This is a most excellent place for technology news and articles.
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.
It's a circle jerk, don't get fooled into thinking this is some new version of trickle down economics
you can't spell fail without AI.
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Human creativity for the win!
Thank you for using IPA instead of other cheap beers.
I saw a dell bill board the other day saying they put the Ai in ipa and it had a picture of a laptop and a beer
Wait, are they saying that if you remove them (ai) then you're just left with P? That's kinda funny
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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.
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
Your average tech hype cycle. New tech comes out, lots of marketing, people try to shove everywhere, then things settle down and the tech either fills a certain chunk of the market or some noche or it dies.
NFT, Blockchain, dot Com boom, there's always another one
Pareto principal for psyops, by a think tank organization too. Why is this nonsense tractable here?
What "wasting"? It's the only case of trickle-down that almost works.
Capitalism wastes money chasing new shiny tech thing
Yeah, we know. AI's not special.
It might be in the volume and price of projects
And I was always taught that capitalism allocates the resources ideally. /s
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."
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.
True for the consumer side, but I'd be willing to bet that a decent chunk of that money that giant corporations burned funded some serious research on AI that can go on to actually useful science things
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%?
And then on top of that, if they phase workers out without some kind of universal income, how the hell do the corporate overlords expect us to have money to fuel their greed?
Government subsidies!
Why don’t companies get this? If you make something free in the beginning, people will become conditioned that it’s not worth paying for.
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!
Well probably not just Nvidia but the next likely beneficiaries are in the same range (Microsoft etc.)
Kinda, but it’s like feeding a starving child nothing but candy until they die.
¯\_(ツ)_/¯
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…
They typically use internal personnel and being parcimonious about it so you're right about that.
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.
I read bits of a programming book once, can't remember which one.
Halfway through it was revealed that all the code snippets they had were from a project that was abandoned before it was finished, once the people paying for it realised they no longer wanted it and stopped funding them.
I wasn't sure what message to take from the book after that. Like, sure, my code is a load of shit, hodge-podged together at the request of people who don't really know what they want, but at least I've got people out there using it...
Here's a fitting AI generated Porky
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.
My new job even said they are using AI. It usurb every goddamm company shoving AI features on us.
My new job said this aswell. When I got into the position I found out it was actually a machine learning model and they were trying to use it but didn't have the time to create a clean dataset for the learning so it has never worked. This hasn't stopped them from advertising that they are using AI.
Isn't that how innovation has always worked?
I feel like all this AI hate is comparable to any other innovation cycle.
Millions of light fabric and dowels wasted on crack pot "air heads" trying to design first ever flying vehicle
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?
Yeah I mean that's r&d 20% success is pretty strong in a new field.
Yeah. I'd love to see this compared to other R&D success rates.
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.
