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Anyone else witnessing a panic inside NLP orgs of big tech companies?

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Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#411
post #232

Earlier quoted context omitted.

This is not an event that calls for pithy adages. The fruits of ML are not a fad just like personal computing was not a fad. It's a watershed event that cuts across every knowledge worker's domain. If you're not currently using these LLMs it may not be obvious to you but those of us that have tried to apply them to our current fields see huge gains in productivity. Just in my own little slice of knowledge work, I've…

Uh-huh. How's them NFTs and Blockchain doing the watershed world changin these days?

ChatGPT Impact Differences.

db112nl@gmail.com Why wasn't Blockchain a watershed moment but chatGPT is.

There are several factors that contribute to why blockchain and chatGPT have had different impacts on their respective fields.

Firstly, blockchain technology has had a significant impact in certain areas, particularly in the financial industry, where it has been used to create new forms of digital currency and facilitate secure and efficient transactions. However, it has not yet achieved the widespread adoption and transformative impact that some had predicted. One reason for this may be that the technology is still relatively new and complex, and many organizations are still trying to figure out how best to implement it.

In contrast, chatGPT is a language model that has been designed to understand and generate natural language text. This technology has been more widely adopted because it has a broad range of potential applications, from customer service chatbots to language translation services. Additionally, language is a fundamental aspect of human communication, which makes the potential impact of language models like chatGPT more readily apparent to people.

Another factor that may have contributed to the different impacts of blockchain and chatGPT is the level of public attention and interest. While blockchain has received significant media coverage, it has not captured the popular imagination in the same way that chatGPT has. ChatGPT has been widely publicized and has even been featured in news articles and talk shows, which has helped to raise awareness and generate interest in the technology.

In conclusion, the differences in impact between blockchain and chatGPT can be attributed to a range of factors, including the complexity and novelty of the technology, the level of public awareness, and the broad range of potential applications.

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#412

Earlier quoted context omitted.

The problem is not that automation will eliminate our jobs. The problem is that we have created an economy where that is a bad thing.

What will the economy look like when the peak intelligence on the planet doesn't care about anything we do?

Probably not very different… since we basically have this in the form of insanely rich billionaires and multi-hundred millionaires, who basically exist in a life where they are divorced from everyone else and they don’t care about “us” … their money just compounding its growth automatically because they passed the tipping point where it’s hard to (other than deciding to do some crazy expensive thing like buy Twitter) spend their money faster than it comes in… I mean sure it might be a little different since an AI won’t eat or sleep, but when the heavily computerised economic activity involved in global investment and banking is already not sleeping and a sort of diffuse collective intelligence… yeah I’m not sure how different it would be unless we’re talking humans they would have to literally let the AI starve people for whatever reasons it may have… I feel like the odds of “communist revolution” type activities, where the workers seize the means of production, is probably higher for ephemeral AI overlord then for flesh and blood bosses and capital owners.

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#413

Earlier quoted context omitted.

"LLM’s can’t scope themselves to be strictly true or accurate" This isn't true though the techniques to do so are 1. Not as yet widespread 2. Decrease the generality of the model and its perceived effectiveness.

I'm interested to hear what these techniques are. Decreasing the generality will help, but I fail to see how that scopes the output. At best that mitigates the errors to an extent.

Requiring the answers to automatically verifiable, or having answers be inputs to a reliable query system?

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#414
post #150

Wow - this is just wild. I've seen lots of arguments around "AI won't take everyone's job, it will just open up new areas for new jobs." Even if you take that with the benefit of the doubt (which I don't really think is warranted): 1. You don't need to take everyone's job. You just need to take a shitload of people's jobs. I think a lot of our current sociological problems, problems associated with wealth inequality,…

> I mean, does anyone think that things like human translators, medical transcriptionists, court reporters, etc. will exist as jobs at all in 10-20 years? Maybe 1-2 years? It's fine to say "great, that can free up people for other thing", but given our current economic systems, how are these people supposed to eat? And it doesn't mean that the replacements will be much better, or even as good as the Humana they repla…

> how are these people supposed to eat?

not only am I sure people will have no trouble eating, I'm willing to wager obesity goes up

i'm not teasing, I don't think your worry is warranted

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#415
post #293

Earlier quoted context omitted.

