Depends on the paper/authors. Sometimes they reallllyyy try to not tell you what they found or how they found it until you get to the method and conclusion.

Doesn't Open AI have an API for direct Chat GPT access?

Perhaps the number of unique queries is overstated: through vector similarity search and result caching, the vast majority of lookups would be duplicate searches already materialized. OpenAI has now introduced a "premium" option suggesting a market for premium search - suggesting room for more cash inflows. This may change their spend strategy, perhaps spending less on marketing and more on hardware.

Just ask ChatGPT for most relevant papers.

If the ChatGPT model were ham-fisted into Google’s existing search
businesses, the impact would be devastating. There would be a $36
Billion reduction in operating income. This is $36 Billion of LLM
inference costs.

"Our model is built from the ground up on a per-inference basis, but it lines up with Sam Altman’s tweet and an interview he did recently. We assume that OpenAI used a GPT-3 dense model architecture with a size of175 billion parameters, hidden dimension of 16k, sequence length of 4k,average tokens per response of 2k, 15 responses per user, 13 million daily active users, FLOPS utilization rates 2x higher than FasterTransformer at <2000ms latency, int8 quantization, 50% hardware utilization rates due to purely idle time, and $1 cost per GPU hour. Please challenge our assumptions"

Correct but the goal is not to train but to infer. I am not saying it wouldn't work just that I don't see why the priors of a transformer model would work better than RNNs or LSTMs in modeling the rewards of each play. Maybe there is something that I don't get about pocker that maps the game to graphs that can be learned through self attention.

Yo dawg I heard you like abstracts so I made an abstract for your abstract

Serious question: how are you using chatGPT programmatically? As I understand, open AI only has GPT3 accessible via API. ChatGPT is only accessible through chat.OpenAI.com, There is a waiting list to access the chat. GPT API

kagi also has a summarizer that can do pdfs : https://labs.kagi.com/ai/sum

Isn’t what abstract is for?

Thats what I'am not quite sure about. I assume the result would not be close to the nash equilibrium.

But I don't know since I have not worked with transformers before.

I think it comes down to, can we train a transformer with feedback on what hands were good and which ones were not. Looking at other responses it seems like that is not possible.

But technically it should be possible to train the model on hands, in the mentioned representation, and get an output that would be a valid poker play?

Using ChatGPT to summarize multiple papers and essentially do a lit survey for you is actually a great idea.

I think the training part is what I was missing.

I thought you would train a transformer like a normal neural net in the sense that you tell it what output you like and what is wrong.

Looking into it a bit more I assume you could get an output but nothing close to the nash equilibrium.

Thank you for the feedback.

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Yes, but what if you need to skim through dozens of papers to find what you need?

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Tabular CFR can be approximated with a neural network, as Noam Brown (1st author of Pluribus) and co-authors show in follow-up work: https://arxiv.org/abs/1811.00164

But you're comparing apples to oranges a bit asking if transformers can replace CFR. Transformers are a neural net architecture. You could of course encode poker stuff in text and feed that to a transformer which predicts the right move to play. But how do you train that network? CFR is a self-play learning algorithm (sort of like Alphago's MCTS) which learns good policies.

It would add value if you can ask questions about the paper. E.g. some mechanics applied.

The strength of transformers lies in the transfer of representations learned over large corpuses of text or images. Those are less likely to bring capabilities that generalise to pocker so traditional RL and Monte Carlo approaches are likely to have the upper hand. Pocker's challenges are not linguistic or visual perspective challenges.

Guys, I tried it,
It is good but not really impressive,
had more expectation,
but ok to say

legally the data is not public and the fact that facebook is actively trying to prevent scraping is making it very difficult to argue otherwise.

Legally, the data cnanot be public. The users give facebook a non-exclusive license with limited rights to store and process the data. From this does not follow the right that anyone who sees the shared images (for example) has a right to process them as well. If that wasthe case, the terms (https://www.facebook.com/terms.php 3.1) would have to state under which license the works are redistributed by facebook.

if it is illegal now it would be super illegal then, because removing watermarks on its own typically violates the license of the material.

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The question is 100% the same as "can i include GPLv3 code in my commercial closed source repository if i remove the license headers and ensure that the code ris never published?"