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This time, it feels different

nadh.in

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Re: This time, it feels different

#211

Post by [deleted] »

oxfordmale wrote: post #208
renonce wrote: post #185

Earlier quoted context omitted.

There is no point in arguing whether LLMs have minds or are conscious, and neither is arguing whether it actually understands any concepts. Neither are LLMs are the first tech to be useful to humans - caculators are invented much earlier. What is interesting is that it’s answering questions in a meaningful way that is competitive to humans. It replaces about 50% of jobs for each field where all work can be done on co…

The type writer, or the PC didn't replace the need for secretaries. PAs just have more responsibilities beyond typing letters. As translation is now cheaper, as it can be part automated, there is more demand for translation, whereas this was previously too expensive. The problem with ChatGPT is that you need to specify exactly what you want. Writing text and drawing is often a creative process where you will only kno…

[deleted]

Re: This time, it feels different

#212

Post by djmips »

probably_wrong wrote: post #35
shanebellone wrote: post #14

Earlier quoted context omitted.

You've also lived through many technologies that failed to achieve mainstream adoption despite demonstrating comparable levels of hype.

I'm constantly resisting the urge to write "MongoDB is webscale" whenever these threads show up. For the uninitiated: https://news.ycombinator.com/item?id=1636198 . The original video is gone but it lives on YouTube: https://m.youtube.com/watch?v=b2F-DItXtZs .

12 years later and I feel like the dream of being a farmer isn't so bad (I know - farming isn't easy).

Re: This time, it feels different

#213

Post by [deleted] »

Izkata wrote: post #199
retrac wrote: post #155

Earlier quoted context omitted.

We have spent the last seventy or more years working on machine translation. All the way back in the 1950s, big money went into it. Decades of hard work, mathematical models of human language, all manner of study, enormous bilingual corpuses of text with phonetic annotation, programmed in general-knowledge databases, fuzzy reasoning algorithms. The amount of work put into it is quite staggering, in hindsight. I remem…

> It is the same story in many other areas. Chess, Go? They learn to play chess and go better than any AI designed specifically to do so. Take GP's "stagnant for decades" with tech and turn it into "stagnant for centuries" with these. When it first started I remember professional Go players talking about just how big a shakeup it was.

[deleted]

Re: This time, it feels different

#214

Post by 9dev »

oxfordmale wrote: post #209
ai-punter wrote: post #194

Earlier quoted context omitted.

lol, really? Me: Can books be fluorescent? GPT-4: While the term "fluorescent" is typically used to describe substances that can absorb light and then re-emit it, often at a different wavelength, there's no inherent reason why a book couldn't be made with fluorescent properties. This could be achieved by using fluorescent ink, dyes, or paints on the cover or the pages, or by incorporating fluorescent fibers into the…

This exactly illustrates the problem of ChatGPT. I asked the same question, phrased slightly differently, and it said no. It also not unlikely my question was used to train CHATGPT further.

Does it, really? I’m pretty sure if you’d ask some people, there are going to be some that’d answer „no“ too.

Besides, you’re shifting the goalposts as you go, altering your arguments as it suits your view. The parent comment just disproved your entire point how LLMs cannot combine different fields - and now you just pick a different angle altogether. Maybe take a step back and reconsider your opinions?

Re: This time, it feels different

#215

Post by pcthrowaway »

oxfordmale wrote: post #209
ai-punter wrote: post #194

Earlier quoted context omitted.

lol, really? Me: Can books be fluorescent? GPT-4: While the term "fluorescent" is typically used to describe substances that can absorb light and then re-emit it, often at a different wavelength, there's no inherent reason why a book couldn't be made with fluorescent properties. This could be achieved by using fluorescent ink, dyes, or paints on the cover or the pages, or by incorporating fluorescent fibers into the…

This exactly illustrates the problem of ChatGPT. I asked the same question, phrased slightly differently, and it said no. It also not unlikely my question was used to train CHATGPT further.

ChatGPT is GPT3.5 isn't it? The other person was using GPT4.

Re: This time, it feels different

#216

Post by fzeroracer »

ukuina wrote: post #195
fzeroracer wrote: post #138

> It just repeats patterns > It is just a glorified probabilistic text generator. > It is just a “stochastic parrot”. > It “hallucinates”. > It is not “intelligent” the way humans are. > It does not actually “think” like humans. > It will never get human qualities like humour.[4] > It is snake oil and is no different from any other technology that has come before. > If it causes job losses, new jobs will emerge, like…

Some (many?) of those statements have been empirically proven false, like understanding humor. Multi-modal LLMs can explain why certain images are funny, for example.

