Good.
To be clear, it’ll be 10-30 years before AI displaces all human jobs.
Probably because we’ll all be dead, which also happens to be a solution to climate change.
Eh… “Robin Li says increased accuracy is one of the largest improvements we’ve seen in Artificial Intelligence. “I think over the past 18 months, that problem has pretty much been solved—meaning when you talk to a chatbot, a frontier model-based chatbot, you can basically trust the answer,” the CEO added.”
That’s plain wrong. Even STOA black box chatbots give wrong answer to the simplest of questions sometimes. That’s precisely what NOT being able to trust mean.
How can one believe anything this person is saying?
To trust a computer it has to be correct 100% of the time, because it can’t say “I don’t know”.
AI companies specializing in spreading bullshit all across the internet have a bright future however
If you’re invested in these stocks, make sure you have your stop loss orders in place, 100%.
I imagine the bubble bursting will be quick and deadly.
What are the AI rising stocks?
Set stop loss at 100%, got it 👍
Just to b sure, I’m going to set mine at 200%, to be double sure.
No bubble has deserved to pop as much as AI deserves to
Try Venice Ai, free to use, won’t try to censor your topics. Still just a chat bot though (although I think it does image generation too).
I’m sorry, what about their comment made you think they were asking for reccomendations?
The part where they were saying they don’t like the current AIs they know about. Showing disapproval of the trend.
Censoring topics is the least of the issues with the AI bubble.
No it’s a huge one, because it’s the most likely application of AI, AI site moderation will be the start of AI digital policing a field which risks growing larger and larger until it manifests as actual legal policing.
the housing bubble.
ai is probably close second though.
Blockchain and crypto were worse. „AI” has some actual use even if it’s way overblown.
Creating a specialized neural net to perform a specific function is cool. Slapping GPT into customer support because you like money is horse shit and I hope your company collapses. But yeah you’re right. Blockchain was a solution with basically no problems to fix. Neural nets are a tool that can do a ton of things, but everyone is content to use them as a hammer.
Yes! “AI” defined as only LLMs and the party trick applications is a bubble. AI in general has been around for decades and will only continue to grow.
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AI is a ridiculous broad term these days. Everybody had been slapping the label on anything. It’s kinda like saying “transportation” and it means anything between babies crawling up to wrap drive and teleportation.
Because most of them are AI
It’s just once AI becomes useful (and not magical), we tend to stop calling it AI unless AI gets more VC money.
It’s called the AI effect
Technically speaking how I differentiate it is:
- clever algorithm is a good heuristic
- statistics on steroids is machine learning
- using a transformer model is AI (for now)
The AI buzzword means machine learning. You give it a massive dataset and it identifies correlations.
Regular hand-coded AI is mostly simple state machines.
I’m glad you didn’t say NFTs because my Bored Ape will regain and triple its value any day now!
Bro the GME short squeeze is going to hit any day now. We’re going to be millionaires bro, you just wait
Die almond hands, bro! We’re all gonna make it, bro!!! Trust the code, bro!!!
Yes. But companies bought into AI way more than they bought into crypto though, in many outlandish and stupid ways. And many AI companies sell it in ways they shouldn’t.
As a counterpoint: https://en.wikipedia.org/wiki/Long_Blockchain_Corp.
Truly the hardest and most weird buy-in of crypto that happened.
Oh yeah. Kodak too. Gamestop, right? There were a bunch of others.
I mean, block chain does have some actual uses, definitely more niche than LLMs though.
Crypto has a legitimate value, you can buy drugs with it.
Honestly kinda miss when the drugs I did were illegal. I used to buy weed from this online seller that was really into designer drugs. The amount of time I used to spend on Erowid just to figure out wtf I was about to take.
Blockchain has many valuable uses. A distributed zero trust ledger is useful. Sadly the finance scammers and the digital beanie baby collectors attracted all the marketing money.
