communication with them beforehand, but they decided later that any sort of free form chatbot was dangerous. What they allo…

> Afterwards OpenAI then added GPT3 chatbot guidelines disallowing basically anything like this. We were in communication with them beforehand, but they decided later that any sort of free form chatbot was dangerous. Was this announced anywhere? We applied to deploy an application in this space, and they refused without providing any context, so I'd be really interested if they published details about restrictions in…

https://beta.openai.com/docs/use-case-guidelines/use-case-re... "reliably being able to limit the conversational topics to strictly X, Y, and Z topics"

Re: OpenAI Codex

#63

Post by maxwells-daemon »

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…

As an add-on to this: I'd encourage anyone interested in this debate to read Rich Sutton's "The Bitter Lesson" (http://www.incompleteideas.net/IncIdeas/BitterLesson.html).

At every point in time, the best systems we can build today will be ones leveraging lots of domain-specific information. But the systems that will continue to be useful in five years will always be the ones freely that scale with increased parallel compute and data, which grow much faster than domain-specific knowledge. Learning systems with the ability to use context to develop domain-specific knowledge "on their own" are the only way to ride the wave of this computational bounty.

Re: OpenAI Codex

#64

Post by mola »

nradov wrote: post #37
minimaxir wrote: post #25

Earlier quoted context omitted.

> But they are so scared of their chatbot saying a bad thing and the PR around that they've removed the possibility of doing anything useful with it. It's not unreasonable to have checks-and-balances on AI content, and there should be. However, in my testing of GPT-3's content filter when it was released (it could be improved now), it was very sensitive to the point that it had tons of false positives. Given that pas…

Why should there be checks and balances on AI content? What most people label as "AI" today is literally just fancy statistics. Should there be checks and balances on the use of linear regression analysis and other statistical techniques? Where do we draw the line?

Ofcourse statistical techniques need checks and balances, hence peer reviewed academic papers, meta analysis, etc. statistics is a major tool for science these days. science needs checks and balances otherwise it's a pretty idle effort. Without checks and balances, you could just imagine any theory and believe it's the truth because you want to.

Re: OpenAI Codex

#65

Post by tux3 »

holler wrote: post #36
reducesuffering wrote: post #23

Earlier quoted context omitted.

Think bigger. Say I'm starting a startup: 1. "Setup Django, Nginx, and Postgres deployed on a Digital Ocean Ubuntu droplet." Done. 2. "Make a shopping page like $URL." Done. 3. "Fill it with data from X and connect with Stripe." Done. 4. ??? 5. Profit Seems like even a great dev will take 20x the time to do that if the model is able to correctly generate this, even with an error, customization, or two.

at the point where 1/2/3 are possible, what value does the startup have when anyone else can ask it to do the same thing?

Do your competitors have access to this tool that gets you started 20x faster? If so, you want the tool.

Your copycat startup may not have incredible value, but selling shovels always pays.

Re: OpenAI Codex

#66

Post by tome »

reducesuffering wrote: post #23
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…

Think bigger. Say I'm starting a startup: 1. "Setup Django, Nginx, and Postgres deployed on a Digital Ocean Ubuntu droplet." Done. 2. "Make a shopping page like $URL." Done. 3. "Fill it with data from X and connect with Stripe." Done. 4. ??? 5. Profit Seems like even a great dev will take 20x the time to do that if the model is able to correctly generate this, even with an error, customization, or two.

Why would you mention "Django", "Nginx", "Postgres", "Digital Ocean", "Ubuntu" or "Stripe"? Surely those are implementation details that the user wouldn't care about.

Re: OpenAI Codex

#67

Post by maxwells-daemon »

option_greek wrote: post #14
Vermeulen wrote: post #10

A warning to devs building on OpenAI APIs: We spent months developing a chatbot using GPT3 for our game and released a video showcasing it: https://www.youtube.com/watch?v=nnuSQvoroJo&t=264s Afterwards OpenAI then added GPT3 chatbot guidelines disallowing basically anything like this. We were in communication with them beforehand, but they decided later that any sort of free form chatbot was dangerous. What they allo…

That's a really interesting demo. What makes the responses so laggy? Does the model take that long to generate text? You can also experiment with things like repeating the user question or adding pauses like "hmm let's see" to make it less noticeable at least some of the time. Too bad they asked you to pull it. What's the danger they are worried about? Annoying thing from their press releases is how seriously they ta…

Autoregressive transformers take a while to generate text, since you need to run the whole model once for every word in the output.

Re: OpenAI Codex

#68

Post by febrilian »

am17an wrote: post #3

I really want to just play with this tech- it’s frightening but also the future, but I’m still waiting to be accepted on the GitHub copilot waitlist. I wonder how long this will take for people who don’t know someone who knows someone…

Uhh... I'm literally no one but got the access for like a week or so. I got 134 repos and 12,060 contributions in the last year. Idk if that mattered.

Re: OpenAI Codex

#69

Post by 6gvONxR4sf7o »

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 deduction of that answer.

These models still can't justify their answers very well, so I'd say they're accurate but only understand with respect to a fairly dumb proof system (e.g. they can select relevant passages or just appeal to overall accuracy statistics). They're still far from being able to justify answers in the various ways we do, which I'd say means that by definition that they still don't understand with regards to the "proof systems" that we understand things with regards to.

Maybe the next step will require increasingly interesting justification systems.

Re: OpenAI Codex

#70

Post by parksy »

throwaway128327 wrote: post #43
parksy wrote: post #38

Earlier quoted context omitted.

This is just nascent technology leading toward something like this: "Computer, I want to play a game." "Okay, what will the game be?" "I want to be a starship captain, give me a cool space ship I can explore the galaxy with" "Okay... like this?" "Not quite, make the galaxy more realistic, with real stars and planets. Also make it 3d. I want to be the captain inside the ship." "How about now?" "Cool, and there should…

Oh! this will be so cool! do you really think it could lead in that direction? To me it seems more like a metaphysical cargo cult. I think I am too pessimistic, I should shake it off, nothing good comes out of being pessimistic (by definition). Thanks for the inspiration!

> 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 endless code until all tests pass, but I didn't really imagine it would be possible to get a computer to take freeform written English (even in a tightly controlled manner) and produce functioning code.

Over the past couple of years I have seen increasingly fluent demonstrations and tried a few myself, and I have fallen off the fence and I think that with the pace that machine learning and AI assisted programming keeps advancing, this outcome is all but inevitable, as far fetched as it seems.

I was messing with the OpenAI sandbox over the weekend and it helped me generate several game design concepts from prompts similar to my post above that I could see myself being interested in building and playing. It's not difficult to imagine down the line with a few more advancements in this tech that the generated design could then instruct the code generator, fetch the assets, and stage the environment for a player or user to enter without ever touching a line of code.

I'm not close enough to the research itself know which of those problems are hard and which are easy, so I don't know if we'll see the first totally AI-generated "proto-holodeck" tech demo in the next 5 years, or the next 20 years, but I can't see it being more than 50 years away, and something tells me with the pace of things it will be much sooner than that, assuming we're all still around at the time to enjoy it.

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