It does not understand humor. LLMs respond affirmatively to whatever input you give it and use the elements of whatever you feed it to try and explain. That's the core mistake the article makes and why that specific point is wrong. Let me demonstrate.

I asked the LLM the following prompt: Can you explain why the joke "Where's the joke?" is funny?

The response: "The humor in the joke "Where's the joke?" is derived from its meta or self-referential nature. The joke plays with the expectation of a traditional joke setup and punchline structure. Typically, when someone tells a joke, there is an expected punchline that delivers the humor. However, in this case, the punchline is intentionally missing, and instead, the question "Where's the joke?" is posed."

All it's doing is the same thing when you ask it to summarize a piece of data. This isn't a joke or meant to be a joke, but by telling it to explain it as a joke/meme will cause the output to differ in and regurgitate a bunch of nonsense about humor. This isn't understanding humor.

Re: This time, it feels different

#217

Post by doctor_eval »

ukuina wrote: post #198
doctor_eval wrote: post #32

Earlier quoted context omitted.

I’m both a business person and an engineer. I recently did a short workshop where a marketing guy took us through using GPT and Midjourney to iterate through new business ideas. In the 4 hours of the workshop, a bunch of mostly non developer people generated about 500 business ideas using GPT, took the top ideas, and turned them into business pitches. A couple of people in the room thought the idea their promoting ca…

How does Midjourney factor into business idea generation?

We used it to generate images relating to a target audience and the product itself.

Interestingly (for me anyway) we got GPT to write the initial prompts for Midjourney.

Re: This time, it feels different

#218

Post by fzeroracer »

stevenhuang wrote: post #207
fzeroracer wrote: post #138

> It just repeats patterns > It is just a glorified probabilistic text generator. > It is just a “stochastic parrot”. > It “hallucinates”. > It is not “intelligent” the way humans are. > It does not actually “think” like humans. > It will never get human qualities like humour.[4] > It is snake oil and is no different from any other technology that has come before. > If it causes job losses, new jobs will emerge, like…

When someone compares LLMs to crypto you know they've lost the plot.

Tell you what, I'll go ahead and favorite this response and see what happens in about two years. By then I have a feeling I'll be vindicated and companies will have moved into the next Big Thing. Much like every other radical revolution that's been claimed in the past 10 years (Crypto, NFTs, Metaverse etc).

Re: This time, it feels different

#219

Post by divan »

oxfordmale wrote: post #172
divan wrote: post #167

Earlier quoted context omitted.

> LLM are mathematical models that, given your question, return a sequence of words based on a very complex probability model. How is this different from how humans respond? Our model could be just some orders of magnitude more complex. Or do you think there some _fundamentally_ different things are going on in the human brain?

You know what a book is and can reason about it. As a human you can provide answers that go beyond the knowledge you have ingested. For example, if you ask ChatGPT if books can be fluorescent it says no. However, as an adult you know someone somewhere has made a book with fluorescent images, as it is a cool thing. You are combining knowledge from two different fields (books + fluorescence) and establishing the likeli…

Yet, this doesn't answer my question. Human brain is obviously has so much more in it (visual cortex for starters, grid cells etc), and, in terms of neural network, much more sophisticated architecture. But still, there is a big probability that what we call "knowledge" and "reasoning" and "conciousness" are just a result of this sophisticated architecture. I.e. there is no special magical thing for "reasoning" that next generations of prediction models can't replicate.

There is a faboulous book by Jeff Hawkins "On Intelligence" (2004) that explores this. I think main premise of it still holds true: brain is "just" a highly sophisticated hierarchical tissue whose main job is to extract patterns and make predictions. Fundamentally it doesn't seem very different from what LLMs are.

Re: This time, it feels different

#220

Post by Mawr »

Every article on this subject is the same:

1. Deny there's hype

2. Start engaging in hype

LLMs are a just a tool. Yes, "just". They're good at certain tasks. Mainly ones that have a lot of training data available and don't require precise output. Images, writing, boilerplate code, etc. For any other task their usefulness falls of sharply.

> What it and its contemporaries have set loose in such a short period of time, and what is to follow on their heels tomorrow, is the real crux of the matter.

What is the idea that LLMs will get significantly better based on? That the technology finally got good enough to be useful is great, but past performance is not a predictor of future performance. Predictions need to be based on the nature of the technology in question.

1. There's only so much usable training data available out there and I suspect most of it is already being used. Once a programming LLM is trained on the code on Github it has basically seen it all.

2. They are incapable of learning anything. Not even trivial concepts. Therefore there's no real way for them to build up their understanding step-by-step like a human would.

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