This is a most excellent place for technology news and articles.
I’m an AI Engineer, been doing this for a long time. I’ve seen plenty of projects that stagnate, wither and get abandoned. I agree with the top 5 in this article, but I might change the priority sequence.
4 & 2 —>1. IF they even have enough data to train an effective model, most organizations have no clue how to handle the sheer variety, volume, velocity, and veracity of the big data that AI needs. It’s a specialized engineering discipline to handle that (data engineer). Let alone how to deploy and manage the infra that models need—also a specialized discipline has emerged to handle that aspect (ML engineer). Often they sit at the same desk.
1 & 5 —> 2: stakeholders seem to want AI to be a boil-the-ocean solution. They want it to do everything and be awesome at it. What they often don’t realize is that AI can be a really awesome specialist tool, that really sucks on testing scenarios that it hasn’t been trained on. Transfer learning is a thing but that requires fine tuning and additional training. Huge models like LLMs are starting to bridge this somewhat, but at the expense of the really sharp specialization. So without a really clear understanding of what can be done with AI really well, and perhaps more importantly, what problems are a poor fit for AI solutions, of course they’ll be destined to fail.
3 —> 3: This isn’t a problem with just AI. It’s all shiny new tech. Standard Gardner hype cycle stuff. Remember how they were saying we’d have crypto-refrigerators back in 2016?
Not to derail, but may I ask how did you become an AI Engineer? I'm a software dev by trade, but it feels like a hard field to get into even if I start training for the AI part of it, because I'd need the data to practice =(
But it's such a big buzz word I feel like I need to start looking that direction if i want to stay employed.
if I want to stay employed
I think this is a little paranoid. Somebody has to handle the production models - deploying them to servers, maintaining the servers, developing the APIs and front ends that provide access to the models… I don’t think software dev jobs are going anywhere
I think the whole system of venture capital might be garbage. We have bros spending millions of dollars like gif sharing while the oceans boil, our schools rot, and our infrastructure rusts or is sold off. Or, I guess I'm just indicting capitalism more generally. But having a few bros decide what to fund based on gutfeel and powerpoints seems like a particularly malignant form.
You think it might be??
Bro say that shit with some confidence.
Venture capital does not contribute beneficially to society.
Say it with your whole chest and both feet. Cuz it's true.
It's mainly because when everyone saw the "oh shiny" tech at first, they rushed it out as soon as possible with intent to replace people so that they can get away with doing less through AI.
Your average tech hype cycle. New tech comes out, lots of marketing, people try to shove it everywhere, then things settle down and the tech either fills a certain chunk of the market or some niche or it dies.
NFT, Blockchain, dot Com boom, there's always another one
Even within a company. Saw coworkers that were trying to establish themselves as the AI pioneers and were backstabbing others get promotions based on how they could best use the ChatGPT AI.
Backstabbing your fellow coworkers over a chatbot has got to be one of the most pathetic things I've read recently
Capitalism wastes money chasing new shiny tech thing
Yeah, we know. AI's not special.
And I was always taught that capitalism allocates the resources ideally. /s
This isn't unique to AI.
80% of new businesses fail, period.
Inside the first 10 years. We've been fucking around with AI for less than three.
AI has been around much longer than 3 years... LLM is just a new twist.
And for the most part it's still powered by underpaid South Asian manpower lol.
80% of AI projects so far...
When did brute force switch from being an antipattern to the preferred pattern?
Isn't it good that the money is being put back into circulation instead of being hoarded? I'm all in for the wealthy wasting their money.
The problem is the bulk of it is going to Nvidia.
Don’t forget all the fuel burned for electricity to power it!
I’m willing to bet the vast majority of that money is changing hands among tech companies like Intel, AMD, nVidia, AWS, etc. Only a small percentage would go to salaries, etc. and I doubt those rates have changed much…
Kinda, but it’s like feeding a starving child nothing but candy until they die.
¯\_(ツ)_/¯
Most people don't want to pay for AI. So they are building stuff that costs a lot for a market that is not willing to pay for it. It is mostly a gimmick for most people.
And like, it's not even a good gimmick. It's a serious labour issue because the primary intent behind a lot of AI has always been to just phase out workers.
I'm all for ending work through technological advancement and universal income, but this definitely wasn't going to get us that, so....
Well, why would I support something that mostly just threatens people's livelihoods and gives even more power to the 0.1%?
Wasting?
A bunch of rich guy’s money going to other people, enriching some of the recipients, in hopes of making the rich guy even richer? And the point of AI is to eliminate jobs that cost rich people money?
I’m all for more foolish AI failed investments.
I've been reading a book about Elizabeth Holmes and the Theranos scam, and the parallels with Gen AI seem pretty astounding. Gen AI is known to be so buggy the industry even created a euphemistic term so they wouldn't have to call it buggy: Hallucinations.
AI is a ponzi scheme to relieve stupid venture capitalists of their money.
To be fair, a large fraction of software projects fail. AI is probably worse because there's probably little notion of how AI actually applied to the problem so that execution is hampered from the start.
https://www.nbcnews.com/id/wbna27190518
https://www.zdnet.com/article/study-68-percent-of-it-projects-fail/
100%, the remaining 20% grift their way to success
That's great. Like 5% more fails than regular software projects. Why do people see this as validation for AI failing? Lol
The interviews revealed that data scientists sometimes get distracted by the latest developments in AI and implement them in their projects without looking at the value that it will deliver.
At least part of this is due to resume-oriented development.
Is that better or worse than IT and software projects in general? It sounds like it might be better.
From the article - "which is twice the failure rate for non-AI technology-related startups."
As I said in a project call where someone was pumping up AI, this is just the latest bubble ready to pop. Everyone is dumping $$ into AI, a couple decent ones will survive but the bulk is either barely functional or just vaporware.
