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TextSynth Server

bellard.org

71–80 of 115 posts

Re: TextSynth Server

#71
post #24

Very interesting as usual from Fabrice Bellard, but I'm a little bit disappointed this time, because libnc is a closed source DLL. Nevertheless it will be interesting to compare it to the amazing work of Georgi Gerganov: GGML Tensor Library. Both are heavily optimized, supports AVX intrinsics and are plain C/C++ implementation without dependencies.

I expect LibNC will be better in every aspect: performance, accuracy, determinism. But hopefully with time we will close the gap.

The comparison table from the ts_server site looks awesome though. I wish we could generate one for llama.cpp, unfortunately too busy with other things at the moment.

Re: TextSynth Server

#72
post #66
post #62

Earlier quoted context omitted.

Using ChatGPT as a disassembler seems like a dumb idea when free disassemblers already exist. What possible advantage does it give?

The ability to explain the code, and extract higher level understanding. Disassembling into raw instructions is the most trivial part of reverse engineering an application. Hence "and explain what they appear to be doing" bit. For the pieces I've tested, it often recognises the source language, and could give ideas about what the code was for and what it did.

> Disassembling into raw instructions is the most trivial part

So why not do it in the proven-correct tools and give ChatGPT the instructions?

I'm all for finding neat use cases but I wouldn't use an AI chatbot as a calculator...

Re: TextSynth Server

#73
post #70

I've been feeling FOMO (for lack of a better term) about recent AI & ML/GPT progression. It feels like ML/AI it might be the beginning of the end for a large class of things (if I wanted to be alarmist I'd say "everything") -- and the fact that Fabrice Bellard has jumped in and done the absolutely obvious rising-tide thing (building an API that abstracts the technologies) speaks volumes. Releasing something like this…

> There are too many world-changing things moving forward at the same time, and I'm only looking at such a small cut of the tech sphere. I don't know what to do with myself, I feel so thoroughly unprepared. I think the general trend is that actual useful applications are emerging from enormous models trained and owned by billion dollar companies only . Even projects that aim to run models on private consumer hardware…

> I think the general trend is that actual useful applications are emerging from enormous models trained and owned by billion dollar companies only.

One way to think about it: Today's LLMs require incredible outlays of capital and processor power (and crews of folks with doctorates), such as billion dollar companies can provide. But how is that different from what Intel brought to commodity CPUs in the '90s/'00s, or what Nvidia brought to GPUs in the '00s/'10s? Or even what Cisco and folks brought to networks?

Though we may never design an artisanal CPU/GPU/router, we get to work with them every day to make things, and to communicate. These LLMs can be that for us at this moment. Let's go out and enjoy them, and see what we can make within their (vast) domain-specific capabilities.

[takes off rose-tinted glasses]

Re: TextSynth Server

#74
post #72
post #66

Earlier quoted context omitted.

The ability to explain the code, and extract higher level understanding. Disassembling into raw instructions is the most trivial part of reverse engineering an application. Hence "and explain what they appear to be doing" bit. For the pieces I've tested, it often recognises the source language, and could give ideas about what the code was for and what it did.

> Disassembling into raw instructions is the most trivial part So why not do it in the proven-correct tools and give ChatGPT the instructions? I'm all for finding neat use cases but I wouldn't use an AI chatbot as a calculator...

You could do that too, but that is entirely missing the point, which is that ChatGPT is capable of inferring higher level semantics from the instructions and explain what the code is doing. You're getting hung up on a minor, unimportant detail.

Re: TextSynth Server

#75
post #73
post #70

Earlier quoted context omitted.

