As a fervent AI enthusiast, I disagree.
…I’d say it’s 97% hype and marketing.
It’s crazy how much fud is flying around, and legitimately buries good open research. It’s also crazy what these giant corporations are explicitly saying what they’re going to do, and that anyone buys it. TSMC’s allegedly calling Sam Altman a ‘podcast bro’ is spot on, and I’d add “manipulative vampire” to that.
Talk to any long-time resident of localllama and similar “local” AI communities who actually dig into this stuff, and you’ll find immense skepticism, not the crypto-like AI bros like you find on linkedin, twitter and such and blot everything out.
For real. Being a software engineer with basic knowledge in ML, I’m just sick of companies from every industry being so desperate to cling onto the hype train they’re willing to label anything with AI, even if it has little or nothing to do with it, just to boost their stock value. I would be so uncomfortable being an employee having to do this.
For sure, it seems like 90% of ai startups are nothing more than front end wrappers for a gpt instance.
They’re all built on top of OpenAI which is very unprofitable at the moment. Feels like the whole industry is built on a shaky foundation.
Putting the entire fate of your company in a different company (OpenAI) is not a great business move. I guess the successful AI startups will eventually transition to self-hosted models like Llama, if they survive that long.
Most projects I’ve been in contact with are very aware of that fact. That’s why telemetry is so big right now. Everybody is building datasets in the hopes of fine tuning smaller, cheaper models once they have enough good quality data.
My company is realizing that hosting a model which will be private, cost-effective, and performing better than traditional algorithms is like finding a unicorn. Few months back, the top execs were jumping around GenAI like a bunch of kids. Fortunately, the Sr. research head beat some sense into them.
As someone who was working really hard trying to get my company to be able use some classical ML (with very limited amounts of data), with some knowledge on how AI works, and just generally want to do some cool math stuff at work, being asked incessantly to shove AI into any problem that our execs think are “good sells” and be pressured to think about how we can “use AI” was a terrible feel. They now think my work is insufficient and has been tightening the noose on my team.
This. Exactly.
Seriously, I’d love to be enthusiastic about it because it’s genuinely cool what you can do with math.
But the lies that are shoved in our faces are just so fucking much and so fucking egregious that it’s pretty much impossible.
And on top of that LLMs are hugely overshadowing actual interesting approaches for funding.
TSMC are probably making more money than anyone in this goldrush by selling the shovels and picks, so if that’s their opinion, I feel people should listen…
There’s little in the AI business plan other than hurling money at it and hoping job losses ensue.
TSMC doesn’t really have official opinions, they take silicon orders for money and shrug happily. Being neutral is good for business.
Altman’s scheme is just a whole other level of crazy though.
I really want to like AI, I’d love to have an intelligent AI assistant or something, but I just struggle to find any uses for it outside of some really niche cases or for basic brainstorming tasks. Otherwise, it just feels like alot of work for very little benefit or results that I can’t even trust or use.
It’s useful.
I keep Qwen 32B loaded on my desktop pretty much whenever its on, as an (unreliable) assistant to analyze or parse big texts, to do quick chores or write scripts, to bounce ideas off of or even as a offline replacement for google translate (though I specifically use aya 32B for that).
It does “feel” different when the LLM is local, as you can manipulate the prompt syntax so easily, hammer it with multiple requests that come back really fast when it seems to get something wrong, not worry about refusals or data leakage and such.
I receive alerts when people are outside my house, using security cameras, Blue Iris, CodeProject AI, Node-RED and Home Assistant, using a Google Coral for local AI. Entirely local - no cloud services apart from Google’s notification system to get notifications to my phone while I’m not home (which most Android apps use). That’s a good use case for AI since it avoids false positives that occur with regular motion detection.
The saddest part is, this is going to cause yet another AI winter. The first few ones were caused by genuine over-enthusiasm but this one is purely fuelled by greed.
The AI ecosystem is flooded, we need a good bubble pop to slow down the massive waste of resources that our current info-remix-based-on-what-you-will-likely-react-positively-to shit-tier AI represents.
Agreed that’s why it’s so dangerous. These tech bros are going to do damage with their shitty products. It seems like it’s Altman’s goal, honestly.
He wants money/power, and he is getting it. The rest of the AI field will forever be haunted by his greed.
I think we should indict Sam Altman on two sets of charges:
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A set of securities fraud charges.
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8 billion counts of criminal reckless endangerment.
He’s out on podcasts constantly saying the OpenAI is near superintelligent AGI and that there’s a good chance that they won’t be able to control it, and that human survival is at risk. How is gambling with human extinction not a massive act of planetary-scale criminal reckless endangerment?
