581–590 of 629 posts
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None of this stuff even existed 3 years ago and you're asking like we're talking about self-driving cars. What hubris. My god.
> None of this stuff even existed 3 years ago Copilot has existed since 2021. "What hubris. My god." listen to yourself...
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Steve Jobs may be a legend at business, but an engineer he is not. To say nothing of the fact that whole reason "it just works" is because of said engineering. If you would like to be the innovator that finally solves that, then great! Otherwise you're just bloviating, and by god do we already have enough of that in this field. I'm approaching 20 years of professional SWE experience myself. The boring shit is my brea…
The point is not the individual tools, which at this point are just wrappers around the major LLMs. The point is the snake oil salesmen of major LLM companies have been telling us for several years now that it is "just about to happen". A new technology revolution. A new post-scarcity world if you will. A tremendous increase in technological output, unleashed creativity etc. Altman routinely blabs about achieving AGI…
I use a couple of different tools because they're each good at something that is useful to me. If Jetbrains AI service had a continue.dev/cline like interface and let me access all the models I want I might not deviate from that. But lucky for me work pays for everything.
You also seem awfully fixated on Copilot. How much exactly do you think your $12/month entitles you to?
Can someone explain what is going with 4o and Anime with Ghibli Style? Why is it suddenly all over x/twitter?
it isn't Ghibli style in particular, just any style as 4o image gen is much better at maintaining a particular art style, the ghibli ones just stand out due to one tweet that blew up and people followed along
Ran through some of my relatively complex prompts combined with using pure text prompts as the de-facto means of making adjustments to the images (in contrast to using something like img2img / inpainting / etc.) https://mordenstar.com/blog/chatgpt-4o-images It's definitely impressive though once again fell flat on the ability to render a 9-pointed star.
Have u had any luck with engineering/schematics/wireframe diagrams such as [1] ?? [1] https://techcrunch.com/wp-content/uploads/2024/03/pasted-ima...
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Do you have another example from YandexArt? https://images.ctfassets.net/kftzwdyauwt9/7M8kf5SPYHBW2X9N46... OpenAI's human faces look *almost* real.
>OpenAI's human faces look almost real. Not sure, I tried a few generations, and it still produces those weird deformed faces, just like the previous generation: https://imgur.com/a/iKGboDH Yeah, sometimes it looks okay. YandexArt for comparison: https://imgur.com/a/K13QJgU
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There are so many points to consider here im not sure i can address them all. - Airplanes dont have wings like birds but can fly. and in some ways are superior to birds. (some ways not) - Human brains may be doing some analogue of sample augmentation which gives you some multiple more equivalent samples of data to train on per real input state of environment. This is done for ml too. - Whether that input data is text…
> Airplanes dont have wings like birds but can fly. and in some ways are superior to birds. (some ways not) I think you're saying exactly what I'm saying. Human brains work differently from LLMs and the OP comment that started this thread is claiming that they work very similarly. In some ways they do but there's very clear differences and while clarifying examples in the training set can improve human understanding…
to be honest i dont really care if they work the same or not. I just like that they do work and find it interesting.
i dont even think peoples brains work the same as eachother. half of people cant even visually imagine an apple.
Neural networks seem to notice and remember very small details, as if they have access to signals from early layers. Humans often miss the minor details. Theres probably a lot more signal normalization happening. That limits calorie usage and artifacts the features.
I dont think that this is necessarily a property neural networks cant have. I think it could be engineered in. For now though seems like were making a lot of progress even without efficiency constraints so nobody cares.
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Just read the release post, or any other official documentation. https://openai.com/index/hello-gpt-4o/ Plenty was written about this at the time.
I read the post, and I can't see anything in the post which says that the model is not multi-modal, nor can I see anything in the post that suggests that the images are being processed in-context.
My experience with these announcements is that they're cherry picking the best results from a maybe several hundred or a thousand prompts. I'm not saying that it's not true, it's just "wait and see" before you take their word as gold. I think MS's claim on their quantum computing breakthrough is the latest form of this.
