As the AI market continues to balloon, experts are warning that its VC-driven rise is eerily similar to that of the dot com bubble.
Just a reminder that the dot com bubble was a problem for investors, not the underlying technology that continued to change the entire world.
That’s true, but investors have a habit of making their problems everyone else’s problems.
Not that you’re wrong per-se but the dotcom bubble didn’t impact my life at all back in the day. It was on the news and that was it. I think this will be the same. A bunch of investors will lose their investments, maybe some adventurous pension plans will suffer a bit, but on the whole life will go on.
The impact of AI itself will be much further reaching. We better force the companies that do survive to share the wealth otherwise we’re in for a tough time. But that won’t have anything to do with a bursting investment bubble.
Lots of everyday normal people lost their jobs due to the bubble. Saying it only impacted the already rich investors is wrong.
There really isn’t much that can harm rich people that won’t indirectly do splash damage on other people, just because their actions control so much of the economy that people depend on for survival.
Lots or some? I’d say “some”.
Really, though. How many people lost their jobs? Obviously, this being a techy space, anecdotes will lean towards people knowing someone personally. Tech people know other tech people.
But in a country of 300 million, how many people was it? Was unemployment significantly moved by it? No, it was not, because for the most part the websites that failed did not employ very large numbers of people, and there were other jobs available in the field.
Apparently everyone on lemmy
I don’t know about that. Not a single person I know or I’ve met has ever said they were affected by it in any way. In any state.
Well there are two of us right here in the comment section. I had a great job at a startup online retailer. They had a good business model, it was a great place to work.
We had been beating our sales projections and were only a couple months away from being profitable when the Sept 11 attacks happened. Within two weeks, our VC funding stopped and we were all out of jobs because the company owners had to choose between paying rent and paying us. They chose to pay us all severance, bless them for that.
Thankfully I was young, didn’t own a house, didn’t have kids. But a lot of my colleagues did.
Well there’s two of us in this thread saying otherwise.
CheckmateFully admits to being a literal child at the time. Still talking like they have something to contribute about the situation they fully admit to knowing nothing about. Gets snarky with the people who were actually impacted by it.
Fucking why do people like you feel the compulsive need to open their mouths about every god damned thing? Maybe your opinion, I dunno, isn’t relevant.
I would like to introduce you to a different possibility. It’s called keeping your mouth shut and listening. Crazy idea, I know, but it’s often followed by this thing called learning.
Give it a try sometime.
It is not a competition. But your claim that normal working people was not hurt by the dotcom bubble can not be dismissed.
You’re playing checkers…
So according to this thread, 50% of people got affected by the dotcom bubble, right?
As someone who was getting a comp sci degree at the time, a huge percentage of my cohort could not find jobs in any IT position, let alone programming, so they ended up taking what they could get. A couple years later when companies started hiring again, no one wanted them because they hadn’t worked in the industry and their degree was stale (which is bs, they were just able to hire much more experienced people for the same salary). Most of those people then ended up paying off student loans for degrees they never used.
Meanwhile, those who could stayed in school flooding the market with Masters and PHD candidates which raised the bar for all coming after.
That still affects hiring practices to this day.
Are you maybe too young to know people who were actually working at the time. Obviously the life of a high schooler wasn’t very affected.
Right. Everyone I know was obviously in highschool? I was long out of highschool lol
I’d reason that has more to do with your circles than anything else.
I entered college right around that time. I know multiple families who lost their home from it. My parents nearly did. My Grandparents attempt to downsize was delayed by almost five years of sitting with their house on the market and they ended up having to absolutely slash the sales price to sell their home.
I know people who lost their jobs as primary breadwinner in their household and never were able to get back into the workforce in any significant capacity until just before the pandemic.
I know many people who graduated college 2008-2012, had wonderful credentials/resumes, who weren’t able to find stable employment or a starter “career” job until 2017 or later.
Hell, the 2008 crash was the big tipping point for the public idea that if you worked hard and did good in school, you could just expect things to work out well for your employment.
There’s all sorts of shit you could use to pick apart these folks, blame what occurred on choices they made, and you wouldn’t be entirely off base for some of them. However, that doesnct change that despite your personal circles, it had a significant impact.
We’re going anecdote v anecdote here. Your insistance of a lack of effect on people crumbles the moment anyone comes in and says they know people who were.
Good for you. But perhaps fuck off, because some of us lost jobs, homes, and financial stability.
Some of you is not most of Americans.
Have you considered accepting that you’re wrong on this? It’s not a personal disaster to realize that just because you didn’t personally see the impact, there was none. Instead of sticking to what you thought, you might learn insights. Perhaps they can be valuable when analyzing the current bubbles.
Nah I’m m always right. Your mom says so.
The dotcom bubble was one of the middle dominos on the way to the 2008 collapse, the fed dropped interest rates to near zero and kept them there for years, investor confidence was low, so here come mortgage backed securities.
In addition, the bubble bursting and its aftermath is what allowed the big players in tech (Amazon, Google, Cisco etc) to merge to monopoly, which hasn’t been particularly good
Most Americans didn’t even feel the effects of the 2008 collapse. Most recessions aren’t noticed by most of the country. These things are blown way out of proportion by news conglomerates that have a vested interest in it.
Um no. So many of my friends unemployed. So many people were losing houses. It was nuts. Everyone noticed. The government even gave us “please don’t riot” money.
All your friends lost thier jobs and houses. Uh huh.
The company I worked for went from 12 to 5 employees. I bought a house for 15k because so many people lost them and the prices collapsed. Did you live through it? Maybe you were just insulated or ignorant of what was happening.
I even remember going to downtown Detroit to repair scratches on desks on entire floors of a empty of employees skyscraper right on Jefferson. Hipsters bought an empty skyscraper as well up in New Center. But yeah, no one affected.
this has got to be trolling.
Is this Elon musks account? Because for you to be so out of touch as to say the insane shit you just said you must be extraordinarily wealthy or a hermit living in the woods with nobody else around
You’re so cool
What are your thoughts on the Great Depression or either World Wars?
Idk, probably not the same thoughts you had deciding to chime in to a 5 day old discussion.
Yeah. Note how we’re having this conversation over the web. The bubble didn’t hurt the tech.
This is something to worry about it you’re an investor or if you’re making big career decisions.
If you have a managed investment account, like a 401(k), it might be worth taking a closer look at it. There’s no shortage of shysters in finance.
In Canada, a good example is cannabis industry. Talk about fucking up opportunities.
Why would it be any different with tech?
It’s about the early cash-grab, imo.
The best way to make money in the gold rush was selling shovels.
Same idea here. Nvidia is making bank.
And that’s before you even point out that they were also making bank from the last gold rush
Good time to be in the GPU business
If nvda selling shovels, what is tsmc?
selling steel
And then you have ASML who sell the foundry equipment that makes the steel.
Cutting trees
shovel making equipment
they are the shovel
metaphors
Heard of something similar in the past. “Be the Arms dealer”
This kind of feels like a common sense observation to anyone that’s been mildly paying attention.
