351–360 of 768 posts
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Hmm…no, I’m not doubting the value of the interface. I’m asking what’s the “killer app”. Maybe I should just ask ChatGPT to explain it to me…
It’s programming. The thing is really great at programming, and everything else is icing on the cake. They already got my $20 a month lol
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> Bard would not trick anyone into thinking it was sentient, yet something they have supposedly did Bard is overtly a reduced-resources model compared to the best version of the same technology (which, if true, is probably a boneheadedly bad choice for a public demo when everyone is already wowed by the people who got theirs out first, but easily explains that disparity. Though so does “guy who wanted public attentio…
> Bard is overtly a reduced-resources model compared to the best version of the same technology There's a scaling problem. ChatGPT/LLM systems cost far more to run per query than the Google search engine. Google can't afford to make those the first line query reply. A big business model question is whether Google will insist you be logged in to get to the large language model. At Google scale, these things are going…
And given how aggressively they limit the number of search results (in spite of listing some ridiculous number of results on page #1) that percentage may well be very large.
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its good for so many things: Need to write a speech as a best man Write a eulogy for a deceased family member Recently used it to speed up the time to fix an oauth problem in code I didnt write, knowing nothing about oauth. Replaces stackexchange with much more tailored answers. can take hundreds of pages of text and distill it down to an executive summary of any length Daughter uses it to explain how to solve algebr…
> Need to write a speech as a best man > Write a eulogy for a deceased family member Yeah, if you're okay with sounding like marketing copy written by a robot. Remember last month when Stable Diffusion was supposed to put Disney out of business? Not gonna happen.
Apple seems to have focused more on being the "best" rather than the "first" for several hardware products (MP3 players, smartphones, tablets, smart watches, wireless earphones) and it seems to have worked out OK.
However I have no idea what their AI plans are.
From my perspective it’s just _confusing_ to work in AI right now. We have some massive models that are doing some really neat stuff, and apparently hundreds of millions of people are using them—but I keep wondering: to do _what_, exactly? I’m not asking what the models can do, I’m asking what people want the models to do every day, all the time. I’ve been shown some neat pictures people made that they thought were c…
Funny enough I don’t use it a lot for programming, maybe just to jog my memory on a topic.
From my perspective it’s just _confusing_ to work in AI right now. We have some massive models that are doing some really neat stuff, and apparently hundreds of millions of people are using them—but I keep wondering: to do _what_, exactly? I’m not asking what the models can do, I’m asking what people want the models to do every day, all the time. I’ve been shown some neat pictures people made that they thought were c…
One thing you're missing is that we now have a pretty good solution to any NLP pipeline that in the past you'd have to spend months to get right. You can probably still get better results by supervised training on specific tasks but it's good enough. NLP (as we knew it) is dead. This will take some time to show in the applications we use, as people figure out how to use and integrate it, and costs need to come down, but it will make it trivial to add smart functionality for things you previously needed an in-house ML team for.
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Reading and validating code is way easier than figuring out how to write it in the first place. A lot of programming is the same - functions, conditionals, loops, libraries, etc.. The hard part is mostly semantics across languages. Way easier for GPT to do the first pass, then go through it and read up on the parts you don't understand.
It isn't in my experience. Understanding code that you did not write for a problem that you do not fully grasp is a lot of work. It's hard enough when you did write the code and when you do fully grasp the problem, which you'd have to if you were to write it yourself. Typically that's what first draft code is for: to see if you actually understand the problem.
But with ChatGPT you can build it piece by piece.
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>Eventually, someone will figure out how to get hundreds of LLMs supervising teams of millions of LLMs to do some really wild stuff that is currently completely impossible. This is an intuitive direction. In fact, it’s so intuitive that it’s a little bit odd that nobody seems to have made proper progress with LLM swarm computation.
In particular, it's odd that the greatest software developer in the world (ChatGPT) hasn't made progress with LLM swarm computation.
From my perspective it’s just _confusing_ to work in AI right now. We have some massive models that are doing some really neat stuff, and apparently hundreds of millions of people are using them—but I keep wondering: to do _what_, exactly? I’m not asking what the models can do, I’m asking what people want the models to do every day, all the time. I’ve been shown some neat pictures people made that they thought were c…
This sub and blog post are all talking about ChatGPT which is no doubt amazing and far ahead of the curve. However I would also point to Metas new vision model: SAM (Segment Anything): it is so far beyond any other vision model, I actually believe vision will be solved in a few years now. People don’t realize that there was an industry of publishing paper with incremental improvements in small datasets in CVPR that h…
What does it mean to solve vision though?