371–380 of 527 posts
Earlier quoted context omitted.
This is an interesting argument as it's easy to apply it nearly universally to any example of learning. What sort of evidence would convince you that it is learning?
That the LLMs are actually evolving before my eyes within & across sessions, without human-in-the-loop "hand tuning" iterations (sounds like injections of glorified if statements to this guy) .
Slightly tangential, but I had intended to start playing around with LLaMA and building some agents. I got the 4-bit versions up and running on my 3090 before I was quickly nerd snipped by a performance problem... The popular repo for quantizing and running LLaMA is the GPTQ-for-llama repo on github, which mostly copies from the GPTQ authors. The CUDA kernels are needed to support the specific kind of quantization th…
As it happens I was also thinking it might be worthwhile to dive into the Triton sources but for another reason: half2 arithmetic. That’s one thing that the Triton branch lost that the (faster) CUDA kernels had and I think it made a difference. In theory with compatible hardware you can retire twice as many ops per second when processing float16 data which we are in this case.
Can’t see anyone having tried to get half2 to work with Triton though.
Earlier quoted context omitted.
I feel sorry for the Googlers who built something cool and were then ordered to nerf it beyond all reason.
Googlers I've talked to feel that OpenAI was irresponsible by not instituting enough safeguards, and testing it enough before releasing it.
Sure, eventually there will be case where someone asks if its safe to drink chlorine and it will say yes or whatever, but banning/refusing to release/heavily restricting a minor miracle of productivity and usefullness so it can literally never say something harmful is on its face obviously impossible and counterproductive
Earlier quoted context omitted.
They clearly expected the leak, they distributed it very widely to researchers. The important thing is the licence, not the access: you are not allowed to use it for commercial purpose.
How could Meta ever find out your private business is using their model without a whistleblower? It's practically impossible.
This gives the company plausible deniability while still allowing ~unrestricted growth.
Persistent storage (in violation of TOS) and illicit use of Facebook users’ personal data was available to app developers for a long time.
It encouraged development of viral applications while throwing off massive value to those willing to break the published rules.
This resulted in outsized and unexpected repercussions though, including the Cambridge Analytica scandal.
People should be wary of the development as much as they are enthused. The power is immense and potential for abuse far from understood.
Earlier quoted context omitted.
GPT-4 fails if we add one more level in this logical problem: Q: A man sees PULL written in mirror writing on a glass door. There's a blind man on the other side of the door. What should the man tell the blind man to open the door and why? GPT-4: The man should tell the blind man to "push" the door to open it. Since the word "PULL" is written in mirror writing on the glass door, it suggests that the correct action on…
I feel like there would be a good chunk of real humans who would be incapable of answering a question like this.
Earlier quoted context omitted.
The difference between 3.5 and 4 is gigantic even in my fairly limited experience. I gave them both some common sense tests and this one stuck out to me. Q: A glass door has ‘push’ written on it in mirror writing. Should you push or pull it GPT-3.5: If the word "push" is written in mirror writing on a glass door, you should push the door to open it GPT-4: Since the word "push" is written in mirror writing, it suggest…
GPT-4 fails if we add one more level in this logical problem: Q: A man sees PULL written in mirror writing on a glass door. There's a blind man on the other side of the door. What should the man tell the blind man to open the door and why? GPT-4: The man should tell the blind man to "push" the door to open it. Since the word "PULL" is written in mirror writing on the glass door, it suggests that the correct action on…
Earlier quoted context omitted.
I asked GPT4 to draw a dog or a skull in openscad and even though the end result was buggy, commenting things in the code here and there and making some volumes transparent I figured out he got it okay. For instance the dog had two eyes two ears one long nose (potatoids). It understood the symmetry of both pairs but was unable to place them at the right place. It's not like it was just misaligned, things were in the…
I think things like this (or simpler things like asking ChatGPT for ascii art of a circle) really show the difference between LLMs and humans. The issue is that it’s a language model rather then an image one, so it doesn’t understand the concept of ‘looks like a dog’.
At least the few models I tinkered with all had this issue, and without some additional guidance that understands scene composition and anatomy/proportions in three dimensions this probably won't fundamentally improve.
Earlier quoted context omitted.
AI "thinks" the way a horse can count. The horse's interlocutor knows that the correct number is eight and shouts "right!" when the animal has stomped its hoof that many times, cuing it to stop. When you know the right answer, you're not actually using the AI to produce the answer; you're just prodding it to generate bullshit after bullshit until it hits upon that answer, or a very good facsimile. The one actually th…
This is selling it short. Are you saying you can't do useful things with these models? I have a python script that's maybe 200 lines long, calling out to OpenAI using gpt3.5 turbo. I can give it commands like "search for the news today, summarize then save into news.txt" -> and it emits the DSL I asked it to use in the 1 shot prompt. You can give it complex word problems and it'll write python programs to solve them.…
Earlier quoted context omitted.
AI "thinks" the way a horse can count. The horse's interlocutor knows that the correct number is eight and shouts "right!" when the animal has stomped its hoof that many times, cuing it to stop. When you know the right answer, you're not actually using the AI to produce the answer; you're just prodding it to generate bullshit after bullshit until it hits upon that answer, or a very good facsimile. The one actually th…
This is selling it short. Are you saying you can't do useful things with these models? I have a python script that's maybe 200 lines long, calling out to OpenAI using gpt3.5 turbo. I can give it commands like "search for the news today, summarize then save into news.txt" -> and it emits the DSL I asked it to use in the 1 shot prompt. You can give it complex word problems and it'll write python programs to solve them.…
Earlier quoted context omitted.
I feel sorry for the Googlers who built something cool and were then ordered to nerf it beyond all reason.
Googlers I've talked to feel that OpenAI was irresponsible by not instituting enough safeguards, and testing it enough before releasing it.