Something curious that I've noticed is that the people who I see that are MOST excited are in tech. When I show ChatGPT to a lay person they don't really care. When I show it to a professional copywriter they say that if they submitted this content to a client they would lose the client. I'm reminded of when my son was learning to talk and everything he said seemed brilliant and coherent to me. To any stranger it sou…

Perhaps those in tech can simply see further out. It reminds me of the advent of the internet, the lay person also didn't care, until websites and web apps were made that catered to their needs. But the people who made those sites and apps were precisely the tech people who could see beyond the lay person's idea of what the internet was. So too with AI.

So too with NFTs and web3 /s

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#416
post #179

Earlier quoted context omitted.

The secret is that there are no grammars in our brains. Rules are statistical, not precise. Rules, idioms are fluid and... statistical. We're a bit more specialised than these new models. But that's it, really.

^ This. I think the more we internalize the fact that we're also basically LLMs, the more we'll realize that there likely isn't some hard barrier beyond which no AI can climb. If you watch the things kids who are learning language say, you'll see the same kinds of slip-ups that belie the fact that they don't yet understand all the words themselves, but nobody thinks that 2-year-olds aren't people or thinks they will…

Internalising the idea (not 'fact') that 'we're basically LLMs' will only take you to a place of deep sterility, delusion and nihilism.

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#417

Earlier quoted context omitted.

> which is possibly the hand-waviest possible means of estimating what is next to occur The "this time it's gonna be completely unlike anything seen before!" is much more suspect. > fleshing out your position here https://en.wikipedia.org/wiki/Parable_of_the_broken_window The parallels with your theory are unmistakable. Prosperity doesn't come from jobs that are little more than make-work.

You still haven't stepped away from historical induction -- your argument still depends on this time not being radically different than last time. There are good reasons -- presented everywhere, right now -- to suppose that this time is substantively different. Sundar Pichai called the invention of AI the most important thing humanity has worked on -- more important than fire, or the alphabet -- and I share his view.…

Non-productive work is exactly what breaking a window and then fixing it is, as well as doing work that is far better done by machine.

As to distribution of economic fruits, as I mentioned before, replacing labor with machines made the US the most prosperous country in history, along with the richest poor people.

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#418
post #59

Earlier quoted context omitted.

Hired in academia? Sure. Hired in industry. That's the opposite. I've had a friend who had to hide that they had a PhD to be hired...

I guess we are living in two different universes. Any job ad for an ML role or ML adjacent role says Ph.d required or Ph.d preferable. Maybe it is also a matter of location. I am in Germany. For a plain SWE role a Ph.d might be a disadvantage here too, but for anything ML related it is mandatory from what I can see.

I am in France. That was in bio-cryptography, which strongly uses ML.

That was a few years ago, though.

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#419

Earlier quoted context omitted.

“ Seeking an improvement that makes a difference in the shorter term, researchers seek to leverage their human knowledge of the domain, but the only thing that matters in the long run is the leveraging of computation. “ http://www.incompleteideas.net/IncIdeas/BitterLesson.html

See also the GPT-4 technical report, page 37. https://images.app.goo.gl/vRP8368Z17zW2hvC9

Report itself: https://arxiv.org/pdf/2303.08774.pdf

Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?

#420
post #343
post #200

Earlier quoted context omitted.

Someone who uses an LLM as a tool to perform a useful service

With a few exceptions, using an LLM to perform a useful service is something that almost anyone will be able to do. Therefore these jobs will be not pay well.

That seems kind of like saying "using Excel to add numbers is something that almost anyone will be able to do" -- true, but the difficult part is (obviously a vast simplification) determining which numbers to add, under what conditions, and to decide what to do based on the result.
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