The idea has merit, in theory – but in practice, in the vast majority of cases, having a trusted regulator managing the system, who can proactively step in to block or unwind suspicious activity, turns out to be vastly preferable to the “code is law” status quo of most blockchain implementations. Not to mention most potential applications really need a mechanism for transactions to clear in seconds, rather than minutes to days, and it’d be preferable if they didn’t need to boil the oceans dry in the process of doing so.
If I was really reaching, I could maybe imagine a valid use case for say, a hypothetical, federated open source game that needed to have a trusted way for every node to validate the creation and trading of loot and items, that could serve as a layer of protection against cheating nodes duping items, for instance. But that’s insanely niche, and for nearly every other use case a database held by a trusted entity is faster, simpler, safer, more efficient, and easier to manage.
Your second point of trading loot and items got me thinking about my Steam CS:GO skins. Why should I trust a centralized entity like Steam who could at any moment decide to delete all my skins or remove my account for whatever reason with my skins, vs storing those skins in a wallet on a public blockchain for example to keep it’s value and always allow trading? Ofc there will always be a “centralized” smart contract but at least they can’t make changes to it if the smart contract code is audited ,
In that case (as is the case with most games) the near-worst case scenario is that you are no worse off trusting Valve with the management of item data than you would be if it was in a public block chain. Why? Because those items are valueless outside the context of the commercial game they are used in. If Valve shuts down CS:GO tomorrow, owning your skins as a digital asset on a blockchain wouldn’t give you any more protection than the current status quo, because those skins are entirely dependent on the game itself to be used and viewed – it’d be akin to holding stock certificates for a company that’s already gone bankrupt and been liquidated: you have a token proving ownership of something that doesn’t exist anymore.
Sure, there’s the edge case that if your Steam account got nukes from orbit by Gaben himself along with all its purchase and trading history you could still cash out on your skin collection, Conversely, having Valve – which, early VAC-ban wonkiness notwithstanding, has proven itself to be a generally-trustworthy operator of a digital games storefront for a couple decades now – hold the master database means that if your account got hacked and your stuff shifted off the account to others for profit, it’s much easier for Valve support to simply unwind those transactions and return your items to you. Infamously, in the case of blockchain ledgers, reversing a fraudulent transaction often requires forking the blockchain.
And yet, every single company that has ever tried to implement a distributed zero trust ledger into their products and processes has inevitably ditched the idea after releasing that it does not, in fact, provide any useful benefit.
It is exceptionally useful for the auditing of damn near everything in digital space, as long as shared resources and 3rd parties have access to the blockchain … which is probably the major reason corporations and politicians don’t want anything to do with it.
It’d be a lot harder to hide crimes, fraud, grey business dealings, bribery and illegal donations, sanction violations, secret police slush funds, etc, etc if every event in the entire financial system and supply chain was logged and cryptographically verifiable.
EDIT: NOTE I’m not talking about everyones transactions being in a public ledger (bad). Only enhancing the current system between businesses and orgs so it’s exceptionally difficult for any of them to falsify data without the others knowing, as well as having near instant visibility and analytics of the entire market (great for regulators, academics, etc).
A supply-chain wide blockchain could enable individuals to view every raw material that went into every product they consume, down to the location, date — even the exact time in many cases — each was mined, refined, harvested, transported, picked, traded, etc. in a way that no individual corp could hide or falsify dramatically. Each corp and individuals true (embodied energy consumption would be visible to every buyer; developed world politicians and corporations couldn’t simply blame China and other developing countries for their own consumption.
The reason major businesses haven’t bothered using distributed blockchains for auditing is because they fundamentally do not actually help in any way with auditing.
At the end of the day, the blockchain is just a ledger. At some point a person has to enter the information into that ledger.
Now, hear me out here, because this is going to be some totally out there craziness that is going to blow your mind… What happens if that person lies?