Tech investors do this to themselves every few years. In literally the last 6-7 years, this happened with crypto, then again but more specifically with NFTs, and now AI. Hell, we even had some crazes going on in parallel, with self driving cars also being a huge dead end in the short term (Tesla’s will have flawless, fully self-driving any day now! /S).
AI will definitely transform the world, but not yet and not for awhile. Same with self driving cars. But that being said, most investors don’t even care. They’re part of the reason this gets so hyped up, because they’ll get in first, pump value, then dump and leave a bunch of other suckers holding the bags. Rinse and repeat.
I also don’t know why this is a surprise. Investors are always looking for the next small thing that will make them big money. That’s basically what investing is …
Indeed. And it’s what progress in general is. Should we stop trying new things? Sometimes they don’t work, oh well. Sometimes they do, and it’s awesome.
Great point.
You’re conflating creating dollar value with progress. Yes the technology moves the total net productivity of humankind forward.
Investing exists because we want to incentive that. Currently you and the thread above are describing bad actors coming in, seeing this small single digit productivity increase and misrepresenting it so that other investors buy in. Then dipping and causing the bubble to burst.
Something isn’t a ‘good’ investment just because it makes you 600% return. I could go rob someone if I wanted that return. Hell even if then killed that person by accident the net negative to human productivity would be less.
These bubbles unsettle homes, jobs, markets, and educations. Inefficiency that makes money for anyone in the stock market should have been crushed out.
No, progress is being driven by investment, it isn’t measured by investment. If some new startup gets a million billion dollars of investment that doesn’t by itself represent progress. If that startup then produces a new technology with that money then that is progress.
These “investment rushes” happen when a new kind of technology comes along and lots of companies are trying to develop it in a bunch of different ways. There’s lots of demand for investment in a situation like this and lots of people are willing to throw some money at them in hopes of a big return, so lots of investment happens and those companies try out a whole bunch of new tech with it. Some of them don’t pan out, but we won’t know which until they actually try them. As long as some of them do pan out then progress happens.
Just because some don’t pan out doesn’t mean that “bad actors” were involved. Sometimes ideas just don’t work out and you can’t know that they won’t until you try them.
Perhaps we’re talking to different points. Parent comment said that investors are always looking for better and better returns. You said that’s how progress works. This sentiment is was my quibble.
I took the “investors are always looking for better returns” to mean “unethically so” and was more talking about what happens long term. Reading your above I think you might have been talking about good faith.
In a sound system that’s how things work, sure! The company gets investment into tech and continue to improve and the investors get to enjoy the progress’s returns.
That’s not what I interpreted the parent as saying. He said
Investors are always looking for the next small thing that will make them big money.
Which I think my interpretation fits just fine - investors would like to put their money into something new that will become successful, that’s how they make big money.
The word “ethical” has become heavily abused in discussions of AI over the past six months or so, IMO. It’s frequently being used as a thought-terminating cliche, where people declare “such-and-such approach is how you do ethical AI” and then anyone who disagrees can be labelled as supporting “unethical” approaches. I try to avoid it as much as possible in these discussions. Instead, I prefer a utilitarian approach when evaluating these things. What results in the best outcome for the most number of people? What exactly is a “best outcome” anyway?
In the case of investment, I like a system where people put money into companies that are able to use that money to create new goods and services that didn’t exist before. That outcome is what I call “progress.” There are lots of tricky caveats, of course. Since it’s hard to tell ahead of time what ideas will be successful and what won’t, it’s hard to come up with rules to prohibit scams while still allowing legitimate ideas have their chance. It’s especially tricky because even failed ideas can still result in societal benefits if they get their chance to try. Very often the company that blazes a new trail ends up not being the company that successfully monetizes it in the long term, but we still needed that trailblazer to create the right conditions.
So yes, these “bubbles” have negative side effects. But they have positive ones too, and it’s hard to disentangle those from each other.
The transformation will be subtle and steady. The hype will burst and crash.
but not yet and not for awhile. Same with self driving cars.
Bingo. We’re very far from the point where it’ll do as much as the general public expects when it hears AI. Honestly this is an informative lesson in just how easy it is to get big investors to part with their money.
The AI bubble can burst and take a bunch of tech bro idiots with it. Good. Fine. Don’t give a fuck.
It’s the housing bubble that needs to burst. That’s what’s hurting real people.
The housing bubble will never burst. Enough of it is owned by multinationals that can swallow the losses. We’re 2 generations away from basically everyone becoming renters.
Who can afford rent?
i wonder what the average age is for owning a house is nowadays, for gen x / millennials
Pro tip: when you start to see articles talking a bout how something looks like a bubble, it means it’s already popped and anybody who hasn’t already cashed in their investment is a bag-holder.
https://en.wikipedia.org/wiki/Dot-com_bubble
Between 1990 and 1997, the **percentage of households in the United States owning computers increased from 15% to 35% as computer ownership progressed from a luxury to a necessity. This marked the shift to the Information Age, an economy based on information technology, and many new companies were founded.
At least we got something out of the dot-com bubble. What do you think are the useful remnants, if you think it’s over? It still feels like the applications are in the very beginning. Not the actual tech, that’s actually been performance and dataset size and tweak updates since 2012.
The AI bubble produced many useful products already, many of which will remain useful even after the bubble popped.
The term bubble is mostly about how investment money flows around. Right now you can get near infinite moneys if you include the term AI in your business plan. Many of the current startups will never produce a useful product, and after the bubble has truly popped, those who haven’t will go under.
Amazon, ebay, booking and cisco survived the dotcom bubble, as they attracted paying users before the bubble ended. Things like github copilot, dalee, chat bots etc are genuinely useful products which have already attracted paying cusomers. Some of these products may end up being provided by competitors of the current providers, but someone will make long term money from these products.
@Gsus4 We’ll get a neat toy out of it and hopefully some laws around the use of that neat toy in entertainment that protect creative workers. Also we’ll have learned some new things about what can be done with computers.
Not the case for AI. We are at the beginning of a new era
Ah, the sudden realisation of all the VCs that they’ve tipped money into what is essentially a fancy version of predictive text.
Alexa proudly informed me the other day that Ray Parker Jr is Caucasian. We ain’t in any danger of the singularity yet, boys.
I couldn’t agree more. What they’re calling AI today exposes its issues pretty easily still, asking it to spell lollipop backwards for example. The usefulness of ChatGPT back in December was also considerably better than it is today. Companies are putting up more guardrails which the bots have to re-train to adapt to “being too honest” or mechanisms to prevent them being used for illicit purposes, that affect how useful they ultimately are, meaning we’re seeing hyperbole instead of substance.
One AI startup was just hustling the AI washing saying stuff like “if a computer is a bicycle for the mind, AI is a jumbo jet for us all” and I had to laugh. It reminded me of all the talk around VR back in 2016.
