461–470 of 554 posts
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I assume both previous comments, and this one, are also GPT-3? Edit: it is amusing to think that soon the way to distinguish them will be that human comments have weird errors caused by smartphone keyboard "spell checking" in them...
You really think my comment above was GPT-3 generated? Wow. Did I really make so little sense?
I'm out of the loop but is GPT-3 a pre-trained model like RedNet is for images? If such how can it be used easily? The article mentions getting access to an API, so is it an online service? Or, there's the pre-trained model (please, a tutorial!) and a service for those that don't want to configure it locally?
Nope, OpenAI didn't release the weights to the public, only a web API which is in private beta.
I published a response today to the sudden hype urging people to temper their expectations for GPT-3 a bit: https://minimaxir.com/2020/07/gpt3-expectations/ GPT-3 is objectively a step forward in the field of AI text-generation, but the current hype on VC Twitter misrepresents the model's current capabilities. GPT-3 isn't magic.
One of the biggest issues is with cherry-picking. Generative ML results benefit greatly from humans sampling the best results. They are capable of producing astonishing results but don’t do this consistently this has a huge impact on any effort to productize. For example I’ve seen quite a few examples of text->design, text->code, with GPT-3 you could build a demo in a day, but the product will probably be useless if…
This will accelerate development. Is the current version there? Probably not. But GPT-4 might, and would then accelerate the development of future versions.
Even though this is not "magic", it sounds like it will turn into a practically usable and extremely valuable tool soon.
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How many attempts did it take or did you just choose the first one? I have to admit, this is passing my turing test...
Really? I got about halfway through and realized that the comment had no point . If you tried to summarize what it was arguing, beyond the first sentence, I don't think you could make a coherent summary. Maybe the real lesson is we don't expect human-written comments on discussion fora to be particularly coherent....
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One of the biggest issues is with cherry-picking. Generative ML results benefit greatly from humans sampling the best results. They are capable of producing astonishing results but don’t do this consistently this has a huge impact on any effort to productize. For example I’ve seen quite a few examples of text->design, text->code, with GPT-3 you could build a demo in a day, but the product will probably be useless if…
If OP article was cherry-picked, the tree must not be very productive. More than cherry-picking, there's the Eliza Effect - it's pretty easy to make people think generated text is intelligent. That text can seem intelligent for a while isn't necessarily impressive at all. https://en.wikipedia.org/wiki/ELIZA_effect
Makes me worry about my own reading comprehension, but I think what happened was that since it was posted on HN and got upvoted a lot, I simply assumed that anything that I didn't understand was not the writer's fault, but mine.
For instance, it was unclear from the post what the bitcoinforum experiment was about, but I just dismissed it as me not being attentive enough while reading.
At one point GPT-3 writes: "The forum also has many people I don’t like. I expect them to be disproportionately excited by the possibility of having a new poster that appears to be intelligent and relevant." Why would people he doesn't like be paricularly excited about a new intelligent poster? Again I just assumed that I missed the author's point, not that it was nonsensical.
Twice it refers to tables or screenshots that are not included, but it seemed like an innocent mistake. "When I post to the forum as myself, people frequently mention that they think I must be a bot to be able to post so quickly" seemed like another simple mistake, meaning to say that when he posted as GPT-3, people thought he was being too quick.
This is like a written Rorschach test, when I'm convinced that what I'm reading must make sense, then I'll guess at the author's intent and force it to make sense, forgiving a lot of mistakes or inconsistencies.
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I recall a researcher filming their child from the day they were born until they began to speak. They wanted to find how many times a child had to hear a word in order to be able to repeat it back to the parent. The result, I think, was that if the child heard the word 2,000 times at all, they would be able to repeat it. But, if they heard the word 600 times at the same place, for instance the end of the couch, that…
> I recall a researcher filming their child from the day they were born until they began to speak. Can’t tell if you are kidding or not, but if you aren’t, mind sharing links about the researcher for the curious?
edit: Can't seem to find it which is a shame. I think it may have been included in a TED talk.
I could tell this was GPT-3 because it reads like SEO-style sentence structure :/ > I imagine that similar results can be obtained by republishing GPT-3’s outputs to other message boards, blogs, and social media. I actually wrote a bit about this scenario and how it could explode comment sections to stonewall topics, which I'm calling Commentdämmerung: https://simonsarris.com/commentdammerung Still, I think a lot of…
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If designers wanted to write texts to create visual designs, they'd be using some form of DSL and learn to code, wouldn't they? I believe the hype is that people think they can replace the designer by "just telling the computer" what they want. I don't believe that will work, as they already have trouble telling a human what they want, and a computer won't really know what to do with "I want it to kind of feel like i…
> people have a hard time writing their ideas about designs & features down, because they don't know what they want From an academic standpoint, writing is part of the thinking process. If you haven't written it down, you haven't fully thought it through. If it feels difficult, that's probably because your understanding isn't as complete as you thought it was. From a software development standpoint, implementing some…
I 100% agree. I noticed a giant shift in tasks when I made one client write tickets instead of making phone calls. Writing it down forces you to think it through.
And I agree about software development as well, yes. Though I think it's even rare to have somebody describe all the features they want unless it's an experienced software developer who basically writes a textual representation of the application.
But for most PMs (that I've worked with at least), they have vague ideas about what they want, and bringing them into focus is a back and forth with developers and designers. I don't see them getting anywhere with an NLP automaton, but maybe with an Eliza-style system: "Give me a big yellow button saying 'Sign up'" - "Why do you want a big yellow button saying 'Sign up'?" - "You're right, that's too on the nose... give me a link saying 'Sign up'"...
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That used to be a pretty annoying thing back in the days of IRC as a kind of DOS: run a bunch of bots that just replay a conversation from another channel. Engaging them fails, but is that because they are bots, or because they're just ignoring you?
The new kind can be more targeted for specific purposes. They could be excellent tools for trolling a forum, inciting flame wars and such.