So either he is putting the entire planet at risk, or he is lying through his teeth about how far along OpenAI is. If he’s telling the truth, he’s endangering us all. If he’s lying, then he’s committing securities fraud in an attempt to defraud shareholders. Either way, he should be in prison. I say we indict him for both simultaneously and let the courts sort it out.
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After getting my head around the basics of the way LLMs work I thought “people rely on this for information?”, the model seems ok for tasks like summarisation though
It’s good for coding if you train it on your own code base. Not great for writing very complex code since the models tend to hallucinate, but it’s great for common patterns, and straightforward questions specific to your code base that can be answered based on existing code (eg “how do I load a user’s most recent order given their email address?”)
the model seems ok for tasks like summarisation though
That and retrieval and the business use cases so far, but even then only if the results can be wrong somewhat frequently.
It’s selling the future, but nobody knows if we can actually get there
It’s selling an anticompetitive dystopia. It’s selling a Facebook monopoly vs selling the Fediverse.
We dont need 7 trillion dollars of datacenters burning the Earth, we need collaborative, open source innovation.
The first part is true … no one cares about the second part of your statement.
TSMC’s allegedly calling Sam Altman a ‘podcast bro’ is spot on, and I’d add “manipulative vampire” to that.
What’s the source for that? It sounds hilarious
When Mr. Altman visited TSMC’s headquarters in Taiwan shortly after he started his fund-raising effort, he told its executives that it would take $7 trillion and many years to build 36 semiconductor plants and additional data centers to fulfill his vision, two people briefed on the conversation said. It was his first visit to one of the multibillion-dollar plants.
TSMC’s executives found the idea so absurd that they took to calling Mr. Altman a “podcasting bro,” one of these people said. Adding just a few more chip-making plants, much less 36, was incredibly risky because of the money involved.
Yep the current iteration is. But should we cross the threshold to full AGI… that’s either gonna be awesome or world ending. Not sure which.
Current LLMs cannot be AGI, no matter how big they are. The fundamental architecture just isn’t right.
You’re absolutely right. LLMs are good at faking language and sometimes not even great at that. Not sure why I got downvoted but oh well. But AGI will be game changing if it happens.
Based on what I’ve witnessed so far, people will play with their AGI units for a bit and then put them down to continue scrolling memes.
Which means it is neither awesome, nor world-ending, but just boring/business as usual.
There are people way smarter than me that claim it will be a threshold and would likely grow exponentially after it’s crossed. I guess we won’t know for sure until it happens. I do agree most people get bored easily but if this thing is possible to think for itself without interaction it won’t matter if the humans get bored.
I know nothing about anything, but I unfoundedly believe we’re still very far away from the computing power required for that. I think we still underestimate the power of biological brains.
Very likely. But 4 years ago I would have said we weren’t close to what these LLMs can do now so who knows.
Ya, it’s like machine learning but better. That’s about it IMO.
Edit: As I have to spell it out: as opposed to (machine learning with) neural networks.
I mean… it is machine learning.
It’s also neural networks, and probably some other CS structures.
AI is a category, and even specific implementations tend to use multiple techniques.
Well there is a very specific architecture “rut” the LLMs people use have fallen into, and even small attempts to break out (like with Jamba) don’t seem to get much interest, unfortunately.
Sure, but LLMs aren’t the only AI being used, nor will they eliminate the other forms of AI. As people see issues with the big LLMs, development focus will change to adopt other approaches.
There is real risk that the hype cycle around LLMs will smother other research in the cradle when the bubble pops.
The hyperscalers are dumping tens of billions of dollars into infrastructure investment every single quarter right now on the promise of LLMs. If LLMs don’t turn into something with a tangible ROI, the term AI will become every bit as radioactive to investors in the future as it is lucrative right now.
Viable paths of research will become much harder to fund if investors get burned because the business model they’re funding right now doesn’t solidify beyond “trust us bro.”
the term AI will become every bit as radioactive to investors in the future as it is lucrative right now.
Well you say that, but somehow crypto is still around despite most schemes being (IMO) a much more explicit scam. We have politicans supporting it.
Sure, but those are largely the big tech companies you’re talking about, and research tends to come from universities and private orgs. That funding hasn’t stopped, it just doesn’t get the headlines like massive investments into LLMs currently do. The market goes in cycles, and once it finds something new and promising, it’ll dump money into it until the next hot thing comes along.
There will be massive market consequences if AI fails to deliver on its promises (and I think it will, because the promises are ridiculous), and we get those every so often. If we look back about 25 years, we saw the same thing w/ the dotcom craze, where anything with a website got obscene amounts of funding, even if they didn’t have a viable business model, and we had a massive crash. But important websites survived that bubble bursting, and the market recovered pretty quickly and within a decade we had yet another massive market correction due to another bubble (the housing market, mostly due to corruption in the financial sector).