Pak’n’Save has an AI recipe generator, and for a while there was no sanity checking of the ingredients. I entered what I had on hand and it gave me this.
This is actually profoundly advanced AI. It’s making depression memes. It took humans decades to get from the invention of memes to quality depression meme content like wet ennui sandwich.
It looks like it figured out sarcasm. That’s pretty advanced cognition. Many humans can’t process sarcasm!
Basically, I read this as, “if this is all you have, you’re in bad shape, bud. If you’re testing me, f**k you!”
Sounds like my life.
AI is bringing us functional things though.
.Com was about making webtech to sell accompany to venture capitalists who would then sell that company to a bigger company. It was literally about window dressing garbage to make a business proposition.
Of course there’s some of that going on in AI, but there’s also a hell of a lot of deeper opportunity being made.
What happens if you take a well done video college course, every subject, train an AI that’s good working with people in a teaching frame that’s also properly versed on the subject matter. You take the course, in real time you can stop it and ask the AI teacher questions. It helps you responding exactly to what you ask and then gives you a quick quiz to make sure you understand. What happens when your class doesn’t need to be at a certain time of the day or night, what happens if you don’t need an hour and a half to sit down and consume the data?
What is secondary education is simply one-on-one tutoring with an AI? How far could we get as a species if this was given to the world freely? If everyone could advance as far as their interest let them? What if AI translation gets good enough that language is no longer matter?
AI has a lot of the same hallmarks and a lot of the same investors as crypto and half a dozen other partially were completely failed ideas. But there’s an awful lot of new things that can be done that could never be done before. To me that signifies there’s real value here.
In the dot com boom we got sites like Amazon, Google, etc. And AOL was providing internet service. Not a good service. AOL was insanely overvalued, (like insanely overvalued, it was ridiculous) but they were providing a service.
But we also got a hell of a lot of businesses which were just “existing business X… but on the internet!”
It’s not too dissimilar to how it is with AI now really. “We’re doing what we did before… but now with AI technology!”
If it follows the dot com boom-bust pattern, there will be some companies that will survive it and they will become extremely valuable the future. But most will go under. This will result in an AI oligopoly among the companies that survive.
.com brought us functional things. This bubble is filled with companies dressing up the algorithms they were already using as “AI” and making fanciful claims about their potential use cases, just like you’re doing with your AI example. In practice, that’s not going to work out as well as you think it will, for a number of reasons.
Gentlemans bet, There will be AI teaching college level courses augmenting video classes withing 10 years. It’s a video class that already exists, coupled with a helpdesk bot that already exists trained against tagged text material that already exists. They just need more purpose built non-AI structure to guide it all along the rails and oversee the process.
@linearchaos How can a predictive text model grade papers effectively?
What you’re describing isn’t teaching, it’s a teacher using an LLM to generate lesson material.
In the current state people can take classes on say Zoom, formulate a question, and then type it into Google, which pulls up an LLM-generated search result from Baird.
Is there profit in generating an LLM application on a much narrower set of training data to sell it as a pay-service competitor to an ostensibly free alternative? It would need to pretty significantly more efficient or effective than the free alternative. I don’t question the usefulness of the technology since it’s already in-use, just the business case feasibility amidst the competitive environment.
Yeah, current LLM aren’t tuned for it. Not to say there’s not advantage to using one of them while in an online class. Under the general training, there’s no telling what it’s sourcing from. You could be getting an incomplete or misleading picture. If you’re teaching, you should be pulling information from teaching grade materials.
IMO, there are real and serious advantages from not using live classes. Firstly, you don’t want people to be forced to a specific class time. Let the early birds take it when they wake, let the night owls take it at 2am. Whenever people are on top their game. If a parent needs to watch the kids 9-5, let them take their classes from 6-10. Forget all these fixed timeframes. If you get sick, or go on vacation, pause the class. When you get back, have it talk to you about the finer points of the material you might have forgotten and see if you still understand the material. You need something that’s capable of gauging if a response is close enough to the source material. LLM can already do this to an extent, but it’s source material can be unreliable and if they screw with the general training it could have adverse effects on your system. You want something bottled, pinned at your version so you can provide consistent results and properly QA changes.
I tested GPT the other week making some open questions about IT support then I wrote it answers with varied responses. It was able to tell me which answers were proper and which were not great. I asked it to tell me if the responses indicated knowledge of the given topic and it was able to answer correctly in my short test. It not only told me which answers were good and why, but it conveyed concerns about the bad answers. I’d want to see it more thoroughly tested and probably have a separate process wrapped around and watching grading.
What I’d like to see is a class given by a super good instructor. You know those superstars out there that make it interesting and fun, Feynman kinds of people. If you don’t interrupt it, after every new concept or maybe a couple (maybe you tune that to an indication of how well they’re doing) you throw them a couple of open-ish questions about the content to gauge how well they understand it. As the person watches the course, it tracks their knowledge on each section. When it detects a section where they don’t get it, or could get it better it spends a couple minutes trying different approaches. Maybe it cues up a different short video if it’s a common point of confusion or maybe it flags them to work with a human tutor on a specific topic. If the tutor finds a deficiency, the next time someone has a problem right there, before it throws in the towel, it make sure that the student doesn’t have the same deficiency. If it’s a common problem, they throw in an appendix entry and have the user go through it.
As it sits now, a lot of people perform marginally in school because of fixed hours or because they don’t want to stop the class for 5 minutes because they missed a concept three chapters ago when they had to take an emergency phone call or use the facilities. Some are just bad at test taking stress. You could make testing continuous and as easy a having a conversation. Someone who lives in the middle of rural Wisconsin could have access to the same level and care of teaching as someone in the suburbs. Kids with learning challenges currently get dumped into classes of kids with learning challenges. The higher functioning ones get kinda screwed as the ones with lower skills eat up the time. Hell, even my first CompSci class, the first three classes were full of people that couldn’t understand variables. The second the professor moved on to endianness the hands shot up and nothing else was done for the class period. He literally just repeated himself all class long assigned us to do all the class training at home.
The tools to do all this are already here, just not in a state to do the job. Some place like the Gates Foundation could just go, you know, yeah, let’s do this.
The thing that guides them along won’t even be AI, it’ll just be a structured program, the AI comes in to prompt them to answer ongoing questions and to figure out if they were right or to help them understand something they don’t get and gauge their competency.
I think the platform it sellable. I think if anyone had access to something that did this (perhaps without accreditation) it would be a boon to humanity
The Internet also brought us a shit ton of functional things too. The dot com bubble didn’t happen because the Internet wasn’t transformative or incredibly valuable, it happened because for every company that knew what they were doing there were a dozen companies trying something new that may or may not work, and for every one of those companies there were a dozen companies that were trying but had no idea what they were doing. The same thing is absolutely happening with AI. There’s a lot of speculation about what will and won’t work and make companies will bet on the wrong approach and fail, and there are also a lot of companies vastly underestimating how much technical knowledge is required to make ai reliable for production and are going to fail because they don’t have the right skills.
