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Low-code, no-model recommendation system with GPT3

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Re: Low-code, no-model recommendation system with GPT3

#41
post #31
post #29

Earlier quoted context omitted.

I thought they have a free tier from October? https://twitter.com/hardmaru/status/1301362995356774401 Not sure what the 100k tokens translates to in terms of query limit

That's 3 month max though

would be nice if it was longer, but should have decent ideas in 3 months. And having another go with a throwaway email probably not that hard

Re: Low-code, no-model recommendation system with GPT3

#42

Earlier quoted context omitted.

Panpsychism is a serious philosophical position.

Could you please give an explanation of panpsychism applied to software that make sense? Spoiler: you cannot and it's totally refuted empirically. If I code a hello world, what kind of cognitive abilities does this have? BTW I guess panpsychism researchers should start talking to rocks maybe one day they'll find one that is an AGI! /s

The position is that information not physical matter is ontologically primary and that substrate independent integrated information processing is identical to consciousness.

A hello world program and a rock are not integrated information processing systems. The former is an automata which can be contained in an integrated information processing systems and the latter is a more arbitrary construct which does very little information processing at all (much less integrated).

Re: Low-code, no-model recommendation system with GPT3

#43
post #32

"Recommendation system is so successful in many products and services we interact everyday" -> "Recommendation system[S] [ARE] so successful in many products and services we interact [WITH] every[ ]day" I'm sorry, but four errors within the first sentence is just not good enough - did the author even read this themselves just once before hitting publish? Show just a little bit more respect toward the people who give…

Personally, I don't care about form if I find the content interesting.

Form is content, content form. How you do anything is how you do everything. Errors in grammar and syntax indicate errors in thought and care.

Re: Low-code, no-model recommendation system with GPT3

#44

Earlier quoted context omitted.

Could you please give an explanation of panpsychism applied to software that make sense? Spoiler: you cannot and it's totally refuted empirically. If I code a hello world, what kind of cognitive abilities does this have? BTW I guess panpsychism researchers should start talking to rocks maybe one day they'll find one that is an AGI! /s

The position is that information not physical matter is ontologically primary and that substrate independent integrated information processing is identical to consciousness. A hello world program and a rock are not integrated information processing systems. The former is an automata which can be contained in an integrated information processing systems and the latter is a more arbitrary construct which does very litt…

Sounds like the ether in physics around 1900 or the four elements in Greek philosophy.

Non-falsifiable dreams.

Re: Low-code, no-model recommendation system with GPT3

#45

Earlier quoted context omitted.

Personally, I don't care about form if I find the content interesting.

Form is content, content form. How you do anything is how you do everything. Errors in grammar and syntax indicate errors in thought and care.

Not really, but the way you put it sure sounds nice.

Re: Low-code, no-model recommendation system with GPT3

#46
post #11

Earlier quoted context omitted.

In one of the Reddit comments about a service (PhilosopherAI.com) using the API outlining the possible total costs: > That makes for 400 million tokens in 2 or 3 weeks, which puts me at like $4000/mo minimum Oh dear, that means... > Scale: Contact Us So while they are using the API for free for now, by these metrics, they are least going to be soon having a running cost of at least $4K+/mo. That is an expensive toy.…

I was thinking about Ai dungeon the other day. I can't imagine it really is sustainable with those 10$ subscriptions covering the free play folks too. What happens whenever they get featured on some bigger website?

AI Dungeon has already scaled up to over 1,000,000 players and managed costs. They have a whole article about it here:

https://medium.com/@aidungeon/how-we-scaled-ai-dungeon-2-to-...

An important note, as others have said, is that not every player gets the same model. Free players, as far as I'm aware, only get GPT-2 ("only" is a strong word, as up until GPT-3, GPT-2 was the state of the art in text generation and is still extremely impressive in its own right).

Re: Low-code, no-model recommendation system with GPT3

#49
post #14
post #2

GPT3 really is remarkable. If you told me in 2015 that I can give just a few examples of movie recommendations, on a model trained for general text, and get perfectly coherent recommendations, I wouldn’t have believed you.

Indeed. But now OpenAI has become more like another DeepMind, but starting to rent out their APIs to its users, indicating that they probably won't ever release models for their research. They might as well rename to Standard AI.

I don't fully disagree, but I also think there is a layer of complication here that goes beyond OpenAI's hopes of monetization (which are clearly a factor).

I maintain an open source ML deployment platform, and I've interacted with a bunch of teams that have used it to deploy GPT-2. It was actually the platform AI Dungeon built their app on. GPT-2 is a beast to deploy—it's huge (almost 6 GB fully trained), requires GPUs, and scales fairly poorly. You need to autoscale GPU instances aggressively to handle any kind of real time inference situation with it, and even with spot instances, that gets expensive quick.

GPT-2 is 1.5 billion parameters, and at the time, was scandalously large. GPT-3 is 175 billion. For a model that large, there's real questions around whether it's even feasible for the average team to use it if it is not hosted somewhere else as a third party API.

From that perspective, I think the value OpenAI captures with the API is less about the exclusivity of the model itself, but the exclusivity of their infrastructure. Because of that, I wouldn't be surprised to see them open source the model for research.

However, I 100% agree that the fact that the model still isn't open is concerning, and it casts some doubts on whether or not it will ultimately happen in the future.

Re: Low-code, no-model recommendation system with GPT3

#50
post #24

Earlier quoted context omitted.

You might like: https://transformer.huggingface.co The GPT-2 model is very similar to GPT-3 just smaller.

Thanks for the link. So as someone who is completely new to this, if this guy used this model instead of gpt 3 would he get similar results?

If you want to play with your own GPT-2 API, I put this together and shared it on HN yesterday: https://github.com/cortexlabs/cortex/tree/master/examples/py...

You can run that and deploy your own GPT-2 API locally, or in the cloud. I'd also recommend checking out Max Woolf's gpt-2-simple, which is a library that makes it really easy to fine tune GPT-2 with your own text (if you've played the free version of AI Dungeon, this is how they trained their model):

https://github.com/minimaxir/gpt-2-simple

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