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.
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.
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.
“When you’re rich, they let you do it.”
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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.
Attractive. You got some pretty solid specs?
Rue the day I cheaped out on RAM. soldered RAMmmm
Soldered is better! It’s sometimes faster, definitely faster if it happens to be lpddr.
But TBH the only thing that really matters his “how much VRAM do you have,” and Qwen 32B slots in at 24GB, or maybe 16GB if the GPU is totally empty and you tune your quantization carefully. And the cheapest way to that (until 2025) is a used MI60, P40 or 3090.
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.
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.
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.
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.
What makes you think there’s a threshold?
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.
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It is. It’s that plus an important process for living organisms rather than just burning something.
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.
There’s a name for it the phenomenon: the AI effect.
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 endeavors, 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).
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….
im down for arm improvements
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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.
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.
That’s about right. I’ve been using LLMs to automate a lot of cruft work from my dev job daily, it’s like having a knowledgeable intern who sometimes impresses you with their knowledge but need a lot of guidance.
watch out; i learned the hard way in an interview that i do this so much that i can no longer create terraform & ansible playbooks from scratch.
even a basic api call from scratch was difficult to remember and i’m sure i looked like a hack to them since they treated me as such.
In addition, there have been these studies released (not so sure how well established, so take this with a grain of salt) lately, indicating a correlation with increased perceived efficiency/productivity, but also a strongly linked decrease in actual efficiency/productivity, when using LLMs for dev work.
After some initial excitement, I’ve dialed back using them to zero, and my contributions have been on the increase. I think it just feels good to spitball, which translates to heightened sense of excitement while working. But it’s really just much faster and convenient to do the boring stuff with snippets and templates etc, if not as exciting. We’ve been doing pair programming lately with humans, and while that’s slower and less efficient too, seems to contribute towards rise in quality and less problems in code review later, while also providing the spitballing side. In a much better format, I think, too, though I guess that’s subjective.
I mean, interviews have always been hell for me (often with multiple rounds of leetcode) so there’s nothing new there for me lol
Same here but this one was especially painful since it was the closest match with my experience I’ve ever encountered in 20ish years and now I know that they will never give me the time of day again and; based on my experience in silicon valley; may end up on a thier blacklist permanently.
Blacklists are heavily overrated and exaggerated, I’d say there’s no chance you’re on a blacklist. Hell, if you interview with them 3 years later, it’s entirely possible they have no clue who you are and end up hiring you - I’ve had literally that exact scenario happen. Tons of companies allow you to re-apply within 6 months of interviewing, let alone 12 months or longer.
The only way you’d end up on a blacklist is if you accidentally step on the owners dog during the interview or something like that.
Being on the other side of the interviewing table for the last 20ish years and being told that we’re not going to hire people that everyone unanimously loved and we unquestionably needed more times that I want to remember makes me think that blacklists are common.
In all of the cases I’ve experienced in the last decade or so: people who had faang and old silicon on their resumes but couldn’t do basic things like creating an ansible playbook from scratch were either an automatic addition to that list or at least the butt of a joke that pervades the company’s cool aide drinker culture for years afterwards; especially so in recruiting.
Yes they’ll eventually forget and I think it’s proportional to how egregious or how close to home your perceived misrepresentation is to them.
I think I’ve probably only ever been blacklisted once in my entire career, and it’s because I looked up the reviews of a company I applied to and they had some very concerning stuff so I just ghosted them completely and never answered their calls after we had already begun to play a bit of phone tag prior to that trying to arrange an interview.
In my defense, they took a good while to reply to my application and they never sent any emails just phone calls, which it’s like, come on I’m a developer you know I don’t want to sit on the phone all day like I’m a sales person or something, send an email to schedule an interview like every other company instead of just spamming phone calls lol
Agreed though, eventually they will forget, it just needs enough time, and maybe you’d not even want to work there.
What happened to Linus? He looks so old now…
He got old.
I guess having 3 kids will do that to you.
That, and developing software for 30+ years.
I told him not to go to that beach.
That’s an excessive amount of aging is what folks are seeing. Not that he’s just old.
He’s lost a lot of weight in 4 years so that’s probably exacerbating the wtf.
He’s 54, I think he looks pretty average for that age. He looks like an old dad, because he is.
he aged
If you find out what happened, let me know, because I think it’s happening to me too.
Wow, yeah that’s a big difference from how I remember him
Oxidative stress is a bitch
Time
The only time I’ve seen AI work well are for things like game development, mainly the upscaling of textures and filling in missing frames of older games so they can run at higher frames without being choppy. Maybe even have applications for getting more voice acting done… If the SAG and Silicon Valley can find an arrangement for that that works out well for both parties…
If not for that I’d say 10% reality was being… incredibly favorable to the tech bros
^^
I am thinking of deploying a RAG system to ingest all of Linus’s emails, commit messages and pull request comments, and we will have a Linus chatbot.
Hold on there Satan… let’s be reasonable here.
I play around with the paid version of chatgpt and I still don’t have any practical use for it. it’s just a toy at this point.
I used chatGPT to help make looking up some syntax on a niche scripting language over the weekend to speed up the time I spent working so I could get back to the weekend.
Then, yesterday, I spent time talking to a colleague who was familiar with the language to find the real syntax because chatGPT just made shit up and doesn’t seem to have been accurate about any of the details I asked about.
Though it did help me realize that this whole time when I thought I was frying things, I was often actually steaming them, so I guess it balances out a bit?
I use shell_gpt with OpenAI api key so that I don’t have to pay a monthly fee for their web interface which is way too expensive. I topped up my account with 5$ back in March and I still haven’t use it up. It is OK for getting info about very well established info where doing a web search would be more exhausting than asking chatgpt. But every time I try something more esoteric it will make up shit, like non existent options for CLI tools
ugh hallucinating commands is such a pain
It’s useful for my firmware development, but it’s a tool like any other. Pros and cons.
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.
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.
Decided to say something popular after his snafu, I see.
Ai bad gets them every time.
Copilot by Microsoft is completely and utterly shit but they’re already putting it into new PCs. Why?
Copilot + Pcs tho…
Linus is known for his generosity.
Linus is a generous man.
Dude…
What?
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.