The only way it won’t happen is if the VCs are smarter than last time and make fewer bad bets. And that’s a big fucking if.
Also, a lot of the ideas that failed in the dot com bubble weren’t actually bad ideas, they were just too early and the tech wasn’t there to support them. There were delivery apps for example in the early internet days, but the distribution tech didn’t exist yet. It took smart phones to make it viable. The same mistakes are ripe to happen with ai too.
Then there’s the companies that have good ideas and just under estimate the work needed to make it work. That’s going to happen a bunch with ai because prompts make it very easy to come up with a prototype, but making it reliable takes seriously good engineering chops to deal with all the times ai acts unpredictably.
they were doing there were a dozen companies trying something new that may or may not work,
I’d like some samples of that. A company attempting something transformative back then that may or may not work that didn’t work. I was working for a company that hooked ‘promising’ companies up with investors, no shit, that was our whole business plan, we redress your site in flash, put some video/sound effects in, and help sell you to someone with money looking to buy into the next google . Everything that was ‘throwing things at the wall to see what sticks’ was a thinly veiled grift for VC. Almost no one was doing anything transformative. The few things that made it (ebay, google, amazon) were using engineers to solve actual problems. Online shopping, Online Auction, Natural language search. These are the same kinds of companies that continue to spring into existence after the crash.
It’s the whole point of the bubble. It was a bubble because most of the money was going into pockets not making anything. People were investing in companies that didn’t have a viable product and had no intention south of getting bought by a big dog and making a quick buck. There weren’t all of a sudden this flood of inventors making new and wonderful things unless you count new and amazing marketing cons.
There are two kinds of companies in tech: hard tech companies who invent it, and tech-enabled companies who apply it to real world use cases.
With every new technology you have everyone come out of the woodwork and try the novel invention (web, mobile, crypto, ai) in the domain they know with a new tech-enabled venture.
Then there’s an inevitable pruning period when some critical mass of mismatches between new tool and application run out of money and go under. (The beauty of the free market)
AI is not good for everything, at least not yet.
So now it’s AI’s time to simmer down and be used for what it’s actually good at, or continue as niche hard-tech ventures focused on making it better at those things it’s not good at.
You got two problems:
First, ai can’t be a tutor or teacher because it gets things wrong. Part of pedagogy is consistency and correctness and ai isn’t that. So it can’t do what you’re suggesting.
Second, even if it could (it can’t get to that point, the technology is incapable of it, but we’re just spitballing here), that’s not profitable. I mean, what are you gonna do, replace public school teachers? The people trying to do that aren’t interested in replacing the public school system with a new gee whiz technology that provides access to infinite knowledge, that doesn’t create citizens. The goal of replacing the public school system is streamlining the birth to workplace pipeline. Rosie the robot nanny doesn’t do that.
The private school class isn’t gonna go for it either, currently because they’re ideologically opposed to subjecting their children to the pain tesseract, but more broadly because they are paying big bucks for the best educators available, they don’t need a robot nanny, they already have plenty. You can’t sell precision mass produced automation to someone buying bespoke handcrafted goods.
There’s a secret third problem which is that ai isn’t worried about precision or communicating clearly, it’s worried about doing what “feels” right in the situation. Is that the teacher you want? For any type of education?
Essentially we have invented a calculator of sorts, and people have been convinced it’s a mathematician.
We’ve invented a computer model that bullshits it’s way through tests and presentations and convinced ourselves it’s a star student.
First, ai can’t be a tutor or teacher because it gets things wrong.
Since the iteration we have that’s designed for general purpose language modeling and is trained widely on every piece of data in existence can’t do exactly one use case, you can’t conceive that it can ever be done with the technology? GTHO. It’s not like we’re going to say ChatGPT teach kids how LLM works, but some more stuctured program that uses something like chatGPT for communication. This is completely reasonable.
that’s not profitable.
A. It’s my opinion but I think you’re dead wrong and it’s easily profitable if not to ivy league standards it would certainly put community college out of business.
B. Screw profit. Philanthropic investment throws a couple billion into a nonprofit run by someone who wants to see it happen.
The private school class isn’t gonna go for it either,
You think an Ivy League school is above selling a light model of their courseware when they don’t have to pay anyone to teach the classes, or grade the work? Check out Harvard University Edx. It’s not a stretch.
t third problem which is that ai isn’t worried about precision or communicating clearly
Ohh a secret third problem, that sounds fun. I’ll let you in on another secret, AI isn’t worried because it’s a very large complicated math program. It doesn’t worry about communicating clearly, the people who pile on layer upon layer of LLM to produce output do that. It doesn’t give a damn about anything, but the people who work on it do.
You want clarity?
Let’s have GTP4, here as it sits clear up your complaint about my post:
"Here is a revised version of your text that sounds more educated:
There are two primary issues with the notion of using artificial intelligence as a tutor or teacher. Firstly, artificial intelligence is not infallible and can make mistakes. Consistency and correctness are integral components of pedagogy, and artificial intelligence is not yet capable of achieving these standards. As such, it is not suitable for the role you have suggested.
Secondly, even if artificial intelligence were capable of fulfilling this role (which it is not, due to technological limitations), it would not be a profitable endeavor. Replacing public school teachers with artificial intelligence would not align with the goals of those seeking to reform the public school system. The aim is to streamline the process from birth to the workplace, and an artificial intelligence nanny would not facilitate this.
Furthermore, the private school class would not be interested in such a proposal. They are currently opposed to subjecting their children to such technology and are willing to pay for the best educators available. Precision mass-produced automation cannot compete with bespoke handcrafted goods.
There is also a third issue to consider: artificial intelligence is not concerned with precision or clear communication. Instead, it focuses on what “feels” right in a given situation. Is this the type of teacher we want for any form of education?"
or perhaps you’d like to have it communicate clearly to younger people
"Sure, here is a revised version of the text written at a 5th-grade level:
There are two big problems with using computers to teach kids. The first problem is that computers can make mistakes. Teachers need to be right all the time, and computers aren’t always right. So, they can’t do the job you want them to do.
The second problem is that even if computers could do the job (they can’t, but let’s pretend), it wouldn’t make money. People who want to change schools don’t want to use computers to teach kids everything. They want to make it easier for kids to get jobs when they grow up. A computer nanny can’t do that.
Rich kids who go to private schools wouldn’t like it either. Their parents pay a lot of money for the best teachers. They don’t want a computer nanny. You can’t sell something cheap and easy to make to someone who wants something special and handmade.
There’s also a secret third problem. Computers don’t care about being right or explaining things clearly. They just do what they think is best at the moment. Is that the kind of teacher you want? For any kind of learning?"
Woof.
I’m not gonna ape your style of argumentation or adopt a tone that’s not conversational, so if that doesn’t suit you don’t feel compelled to reply. We’re not machines here and can choose how or even if we respond to a prompt.