That’s how the market goes. I think AI will crash, and I think it’ll likely crash in the next 5 years or so, but the underlying technologies will absolutely be a core part of our day-to-day life in the same way the Internet is after the dotcom burst. It’ll also look quite a bit different IMO than what we’re seeing today, and within 10 years of that crash, we’ll likely be beyond where we were just before the crash, at least in terms of overall market capitalization.
It’s a messy cycle, but it seems to work pretty well in aggregate.
I had a professor in college that said when an AI problem is solved, it is no longer AI.
Computers do all sorts of things today that 30 years ago were the stuff of science fiction. Back then many of those things were considered to be in the realm of AI. Now they’re just tools we use without thinking about them.
I’m sitting here using gesture typing on my phone to enter these words. The computer is analyzing my motions and predicting what words I want to type based on a statistical likelihood of what comes next from the group of possible words that my gesture could be. This would have been the realm of AI once, but now it’s just the keyboard app on my phone.
The approach of LLMs without some sort of symbolic reasoning layer aren’t actually able to hold a model of what their context is and their relationships. They predict the next token, but fall apart when you change the numbers in a problem or add some negation to the prompt.
Awesome for protein research, summarization, speech recognition, speech generation, deep fakes, spam creation, RAG document summary, brainstorming, content classification, etc. I don’t even think we’ve found all the patterns they’d be great at predicting.
There are tons of great uses, but just throwing more data, memory, compute, and power at transformers is likely to hit a wall without new models. All the AGI hype is a bit overblown. That’s not from me that’s Noam Chomsky https://youtu.be/axuGfh4UR9Q?t=9271.
I’ve often thought LLMs could replace all of the C-suites and upper and middle management.
Funny how no companies push that as a possibility.
I almost expect that we’ll see some company reveal it has been letting an AI control the top level decision making for the business itself, including if and when to reveal the AI.
But the funny thing will be that all the executives and board members still have jobs and huge stock awards. They will all pat each other on the back for getting paid more money to do less work, by being bold and taking a risk to let the computer do half their job for them.
Sounds about right. There are some valid and good use cases for “AI”, but the majority is just buzzword marketing.
I have lots of uses for Attack Insects….
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Yup.
I don’t know why. The people marketing it have absolutely no understanding of what they’re selling.
Best part is that I get paid if it works as they expect it to and I get paid if I have to decommission or replace it. I’m not the one developing the AI that they’re wasting money on, they just demanded I use it.
That’s true software engineering folks. Decoupling doesn’t just make it easier to program and reuse, it saves your job when you need to retire something later too.
Their goal isn’t to make AI.
The goal of both the VCs and the startups is to make money. That’s why.
It’s not even to make money, they already do that. They need GROWTH. More money this quarter than last or the stockholders don’t get paid.
Growth doesn’t mean revenue over cost anymore, it just means number go up. The easiest way to create growth from nothing is marketing tulips to venture capital and retail investors.
The people marketing it have absolutely no understanding of what they’re selling.
Has it ever been any different? Like, I’m not in tech, I build signs for a living, and the people selling our signs have no idea what they’re selling.
The worrying part is the implications of what they’re claiming to sell. They’re selling an imagined future in which there exists a class of sapient beings with no legal rights that corporations can freely enslave. How far that is from the reality of the tech doesn’t matter, it’s absolutely horrifying that this is something the ruling class wants enough to invest billions of dollars just for the chance of fantasizing about it.
AI as we know it does have its uses, but I would definitely agree that 90% of it is just marketing hype
The image generation features are fun, even though you have to browbeat the idiot AI into following the description.
You just haven’t tried OpeningAI’s latest orione model. A company employee said it is soooo smart, can you believe it? And the government is like, goddamn we are so scareded of it. Im telling you AGI december 2024, you’ll will see!
Year of the Linux Deskto…oh wait wrong thread, same same though. If we just wait one more year, we’ll have FULL FSD!
Next year, I promise, is the year we all switch to crypto, just wait!
In just two years, no one will be driving 4,000lb cars anymore, everyone just needs a Segway.
We’re going to have “just walk out” grocery stores in two years, where you pick items off the shelf, and
10,000 outsourced Indians will review your purchase and complete your CC transaction in about a half hour.our awesome technology will handle everything, charging you for your groceries as you leave the store, in just two more years!
I make DNNs (deep neural networks), the current trend in artificial intelligence modeling, for a living.
Much of my ancillary work consists of deflating tempering the C-suite’s hype and expectations of what “AI” solutions can solve or completely automate.