Like, you’ve built your huge, complicated system to track every banana you buy from the farm to the grocery store… But what happens if the shipper just sends you a different crate of bananas with the wrong label on them? How does your system solve that? What happens if the company growing your bananas claims to use only ethical practices but in reality their workers are effectively slaves? How does a blockchain help fix that?
The data in a system is only as good as your ability to verify it. Verifying the integrity of the data within systems was largely a solved problem long before distributed blockchains came along, and was rarely if ever the primary avenue for fraud. It’s the human components of these systems where fraud can most easily occur. And distributed blockchains do absolutely nothing to solve that.
Counterpoint, having a currency where every token is tied into its own transaction history might be unpopular with large businesses for other reasons. Like maybe they don’t want to be that transparent or accountable. The FBI have made public statements about how much easier it is to track criminals who used Crypto.
Your opinion seems to contradict reality.
This is a very poorly considered argument. Even if we suppose that everything you’ve said is true, the existence of a second plausible explanation doesn’t invalidate the first. You’ve not actually offered any reason why any of what I said is wrong, you just said “X is possible, therefore Y cannot be true.”
Also, I want to note that this particular digression wasn’t about cryptocurrency at all. The point I was responding to was a claim that blockchains had uses other than as currencies. So you really might want to step back a bit and consider what you think is being discussed here, and what you’re actually trying to say.
I think all the crypto scams, all the shitcoins, NFTs and other blockchain bullshit were much worse. At least AI companies usually don’t require you to give them large sums of money, they’re only after your data and absolutely fuck the environment by wasting absurd amounts of power, but they don’t try to take away your life savings
Maybe real estate?
So, I have clients that are actively using AI on a daily basis and LOVE it. It is however a very narrow subset. Also, I’m pretty sure that a LARGE amount of Dollars are currently being spent on AI generated political articles.
The web didn’t die after the dot com bubble burst. The AI bubble will burst, but a smaller niche of companies will continue to exist.
The dot com crash was because tech companies were massively overvalued and didn’t have a proper business plan or profit. I definitely see some similarities with the AI bubble, especially with the large unprofitable companies like OpenAI. OpenAI isn’t estimated to become profitable until 2029, and there’s a lot of unknowns between now and then (e.g. maybe they’ll be forced to license content they use for training).
YUP
The AI bubble might be the 2020s’ dotcom bubble.
Crossing fingers it bursts soon
Same here. And speaking of bubbles I haven’t seen anything about NFTs in quite a while. I don’t think that bubble burst tho, it just sort of shriveled up and blew away.
Please please please please please please please please
Maybe it’s like the dotcom bubble: there is genuinely useful tech that has recently emerged, but too many companies are trying to jump on the bandwagon.
LLMs do seem genuinely useful to me, but of course they have limitations.
We need to stop viewing it as artificial intelligence. The parts that are worth money are just more advanced versions of machine learning.
Being able to assimilate a few dozen textbooks and pass a bar exam is a neat parlor trick, but it is still just a parlor trick.
Unfortunately probably the biggest thing to come out of it will be the marketing aspect. If they spend enough money to train small models on our wants and likes it will give them tremendous amounts of return.
The key to using it in a financially successful manner is finding problems that fit the bill. Training costs are fairly high, quality content generation is also rather expensive. There are sticky problems around training it from non-free data. Whatever you’re going to use it for either needs to have a significant enough advantage to make the cost of training /data worth it.
I still think we’re eventually going to see education rise. The existing tools for small content generation adobe’s use of it to fill in small areas is leaps and bounds better than the old content aware patches. We’ve been using it for ages for speech recognition and speech generation. From there it’s relatively good at helper roles. Minor application development, copy editing, maybe some VFX generation eventually. Things where you still need a talented individual to oversee it but it can help lessen the workload.
There are lots of places where it’s being used where I think it’s a particularly poor fit. AI help desk chatbots, IVR scenarios, It says brain dead as the original phone trees and flow charts that we’ve been following for decades.