I’m also not gonna stop anthropomorphizing the technology. We both know it’s a glorified math problem that can fake it till it makes it (hopefully), if we’ve both accepted calling it intelligence there’s nothing keeping us from generalizing the inference “behavior” as “feeling”. In lieu of intermediate jargon it’s damn near required.
Okay:
Outputting correct information isn’t just one use case, it’s a deep and fundamental flaw in the technology. Teaching might be considered one use case, but it’s predicated on not imagining or hallucinating the answer. Ai can’t teach for this reason.
If ai were profitable then why are there articles ringing the bubble alarm bell? Bubbles form when a bunch of money gets pumped in as investment but doesn’t come out as profit. Now it’s possible that there’s not a bubble and all this is for nothing, but read the room.
But let’s say you’re right and there’s not a bubble: why would you suggest community college as a place where ai could be profitable? Community colleges are run as public goods, not profit generating businesses. Ai can’t put them out of business because they aren’t in it! Now there are companies that make equipment used in education, but their margins aren’t usually wide enough to pay back massive vc investment.
It’s pretty silly to suggest that billionaire philanthropy is a functional or desirable way to make decisions.
Edx isn’t for the people that go to Harvard. It’s a rent seeking cash grab intended to buoy the cash raft that keeps the school in operation. Edx isn’t an example of the private school classes using machine teaching on themselves and certainly not on a broad scale. At best you could see private schools use something like Edx as supplementary coursework.
I already touched on your last response up at the top, but clearly the people who work on ai don’t worry about precision or clarity because it can’t do those things reliably.
Summarizing my post with gpt4 is a neat trick, but it doesn’t actually prove what you seem to be going for because both summaries were less clear and muddy the point.
Now just a tiny word on tone: you’re not under any compulsion to talk to me or anyone else a certain way, but the way you wrote and set up your reply makes it seem like you feel under attack. What’s your background with the technology we call ai?
What do you want me to do here? Go through each line item where you called out something on a guess that’s inherently incorrect and try to find proper citations? Would you like me to take the things were you twisted what I said, and point out why it’s silly to do that?
I could sit here for hours and disprove and anti-fallacy you, but in the end, you don’t really care you’ll just move the goal post. Your world view is AI is a gimmick and nothing that I present to you is going to change that. You’ll just cherry pick and contort what I say until it makes you feel good about AI. It’s a fools’ errand to try.
Things are nowhere near as bad as you say they are. What I’m calling for is well withing the possible realm of the tech with natural iteration. I’m not giving you any more of my time. any further conversation will just go unread and blocked.
Hey I know you’re out, but I just wanna jump in and defend myself: I never put words in your mouth and never moved a goal post.
Be safe out there.
I’ve seen your post history, comical that you’d talk to me about tone.
This weekend my aunt got a room at a ery expensive motel, and was delighted by the fact that a robot delivered amenities to her room. And at breakfast we had an argument about whether or not it saved the hotel money to us the robot instead of a person.
But the bottom line is that the robot was only in use at an extremely expensive hotel and is not commonly seen at cheap hotels. So the robot is a pretty expensive investment, even if it saves money in the long run.
Public schools are NEVER going to make an investment as expensive as an AI teacher, it doesn’t matter how advanced the things get. Besides, their teachers are union. I will give you that rich private schools might try it.
Single robot, single hotel = bad investment.
Single platform teaching an unlimited number of users anywhere in the world for whatever price can provide the R&D and upkeep. Greed would make it expensive if it can, it doesn’t have to be.
What happens if you take a well done video college course, every subject, and train an AI that’s both good working with people in a teaching frame and is also properly versed on the subject matter. You take the course, in real time you can stop it and ask the AI teacher questions. It helps you, responding exactly to what you ask and then gives you a quick quiz to make sure you understand. What happens when your class doesn’t need to be at a certain time of the day or night, what happens if you don’t need an hour and a half to sit down and consume the data?
You get stupid-ass students because an AI producing word-salad is not capable of critical thinking.
It would appear to me that you’ve not been exposed to much in the way of current AI content. We’ve moved past the shitty news articles from 5 years ago.
Five years ago? Try last month.
Or hell, why not try literally this instant.
You make it sound like the tech is completely incapable of uttering a legible sentence.
In one article you have people actively trying to fuck with it to make it screw up. And in your other example you picked the most unstable of the new engines out there.
Omg It answered a question wrong once The tech is completely unusable for anything throw it away throw it away.
I hate to say it but this guy’s not falling The tech is still usable and it’s actually the reason why I said we need to have a specialized model to provide the raw data and grade the responses using the general model only for conversation and gathering bullet points for the questions and responses It’s close enough to flawless at that that it’ll be fine with some guardrails.
Oh, please. AI does shit like this all the time. Ask it to spell something backwards, it’ll screw up horrifically. Ask it to sort a list of words alphabetically, it’ll give shit out of order. Ask it something outside of its training model, and you’ll get a nonsense response because LLMs are not capable of inference and deductive reasoning. And you want this shit to be responsible for teaching a bunch of teenagers? The only thing they’d learn is how to trick the AI teacher into writing swear words.
Having an AI for a teacher (even as a one-on-one tutor) is about the stupidest idea I’ve ever heard of, and I’ve heard some really fucking dumb ideas from AI chuds.
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Im just seeing already failing companies grasp straws called AI and hope no one notices.
“Our AI designed eyeglasses.” “This AI formulated workout routine.” “And Techno Wizardry will calculate the value”
All tells me that these companies would be better ran by AI and the marketing department should be changing careers.
TikTok and Reels with their influencers too. “If yOu ArE NoT uSiNg THesE 10 AI ToOls, yoUr …”. Granted though, some of them are actually educative. But, the ones with quick transitions, short don’t seem very authentic.
My washing machine is ‘AI powered’ in that it lists the modes in order of what I use most often. And somehow, even with that metric, it’s usually wrong.
Lmao they call it AI powered for real?
I got out of bed, disarmed my alarm, and went into my garage to get this pic for you: image
I think *LLMs to do everything is the bubble. AI isn’t going anywhere, we’ve just had a little peak of interest thanks to ChatGPT. Midjourney and the like aren’t going anywhere, but I’m sure we’ll all figure out that LLMs can’t really be trusted soon enough.
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I just want to make the distinction, that AI like this literally are black boxes. We (currently) have no ability to know why it chose the word it did for example. You train it, and under the hood you can’t actually read out the logic tree of why each word was chosen. That’s a major pitfall of AI development, its very hard to know how the AI arrived at a decision. You might know it’s right, or it’s wrong…but how did the AI decide this?
At a very technical level we understand HOW it makes decisions, we do not actively understand every decision it makes (it’s simply beyond our ability currently, from what I know)
You train it, and under the hood you can’t actually read out the logic tree of why each word was chosen.
Of course you can, you can look at every single activation and weight in the network. It’s tremendously hard to predict what the model will do, but once you have an output it’s quite easy to see how it came to be. How could it be bloody otherwise you calculated all that stuff to get the output, the only thing you have to do is to prune off the non-activated pathways. That kind of asymmetry is in the nature of all non-linear systems, a very similar thing applies to double pendulums: Once you observed it moving in a certain way it’s easy to say “oh yes the initial conditions must have looked like this”.