DNN algorithms can be powerful tools and muses in scientific, engineering, creativity and innovation. They aren’t full replacements for the power of the human mind.
I can safely say that many, if not most, of my peers in DNN programming and data science are humble in our approach to developing these systems for deployment.
If anything, studying this field has given me an even more profound respect for the billions of years of evolution required to display the power and subtleties of intelligence as we narrowly understand it in an anthropological, neuro-scientific, and/or historical framework(s).
Oh please. Wait until they release double-sided, double-density 128bit AI quantum blockchain that runs on premises/in the cloud edge hybrid.
I feel like they snuck in a little square of reasonable terms with
Best practices Optimization Industry standard Authenticate
But now that I’ve typed it, I’m scared that optimization and authenticate have gross business-speak definitions I just don’t know about yet.
It will have revolutionary rock star synergy
The blue sky, out of the box thinking will disrupt the glass ceiling.
I’m waiting for the part that it gets used for things that are not lazy, manipulative and dishonest. Until then, I’m sitting it out like Linus.
I’m waiting for the part that it gets used for things that are not lazy
Replacing menial or boring tasks is like 90% of what I’m hoping from it.
AI has been used for these things for decades, they are just in the background and not noticed by laypeople
Though the biggest issue is that when people say “AI” today, they mean specifically LLMs, but the world of AI is so much larger than that
This is where I’m at. The push right now has nft pump and dump energy.
The moment someone says ai to me right now I auto disengage. When the dust settles, I’ll look at it seriously.
Just chiming in as another guy who works in AI who agrees with this assessment.
But it’s a little bit worrisome that we all seem to think we’re in the 10%.
it’s a little bit worrisome that we all seem to think we’re in the 10%.
A bit like how when you poll drivers on how good they think they are at driving, the vast majority say they’re better than average lol
That’s possible though, if there are some really bad drivers screwing the average.
Edit: it’s probably even true in this case, it just depends on how you define ‘good’. For example if you define it by getting tickets, only 36% of drivers are issued tickets. The average number of tickets issued is > 0 but the majority of drivers aren’t issued tickets, the average is skewed, because most drivers are at 0.
I don’t know how you’d measure driving “goodness”, but I expect the distribution would be something like exponential (there are billions of non-drivers, and only a few rally/stunt drivers). So the average is likely to be higher than the median.
No AI is a very real thing… just not LLMs, those are pure marketing
And then people will complain about that saying it’s almost all hype and no substance.
Then that one tech bro will keep insisting that lemmy is being unfair to AI and there are so many good use cases.
No one is denying the 10% use cases, we just don’t think it’s special or needs extra attention since those use cases already had other possible algorithmic solutions.
Tech bros need to realize, even if there are some use cases for AI, there has not been any revolution, stop trying to make it happen and enjoy your new slightly better tool in silence.
Hi! It’s me, the guy you discussed this with the other day! The guy that said Lemmy is full of AI wet blankets.
I am 100% with Linus AND would say the 10% good use cases can be transformative.
Since there isn’t any room for nuance on the Internet, my comment seemed to ruffle feathers. There are definitely some folks out there that act like ALL AI is worthless and LLMs specifically have no value. I provided a list of use cases that I use pretty frequently where it can add value. (Then folks started picking it apart with strawmen).
I gotta say though this wave of AI tech feels different. It reminds me of the early days of the web/computing in the late 90s early 2000s. Where it’s fun, exciting, and people are doing all sorts of weird,quirky shit with it, and it’s not even close to perfect. It breaks a lot and has limitations but their is something there. There is a lot of promise.
Like I said else where, it ain’t replacing humans any time soon, we won’t have AGI for decades, and it’s not solving world hunger. That’s all hype bro bullshit. But there is actual value here.
Hi! It’s me, the guy you discussed this with the other day! The guy that said Lemmy is full of AI wet blankets.
Omg you found me in another post. I’m not even mad; I do like how passionate you are about things.
Since there isn’t any room for nuance on the Internet, my comment seemed to ruffle feathers. There are definitely some folks out there that act like ALL AI is worthless and LLMs specifically have no value. I provided a list of use cases that I use pretty frequently where it can add value. (Then folks started picking it apart with strawmen).
What you’re talking about is polarization and yeah, it’s a big issue.
This is a good example, I never did any strawman nor disagree with the fact that it can be useful in some shape or form. I was trying to say its value is much much lower than what people claim to be.
But that’s the issue with polarization, me saying there is much less value can be interpreted as absolute zero, and I apologize for contributing to the polarization.
Just like Furbys
Seems generous, might be more like 5% reality.
I agree with Mr. Torvalds
Yeah, he’s right. AI is mostly used by corps to enshittificate their products for just extra profit