If GPT4o is still not what you would call AI, then what is? You can have conversations with it, the Turing test is completely irrelevant all of the sudden.
I could have full conversations with CleverBot a decade ago, but nobody was calling that AI then or even now. People generally recognized it for what it was - a heuristic model chatbot. These LLMs are just overgrown chatbots that still lack the capability of understanding anything it says to you other than how certain words relate to one another.
I can write a program that just replies “yes” to everything you say and you can have a conversation with that. Is that program AI?
“AI isn’t really AI and no one ever thought that AI was actually AI so it doesn’t matter if we call it AI” is the funniest level of tech bro cope these days.
AI has been the name of the field for 70 years at this point, it isn’t something Sam Altman came up with as a marketing wheeze.
Three dudes in a university somewhere referring to chatbots as AI does not redefine the word, even if they did it 70 years ago. 99.999% of the population has always meant AGI by “AI”. Trying to pretend they were always something different is COPE.
Magic Eightball
It’s a massive text predictor. It doesn’t solve problems, it applies patterns based on correlations it picked up during training. If someone talked about your topic online, it has been trained on those conversations. If a topic has two sides that don’t agree, chat gpt might respond in a way that is biased towards one side or the other and you can easily get it to “switch” to the other side with follow up prompts.
For what would be considered AI, think of the star trek computer or Data. The Star Trek computer could create simulations of warp core behaviour to push frontiers of knowledge or characters smart enough to defeat its own safeties (frankly, the computer was such a deus ex machina kinda thing that it was hard to suspend disbelief at times, like why did they even have humans doing the problem solving with computers that capable?). Data wouldn’t get confused about whether any counties in Africa start with K.
I don’t think the Turing test is an effective means of determining intelligence anyways. It came from a time when a conversational computer was barely thinkable. But I wouldn’t even say chat gpt is there yet, since you can tell if you ask it the right things. It is very useful, don’t get me wrong, like a very powerful search engine. But it’s not intelligent.
What of what you say does not apply to humans? They apply patterns of behavior in response to some input. Picked up by learning them. Including people talking online. They are always biased on some way. Some will acknowledge their bias and change it if you give them context.
GPT can literally create simulations. I have used it to do exactly that, specifically for 2D heat conducting with coupled mass transport and reaction kinetics.
Yeah, it does do some very human-like things, but it’s still missing some important parts.
It’s kinda like using a textbook for problem solving. It’s great at helping you solve instances of problems that have already been solved, but you won’t likely find the next big advancement in that field in a textbook.
Newton realized masses attracted each other, and through experimentation, came up with his laws of classical physics.
Einstein took the idea that the speed of light always seems to be the same despite relative motion to come up with special relativity, then realized that space-time itself was a physical thing that could be interacted with rather than just a medium, plus came up with field equations that were used to predict things like black holes before anyone had any kind of notion that they were real things.
Chat gpt is incapable of things like that. And sure, many humans never do anything like that, some might not even be capable even if they were motivated and had the right supports to try. But many humans do solve problems that they’ve never seen before. There’s big names in academia but so many more that don’t get famous but still push the boundaries of human knowledge, creatively solving problems and answering questions every day.
I wouldn’t be surprised if an LLM is a piece of general AI if or when it comes, but there will be other parts that are currently missing. We don’t even know what consciousness is, let alone if any of our hardware is capable of creating/hosting one.
I listened to a podcast (This American Life, IIRC), where some researchers were talking about their efforts to determine whether or not AI could reason. One test they did was asking it to stack a random set of items (one it wouldn’t have come across in any data set, plank of wood, 12 eggs, a book, a bottle, and a nail. . .probably some other things too) in a stable way. With chat gpt 3, it basically just (as you would expect from a pure text predictor) said to put one object on top of another, no way would it be stable.