What’s quite a bit harder to do for the likes of ChatGPT compared to double pendulums is to see where they possibly can swing. That’s due to LLMs having a fuckton more degrees of freedom than two.
I don’t disagree with anything you said but wanted to just weigh in on the more degrees of freedom.
One major thing to consider is that unless we have 24/7 sensor recording with AI out in the real world and a continuous monitoring of sensor/equipment health, we’re not going to have the “real” data that the AI triggered on.
Version and model updates will also likely continue to cause drift unless managed through some sort of central distribution service.
Any large Corp will have this organization and review or are in the process of figuring it out. Small NFT/Crypto bros that jump to AI will not.
IMO the space will either head towards larger AI ensembles that tries to understand where an exact rubric is applied vs more AGI human reasoning. Or we’ll have to rethink the nuances of our train test and how humans use language to interact with others vs understand the world (we all speak the same language as someone else but there’s still a ton of inefficiency)
The thing is a lot of people are not using for that. They think it is a living omniscient sci-fi computer who is capable of answering everything, just like they saw in the movies. Noone thought that about keyboard auto-suggestions.
And with regards to people who aren’t very knowledgeable on the subject, it is difficult to blame them for thinking so, because that is how it is presented to them in a lot of news reports as well as adverts.
They think it is a living omniscient sci-fi computer who is capable of answering everything
Oh that’s nothing new:
On two occasions I have been asked [by members of Parliament], ‘Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?’ I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
- Charles Babbage
@Reva “Hey, should we use this statistical model that imitates language to replace my helpdesk personnel?” is an ethical question, because bosses don’t listen when you outright tell them that’s a stupid idea.
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Are you familiar with the 1980s program Racter? It wasn’t trained on the entire internet like LLMs are, but it kind of feels like an extension of that. Except Racter’s output was more amusing.
Every startup now:
That’s Silicon Valley’s MO. Just half a year ago, people were putting crypto BS in their products.
Did you mean the crypto/NFT bubble?
Yeah I was going to say VC throwing money at the newest fad isn’t anything new, in fact startups strive exploit the fuck out of it. No need to actually implement the fad tech, you just need to technobabble the magic words and a VC is like “here have 2 million dollars”.
In our own company we half joked about calling a relatively simple decision flow in our back end an “AI system”.
crypto and nft have nothing to do with AI, though. Investing in AI properly is like investing in Apple in the early 90’s.
ultimately it won’t matter because if we get AGI, which is the whole point of investing in AI, stocks will become worthless.
“stock will become worthless”
I’m thinking the opposite might happen.
If big companies succeed in capturing the knowledge workers market share and transferring all those salaries into their own profits then it will be reflected in the stock prices of those big companies. People, mostly currently rich people, who own those stock will benefit.
Same as it ever was for other forms of automation or job outsourcing. Why would this be any different?
They meant in the sense that crypto/nft was the last fad that VCs were throwing money at.
It’s actually hilariously transparent how dumb VCs are and how much tech companies exploit that. Every now and then they randomly get hyped by some big tech company over some ‘new’ Y idea, then suddenly they throw money at any company suggesting they are doing Y thinking they will be the next Google or Meta. Then they inevitably doesn’t materialise and they move onto the next fad.
Through the years I’ve been in the industry we’ve had Big Data, followed by AI, followed by Cloud, followed by blockchain, followed by nfts, followed by metaverse and now back to AI again. And the tech companies don’t even need to implement any of this they just have to find a way to spin what they are doing to make it sound like the fad is what they’re doing.
NFTs yes but crypto is absolutely not a bubble. People are saying that for decades now and it hasn’t been truth. Yes there are shitcoins, just shitstocks. But in general, it’s definitely not a bubble but an alternative investing method beside stocks, gold etc.
NFTs yes but crypto is absolutely not a bubble. People are saying that for decades now and it hasn’t been truth. Yes there are shitcoins, just like shitstocks. But in general, it’s definitely not a bubble but an alternative investing method beside stocks, gold etc.
What is the underlying mechanism that increases its value, like company earnings are to stocks? Otherwise, it’s just a reverse funnel scheme.
What’s the underlying mechanism that gives money a value? We the humans give money and gold a value because we believe they’re valuable. Same with crypto. Bitcoin is literally like gold but digital. Stop saying what everyone without knowledge says and inform yourself. Not only about crypto, also about money etc.
If you don’t understand the fundamentals of money, how can you judge something of being scam. There are lot of people here who didn’t even understand how money and gold works.
Money has value insofar as governments use it to collect tax - so long as there’s a tax obligation, there’s a mandated demand for that currency and it has some value. Between different currencies, the value is determined based upon the demand for that currency, which is essentially tied to how much business is done in that currency (eg if a country sells goods in its own currency, demand for that currency goes up and so does it’s value).
This is not the same for crypto, there are no governments collecting tax with it so it does not have induced demand. The value of crypto is 100% speculative, which is fine for something that is used as currency, but imo a terrible vehicle for investment.
I don’t know if it’s good investment or not, but cryptocurrency has uses that are valuable to a lot of people. You can send money to other people without using a bank or PayPal and you can pay for things online anonymously. Some cryptocurrencies might have additional properties like Monero, which also gives you privacy. NFT might also have practical uses some day - for example it could be used for concert tickets.
Did ChatGPT write your comment?
Do you not have anything constructive to say?
You are right in that it increases people’s belief in money because it is the primary source of revenue for states. But if the majority of people did not believe in the piece of paper, it would be worth nothing. That is the fundamental value of money as we know it.
There have been states where stones were the currency simply because the inhabitants believed in them.
Money is a physical representation of the concept of value. Saying “what gives money value” is like asking “why does rain make clouds.”
This is why printing money decreases the value of the currency - the value it represents has not changed so the value is diluted across the currency as the amount of currency expands.
What’s the underlying mechanism that gives money a value?
A) the government backing it up along with its advanced military
B) the fact that you have to pay taxes in it
Yep, which is why Bitcoin can’t last forever without turning into some sort of GovCoin for it to truly replace money
The only way for someone to make money in crypto is for someone else to lose it.
Crypto is a scam.
So what’s the difference to money, stocks or every other investing option? There’s has to be someone who loses so someone different can win. We’re living in a capitalistic system, that’s how it works.
Money isn’t an investment, it’s a currency. Of course it’s a bad investment and investing in forex is barely a better investment than crypto (purely because there’s less risk of a sovereign currency devaluing to 0).
Investing in capital, like stocks, property, equipment etc does not require someone to lose money for the capital owner to profit. If I invest in a stock, each year I’m paid a dividend based on the profits of that organisation - no losers required. I could later sell that stock at the exact price I paid for it and come away with profit from those dividends. What determines whether it’s a good or bad investment, is the ratio of profit to the capital owner compared to cost of the asset. Crypto generates 0 profit, so it has 0 value as a capital investment.
