181–190 of 207 posts
image-2023-04-25 looks more like an unicorn to me (although more a cow based unicorn than a horse based unicorn).
Which leads me to this genuine question: : how close do the images resemble a unicorn? I mean how can one track resemblance and how to draw a line saying GPT has drawn an unicorn?
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> This comment section is a super fascinating case study on the inherent flaws in human cognition. Especially when it comes to seeing patterns in random noise. The fact that some people believe that the model really has to have changed in the past few days is amazing You need only to look at the discourse around the Tesla FSD superusers to see this: they report a glitch at an intersection one day, then believe the ne…
Go into /r/chatgpt and /r/bing and it's a bit scary how many people anthropomorphize the models.
I agree that some people take it too far, but most seem to be using metaphor to abstract away the underlying complexities and facilitate conversation. I did the same thing back in college, anthropomorphizing cells and even molecules when I was learning about microbiology and biophysics (e.g., kinesins[1] are a family of postal workers who work hard to deliver packages to their clients in a timely manner, and they spend their free time going for strolls and practicing on their favorite tightropes). I now do it in my day-to-day work at an AI/ML shop to communicate not just what the entire pipeline is doing, but what individuals layers or encoders are doing, or even what variables in an equation are doing. I find that my colleagues and I are better able to understand and remember concepts and ideas when they're communicated as part of an anthropomorphic story, but we scarcely forget that the things we're dealing with aren't human.
But maybe I'm missing the point, and you're really worried about that first, smaller group of people who have really swallowed the Kool aid. To that, I can say that I don't think their behavior exceeds the baseline craziness/weirdness that I've come to expect from humanity. I'm sure there are far more people who believe in astrology than who believe that we've achieved true humanlike artificial general intelligence, for example.
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Go into /r/chatgpt and /r/bing and it's a bit scary how many people anthropomorphize the models.
Interesting that modern discourse is to use "scary" and "dangerous" and such words so much more. I wonder if it is related to the present rise in neuroticism and trigger warnings etc. It's not particularly "scary" to me that people do that. I remember Boomer and Scooby Doo bots that people anthropomorphized and those were warbots from barely 10 y ago. I suppose, in today's parlance, "it's scary how much people use fe…
It seems to be the current trend in communication nowadays: A race to induce the strongest reaction possible.
Why should someone be scared of that? We have anthropomorphised chairs, brooms and whatnot since the Walt Disney times and I am sure before in classic literature (I am not that literate to know for certain).
I prefer to be 'amazed' or 'excited' about what is happening: It means that AI is getting to a point where people feel it more 'relatable'. We are getting to that point in our technology development. The number of things we will be able to do with a technology with which we can interact that seamlesly is great.
Fast forward a couple of months later, I tried it again, and it was "blocked": It kept telling me "as an AI I cannot draw", even after emphazising the part of "generate SVG code". For me, it was another example of OpenAI "borking" the capabilities of ChatGPT.
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One important source of non-determinism is from using massive parallelism together with floating point arithmetic. In real math, a sum of numbers has an exact value that doesn't change if you change which order the numbers are added up in, but floating point arithmetic addition is not associative in the same way as real math, and parallelism can cause numbers to be added in a different order from execution to executi…
>and parallelism can cause numbers to be added in a different order from execution to execution Parallelism doesn't magically add non-determinism of this kind unless you intentionally build it to be non deterministic. Nothing prevents you from processing an array in order in parallel.
You would have to explicitly order the terms prior to reduction but you don't always have that level of control.
Several months ago when ChatGPT was just published, I asked it to draw a diagram of the contents of a cell (nucleus, membrane, amynoacids etc) in SVG (similar to the experiment shown here). At that time, it generated an OK SVG drawing, with very basic figures (squares, trianlges, circles, etc) representing the elements in a cell. I did this test to show my Biologist mom, the "power" of this new AI technology. Fast fo…
> Write SVG code to make a basic diagram of a cell showing structures such as the nucleus, ribosomes, and mitochondria.
Here's a very basic example of SVG code to represent a cell that includes structures like the nucleus, ribosomes, and mitochondria:
```svg
...
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It’s using GPT-4 by default, but we can’t know what it uses for real since that’s in the environment config.
It says "gpt-4-0613" on the web page as well. Why would they pretend it's GPT-4 but use GPT-3.5 in the background?
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My prompt was: Imagine you have to draw a SVG of an object. As a model that does not have any idea about how things look, you have to draw "blindly" - as there's no visual feedback, the only feasible tactic is to first list things components each thing consists of (e.g. for a car wheels, windows, chassis, bumpers, lights, etc.) with as much accuracy as you can, establish some constraints (e.g. in a horse legs come ou…
This prompt actually works pretty well. I suspect that because you added a step requiring the model to list out what it needs to draw first, it has a much easier time creating a reasonable SVG. https://chat.openai.com/share/be9cea50-d00d-4b05-ab54-b64619...
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I mean random sampling in the sense how autoregressive language models like GPT generate sequences using token probabilities. It's not a random svg, but the text sequence that is used to draw it suffers from inherent non-determinism in the underlying model.
Relying on token probabilities seems like the exact opposite of random
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Agree with this except for one data point. OpenAI does enhance/tweak/do something with the models at different levels. This can be determined by: 1. A change in the current model number (eg. gpt-3.5-turbo-0613) 2. On ChatGPT UI, the date at the bottom (eg. August 2023) So it isn’t correct to say “it is incredibly obvious that nothing has happened”. Not that obvious to me. A bit like how you can never tell for sure if…
The ChatGPT UI is indeed a wildcard. But it is irrelevant here because according to the github repo this page queries the API and OpenAI guarantees it doesn't change models with version number information (like gpt-4-0613, which is mentioned in the latest images). So this "experiment" would make a lot more sense if it was only run once every few months when the API actually offers new model versions and then generate…