> There are too many world-changing things moving forward at the same time, and I'm only looking at such a small cut of the tech sphere. I don't know what to do with myself, I feel so thoroughly unprepared. I think the general trend is that actual useful applications are emerging from enormous models trained and owned by billion dollar companies only . Even projects that aim to run models on private consumer hardware…

> I think the general trend is that actual useful applications are emerging from enormous models trained and owned by billion dollar companies only. One way to think about it: Today's LLMs require incredible outlays of capital and processor power (and crews of folks with doctorates), such as billion dollar companies can provide. But how is that different from what Intel brought to commodity CPUs in the '90s/'00s, or…

> But how is that different from what Intel brought to commodity CPUs in the '90s/'00s, or what Nvidia brought to GPUs in the '00s/'10s? Or even what Cisco and folks brought to networks?

Yes, they made these technologies accessible and useful. And very few people needed to understand high-K dialetrics or out-of-order execution to use them, hence I think the FOMO is misplaced

Re: TextSynth Server

#76
post #74
post #72

Earlier quoted context omitted.

> Disassembling into raw instructions is the most trivial part So why not do it in the proven-correct tools and give ChatGPT the instructions? I'm all for finding neat use cases but I wouldn't use an AI chatbot as a calculator...

You could do that too, but that is entirely missing the point, which is that ChatGPT is capable of inferring higher level semantics from the instructions and explain what the code is doing. You're getting hung up on a minor, unimportant detail.

Apparently the point is proving it's possible. Not making it useful.

Re: TextSynth Server

#77
post #71

Earlier quoted context omitted.

I expect LibNC will be better in every aspect: performance, accuracy, determinism. But hopefully with time we will close the gap.

The comparison table from the ts_server site looks awesome though. I wish we could generate one for llama.cpp, unfortunately too busy with other things at the moment.

Hey liuliu, would love if you join the project when you find the time - your work is really inspiring!

Re: TextSynth Server

#78

I've been feeling FOMO (for lack of a better term) about recent AI & ML/GPT progression. It feels like ML/AI it might be the beginning of the end for a large class of things (if I wanted to be alarmist I'd say "everything") -- and the fact that Fabrice Bellard has jumped in and done the absolutely obvious rising-tide thing (building an API that abstracts the technologies) speaks volumes. Releasing something like this…

Every one of these articles fills me with a related kind of dread.

My whole life, my whole personality is architected around making things by hand for other people. My ideal world is a hipster stereotype where we all sit around using a small number of artisanal products to make other artisanal products for each other.

The arc of my programming career has gone lower and lower down the stack because when I create, I enjoy it most when it feels concrete, deliberate, and long-lasting. I get no joy out of duct taping a few libraries together (though I respect others who do).

While I spend a lot of my day doing code review and think it's a valuable, important part of the process, it's not my favorite task. I like making stuff, not just socially interacting with others to loosely guide them towards making stuff. The idea of AI-assisted software development to me just sounds like taking the one part of the job I like most—writing code—and turning it into even more code review, except now I'm reviewing code vomited out by a machine.

And I completely dread the long term societal implications of a world where most people spend most of their day consuming media auto-generated by a machine. Where lonely men and women hide from their social anxiety by cultivating simulated romantic relationships with chatbots. Where teens have their expectations of sex set by watching synthesized porn starring virtual actors doing things that are physically impossible. Where people watch auto-generated videos of impossibly idyllic vistas instead of actually leaving the house and going for a hike. Where our beliefs of the world are formed largely by synthesized news articles that may or may not accurately reflect it. Where children learn to speak, read, and write from AI tutors and pick up all the grammatical and stylistic quircks of the AI model such that they now because actual real parts of human language.

And, of course, where almost all of the massive profit generated by all of that flows to an increasingly small number of huge corporations.

None of that sounds like a world I want to live in.

I totally get the value of AI for things like classification and understanding. But generative AI feels like a pandora's box to me.

Re: TextSynth Server

#80
post #21
post #7

This man, Fabrice Bellard again... Frankly, I have not seen a more impressive portfolio of programming output.

I wonder if he ever went to interview they would try leetcode, or what is that squiggly thing in a code sample is for or are you a Language XXX programmer and other similar things. I can bet that this guy would probably fail many standard selection criteria.

I can bet that he wouldn’t.
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