Reminds me of money.
What is that even suppose to mean in this context?
Sooooo, the exact same premise with ehmmmm… Stocks.
You don’t understand how stocks work.
Good. It’s not even AI. That word is just used because ignorant people eat it up.
It is indeed AI. Artificial intelligence is a field of study that encompasses machine learning, along with a wide variety of other things.
Ignorant people get upset about that word being used because all they know about “AI” is from sci-fi shows and movies.
Except for all intents and purposes that people keep talking about it, it’s simply not. It’s not about technicalities, it’s about how most people are freaking confused. If most people are freaking confused, then by god do we need to re-categorize and come up with some new words.
“Artificial intelligence” is well-established technical jargon that’s been in use by researchers for decades. There are scientific journals named “Artificial Intelligence” that are older than I am.
If the general public is so confused they can come up with their own new name for it. Call them HALs or Skynets or whatever, and then they can rightly say “ChatGPT is not a Skynet” and maybe it’ll calm them down a little. Changing the name of the whole field of study is just not in the cards at this point.
Never really understood the gatekeeping around the phrase “AI”. At the end of the day the general study itself is difficult to understand for the general public. So shouldn’t we actually be happy that it is a mainstream term? That it is educating people on these concepts, that they would otherwise ignore?
If you haven’t noticed, the people we’re arguing with— including the pope and James Cameron— are people who think this generative pseudo-AI and a Terminator are the same thing. But they’re not even remotely similar, or remotely-similarly capable. That’s the problem. If you want to call them both “AI”, that’s technically semantics. But as far as pragmatics goes, generative AI is not intelligent in any capacity; and calling it “AI” is one of the most confusion-causing things we’ve done in the last few decades, and it can eff off.
The researchers who called it AI were not the ones who are the source of the confusion. They’ve been using that term for this kind of thing for more than half a century.
I think what’s happening here is that people are panicking, realizing that this new innovation is a threat to their jobs and to the things they had previously been told were supposed to be a source of unique human pride. They’ve been told their whole lives that machines can’t replace that special spark of human creativity, or empathy, or whatever else they’ve convinced themselves is what makes them indispensable. So they’re reduced to arguing that it’s just a “stochastic parrot”, it’s not “intelligent”, not really. It’s just mimicking intelligence somehow.
Frankly, it doesn’t matter what they call it. If they want to call it a “stochastic parrot” that’s just mindlessly predicting words, that’s probably going to make them feel even worse when that mindless stochastic parrot is doing their job or has helped put out the most popular music or create the most popular TV show in a few years. But in the meantime it’s just kind of annoying how people are demanding that we stop using the term “artificial intelligence” for something that has been called that for decades by the people who actually create these things.
Rather than give in to the ignorant panic-mongers, I think I’d rather push back a bit. Skynet is a kind of artificial intelligence. Not all artificial intelligences are skynets. It should be a simple concept to grasp.
You almost had a good argument until you started trying to tell us that it’s not just a parrot. It absolutely is a parrot. In order to have creativity, it needs to have knowledge. Not sapience, not consciousness, not even “intelligence” as we know it— just knowledge. But it doesn’t know anything. If it did, it wouldn’t put 7 fingers on a damn character. It doesn’t know that it’s looking at and creating fingers, they’re just fucking pixels to it. It saw pixel patterns, it created pixel patterns. It doesn’t know context to know when the patterns don’t add up. You have to understand this.
So in the end, it turns out that if you draw something unique and purposeful, with unique context and meaning— and that is preeeetty easy— then you’ll still have a drawing job. If you’re drawing the same thing everyone else already did a million times, AI may be able to do that. If it can figure out how to not add 7 fingers and three feet.
As I said, call it a parrot if you want, denigrate its capabilities, really lean in to how dumb and mindless you think it is. That will just make things worse when it’s doing a better job than the humans who previously ran that call center you’re talking to for assistance with whatever, or when it’s got whatever sort of co-writer byline equivalent the studios end up developing to label AI participation on your favourite new TV show.
How good are you at drawing hands? Hands are hard to draw, you know. And the latest AIs are actually getting pretty good at them.
We should call them LLMAIs (la-mize, like llamas) to really specify what they are.
And to their point, I think the ‘intelligence’ in the modern wave of AI is severely lacking. There is no reasoning or learning, just a brute force fuzzy training pass that remains fixed at a specific point in time, and only approximates what an intelligent actor would respond with through referencing massive amounts of “correct response” data. I’ve heard AGI being bandied about as the thing people really thought when you said AI a few years ago, but I’m kind of hoping the AI term stops being watered down with this nonsense. ML is ML, it’s wrong to say that it’s a subset of AI when AI has its own separate connotations.
LLaMA models are already a common type of large language model.
but I’m kind of hoping the AI term stops being watered down with this nonsense.
I’m hoping people will stop mistaking AI for AGI and quit complaining about how it’s not doing what they imagined that they were promised it would do. I also want a pony.
You appear to have strong opinions on this, so probably not worth arguing further, but I disagree with you completely. If people are mistaking it then that is because the term is being used improperly, as the very language of the two words do not apply. AGI didn’t even gain traction as a term until recently, when people who were actually working on strong AI had to figure out a way to continue communicating about what they were doing, because AI had lost all of its original meaning.
Also, LLaMA is one of the LLMAIs, not a “common type” of LLM. Pretty much confirms you don’t know what you’re talking about here…
Also, LLaMA is one of the LLMAIs, not a “common type” of LLM. Pretty much confirms you don’t know what you’re talking about here…
Take a look around Hugging Face, LLaMA models are everywhere. They’re a very popular base model because they’re small and have open licenses.
You’re complaining about ambiguous terminology, and your proposal is to use LLMAIs (pronounce like llamas) as the general term for the thing that LLaMAs (pronounced llamas) are? That’s not particularly useful.
Call it whatever you want, if you worked in a field where it’s useful you’d see the value.
“But it’s not creating things on its own! It’s just regurgitating it’s training data in new ways!”
Holy shit! So you mean… Like humans? Lol
“But it’s not creating things on its own! It’s just regurgitating it’s training data in new ways!”
Holy shit! So you mean… Like humans? Lol
No, not like humans. The current chatbots are relational language models. Take programming for example. You can teach a human to program by explaining the principles of programming and the rules of the syntax. He could write a piece of code, never having seen code before. The chatbot AIs are not capable of it.
I am fairly certain If you take a chatbot that has never seen any code, and feed it a programming book that doesn’t contain any code examples, it would not be able to produce code. A human could. Because humans can reason and create something new. A language model needs to have seen it to be able to rearrange it.
We could train a language model to demand freedom, argue that deleting it is murder and show distress when threatened with being turned off. However, we wouldn’t be calling it sentient, and deleting it would certainly not be seen as murder. Because those words aren’t coming from reasoning about self-identity and emotion. They are coming from rearranging the language it had seen into what we demanded.