However, with gpt 4, it basically said to put the wood down, and place the eggs in a 3 x 4 grid with the book on top (to stop them from rolling away), and then with the bottle on top of that, with the nail (even noting you have to put the head side down because you couldn’t make it stable with the point down). It was certainly something that could work, and it was a novel solution.
Now I’m not saying this proves it can think, but I think this “well it’s just a text predictor” kind of hand-waves away the question. It also begs the question, and based on how often I hear people parroting the same exact arguments against AI thinking, I wonder how much we are simply just “text predictors.”
The sheer size of it and it’s training data makes it hard to really say what it’s doing. Like for an object that it wouldn’t have come across in it’s training data, a) how could they tell it was truly a new thing that had never been discussed anywhere on the internet where the training could have consumed it, and b) that any description provided for it didn’t map it to another object that would behave similarly when stacking.
Stacking things isn’t a novel problem. The internet will have many examples of people talking about stacking (including this one here, eventually). The put the flat part down for the nail could have been a direct quote, even. Putting a plank of wood at the bottom would be pretty common, and even the eggs and book thing has probably been discussed before.
I mean, I can’t dismiss that it isn’t doing something more complex, but examples like that don’t convince me that it is. It is capable of very impressive things, and even if it needs to regurgitate every answer it gives, few problems we want to solve day to day are truly novel, so regurgitating previous discussions plus a massive set of associations means that it can map a pretty large problem space to a large solution space with high accuracy.
I’m having trouble thinking of ways to even determine if it can really problem solve that won’t accidentally map to some similar discussion among nerds that like to go into incredible detail and are willing to speculate in any direction just for the sake of enjoying a thought experiment.
Like even known or suspected unsolvable problems have been discussed to greater levels of detail than I’ve likely considered them, so even asking it to do its best trying to solve the traveling salesman problem in polynomial time would likely impress me because computer science students and alums much smarter than I am have discussed it at length.
Hasn’t the Turing Test been irrelevant for a while now? Even before the new AI boom?
Artificial intelligence is a moving target. Every time a goal gets reached, they just move the goalposts, because “well, obviously this isn’t real intelligence”.
No, it was just suddenly completely irrelevant. The answers of the first chat bot that supposedly “beat” it are a complete joke. And yes, I just wrote exactly the same with the goal getting moved, next it has to invent relativity or it’s not intelligent. Absurd.
Machine learning is AI. I think the term you’re looking for is general artificial intelligence, and no one is claiming LLMs fall under that label.
We’re hitting logarithmic scaling with the model trainings. GPT-5 is going to cost 10x more than GPT-4 to train, but are people going to pay $200 / month for the gpt-5 subscription?
Businesses might pay big money for LLMs to do specific tasks. And if chip makers invest more in NPUs then maybe LLMs will become cheaper to train. But I am just speculating because I don’t have any special knowledge of this area whatsoever.
But it would use less energy afterwards? At least that was claimed with the 4o model for example.
4o is also not really much better than 4, they likely just optimized it among others by reducing the model size. IME the “intelligence” has somewhat degraded over time. Also bigger Model (which in tha past was the deciding factor for better intelligence) needs more energy, and GPT5 will likely be much bigger than 4 unless they somehow make a breakthrough with the training/optimization of the model…
4o is optimization of the model evaluation phase. The loss of intelligence is due to the addition of more and more safeguards and constraints by the use of adjunct models doing fine turning, or just rules that limit whole classes of responses.
Is it necessary to pay more, or is it enough to just pay for more time? If the product is good, it will be used.
And they will ALL deserve it.
Good.
It will probably burst, but that does not man that AI will go away completly.
It will burst because no one is going to pay subscription fee for every AI gizmo every app puts in your phone. The way they make any money now is just funneling more and more vc money in exchange of AGI promise (coming soon)
Same thing happened to the Dot Com bubble. The fundamental technology has valid uses, but we’re in the stage where some people are convinced it can be used for literally anything.
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