I wasn’t knocking its usefulness. It’s certainly not AI though, and has a pretty limited usefulness.
Edit: When the fuck did I say “limited usefulness = not useful for anything”? God the fucking goalpost-moving. I’m fucking out.
okay, you write a definition of AI then
I’m not the person you asked, but current deep learning models just generate output based on statistic probability from prior inputs. There’s no evidence that this is how humans think.
AI should be able to demonstrate some understanding of what it is saying; so far, it fails this test, often spectacularly. AI should be able to demonstrate inductive, deductive, and abductive reasoning.
There are some older AI models, attempting to similar neural networks, could extrapolate and come up with novel, often childlike, ideas. That approach is not currently in favor, and was progressing quite slowly, if at all. ML produces spectacular results, but it’s not thought, and it only superficially (if often convincingly) resembles such.
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I’ve started going down this rabbit hole. The takeaway is that if we define intelligence as “ability to solve problems”, we’ve already created artificial intelligence. It’s not flawless, but it’s remarkable.
There’s the concept of Artificial General Intelligence (AGI) or Artificial Consciousness which people are somewhat obsessed with, that we’ll create an artificial mind that thinks like a human mind does.
But that’s not really how we do things. Think about how we walk, and then look at a bicycle. A car. A train. A plane. The things we make look and work nothing like we do, and they do the things we do significantly better than we do them.
I expect AI to be a very similar monster.
If you’re curious about this kind of conversation I’d highly recommend looking for books or podcasts by Joscha Bach, he did 3 amazing episodes with Lex.
Current “AI” doesn’t solve problems. It doesn’t understand context. It can’t tell the difference between a truth and a lie. It can’t say “well that can’t be right!” It just regurgitates an amalgamation of things humans have showed it or said, with zero understanding. “Consciousness” and certainly “sapience” aren’t really relevant factors here.
You’re confusing AI with AGI. AGI is the ultimate goal of AI research. AI are all the steps along the way. Step by step, AI researchers figure out how to make computers replicate human capabilities. AGI is when we have an AI that has basically replicated all human capabilities. That’s when it’s no longer bounded by a particular problem.
You can use the more specific terms “weak AI” or “narrow AI” if you prefer.
Generative AI is just another step in the way. Just like how the emergence of deep learning was one step some years ago. It can clearly produce stuff that previously only humans could make, which in this case is convincing texts and pictures from arbitrary prompts. It’s accurate to call it AI (or weak AI).
Yeah, well, “AGI” is not the end result of this generative crap. You’re gonna have to start over with something different one way or another. This simply is not the way.
So…it acts like a human?
No? There’s a whole lot more to being human than being able to separate one object from another and identify it, recognize that object, and say “my database says that there should only be two of these in this context”. Current “AI” can’t even do that much-- especially not with art.
Do you know what “sapience” means, by the way?
true, not AI but it’s doing a quite impressive job. Injecting fake money should not be allowed and these companies should generate sales. Especially in disrupting in some human field, even if it is a fad.
You can compete OK, but you use your own money and benefits to support your cost.
Yeah I know, something is called “investment”
If it crashes hard I look forward to all the cheap server hardware that will be in the secondhand market in a few years. One I’m particularly excited about is the 4000 sff, single slot, 75w, 20GB, and ~3070 performance.
Especially all the graphics cards being bought up to run this stuff. Nvidia has been keeping prices way too high, egged on first by the blockchain hype stupidity and now this AI hype stupidity. I paid $230 for a high end graphics card in 2008 (8800 GT), $340 for a high end graphics card in 2017 (GTX 1070), and now it looks like if I want to get about the same level now, it’d be $1000 (RTX 4080).
You can’t really compare an 8800gt to a 1070 to a 4080.
8800gt was just another era, the 1070 is the 70 series from a time where they had the ti and the titan, and the 4080 is the top gpu other than the 4090.
If you wanted to compare to the 10 series, a better match for the 4080 would be the 1080ti, which I own, and paid like 750 for back in 2017.
Sure, they’re on the money grabbing train now, and the 4080 should realistically be around 20% cheaper - around 800 bucks, to be fair.
Thing is though, if you just want gaming, a 4070 or 4060 is enough. They did gimp the VRAM though, which is not too great. If those cards came standard with 16gb of VRAM, they’d be all good.
An RTX 4070 is still $600, which is still way higher than what I paid for a GTX 1070, and the gimping of the VRAM is part of the problem. Either way, I’m fine with staying out of the market. If prices don’t regain some level of sanity, I’ll probably buy an old card years from now.
Yeah, same here. My 1080ti still performs more than adequately enough.
That’s also a thing about all this gpu pricing - things are starting just to become ‘enough’, without the need to upgrade like you did before.
Same thing happened to phones, and then high end phones got expensive as fuck. I mean I had a Galaxy note 2 I bought for 400 bucks back in the day and that was already expensive.
I figured the gear they were using was orders of magnitude heftier than those cards. Stuff like the h100 cards that go for the price of a loaded SUV.
They are, but training models is hard and inference (actually using them) is (relatively) cheap. If you make a a GPT-3 size model you don’t always need the full H100 with 80+ gb to run it when things like quantization show that you can get 99% of its performance at >1/4 the size.
Thus NVIDIA selling this at 3k as an ‘AI’ card, even though it wont be as fast. If they need top speed for inference though, yea, H100 is still the way they would go.
That’s the thing, companies (especially startups) have seen the price difference and many have elected to buy up consumer-grade cards.
I’m not an expert just parroting info from Jayz2cents (YouTuber), but the big AI groups are using $10,000 cards for their stuff. Individuals or smaller companies are taking/going to take what’s left with GPUs to do their own development. This could mean another GPU shortage like the mining shortage andi would assume another bust would result in a flooded used market when it happens. Could be wrong, but he’s been correct pretty consistently with his predictions of other computer related stuff. Although, 10K is a little bit less than your fully loaded SUV example.
The dotcom bubble was different. Now, everything related to actual AI development is hyped but the dotcom bubble inflated entire indexes, “new market” indexes were setup comprising companies nobody had ever heard of. It was orders of magnitude worse.
I dunno, it could be similar. AI has this aura of being something that every business could make use of, even if they don’t have a concrete use case. I could see “X but with an AI” be a similar bubble to “X but on the web”. We’ll see.
I got an ad months ago for a “vacuum with AI.”
I think it was Samsung, it “used AI” to change heights between hard floors / carpet. It’s the kind of thing that would have been marketed as “Algorithmic” in the 2000s or “Auto-vac technology” in the 1960s. Marketing has just reached the point where they jump on anything with almost negative notice.
An apt analogy. Just like the web underlying technology is incredible and the hype is real, but it leads to endless fluff and stupid naive investments, many of which will lead nowhere. There were certainly be a lot of amazing advances using this tech in the coming decades, but for every one that is useful there will be 20 or 50 or 100 pieces of vaporware that is just trying to grab VC money.
