Comment on Microsoft seemingly just revealed that OpenAI lost $11.5B last quarter
AnAverageSnoot@lemmy.ca 21 hours ago
AI is funded solely by sunk cost fallacy at this point. I wonder how long it will be before investments start getting pulled back because of a lack of ROI. I can already feel the sentiment towards AI and it getting pushed in everything turning negative amongst consumers recently.
I wouldn’t have a problem if they were actually investing the money in something useful like R&D
Nearly all the investment is in data centers. Their approach for the past 2 years seems to be just throwing more hardware at existing approaches, which is a really great way to burn an absurd amount of money for little to nothing in return
It’s very corporate, isn’t it? “Just keep scaling what we have.”
That being said, a lot of innovation is happening. It’s incredible how my promising papers come out, and get completely passed over by Big Tech AI. The Chinese firms are picking up some at least, but are kinda falling into local maxima too.
AI is funded solely by sunk cost fallacy at this point.
and the us economy an gdp relies solely on ai make of that what you will.
Yeah, Trump will prop it up with tax dollars to prolong the inevitable. That’s the American way.
One of our biggest bookstores contracted with a local artist for some merch. That artist used AI with predictable results. Now everyone involved is getting raked over the coals for it.
No surprise, they just announced a 4th round of layoffs too. 😟
I wonder how long it will be before investments start getting pulled back because of a lack of ROI.
Just wait for the next hot thing to come out
I’d love to see a revisit to META Spaces. Lmao.
Why do you think AI is pushed so hard?
Everyone is aware this has to be useful. Too much money.
How many years did Uber go markiing a loss ? Amazon similarly.
Amazon didn’t make a profit, they didn’t lose 11Billion a quarter
this is not a bad analogy, but you are off by orders of magnitude
more importantly, both Uber and Amazon always had a path to profitability (Amazon specifically was already making tons of money on AWS long before the store front made money). AI has already been shown to not have a path to profitability; whatever little value companies around the world have been able to extract, cannot pay the cost of producing it.
think of it this way:
You produce a little car that can drive 2 people and some bags around, it costs you $1000 to make and you sell it for $3000 which a ton of people can afford… you have a path to profitability
I enter the market with a car that can carry 20 people, plus full on luggage for all and it moves twice as fast… but, in practice, I can only really move 3 people and often take them the wrong way, also the luggage was a complete lie and I can only allow passengers with their purses… also my car cost $50,000 to make so I would have to sell it for $70,000 and nobody would pay that when they could get 20 of your cars for less… also also, I promised the people making some parts of my car that would invest 7 kajillion on their companies somehow.
Which company would succeed? yours or mine?
SSUPII@sopuli.xyz 20 hours ago
Investment is done really to train models for ever more miniscule gains. I feel like the current choices are enough to satisfy who is interested in such services, and what really is lacking is now more hardware dedicated to single user sessions to improve quality of output with the current models.
But I really want to see more development on offline services, as right now it is really done only by hobbyists and only occasionally large companies with a little dripfeed (Facebook Llama, original Deepseek model [latter being pretty much useless as no one has the hardware to run it]).
I remember seeing the Samsung Galaxy Fold 7 presentation and listening to them talking about all the AI features instead of the real phone capabilities. “All of this is offline, right? A powerful smartphone… makes sense to have local models for tasks.” but it later became abundantly clear it was just repackaged always-online Gemini for the entire presentation.
mcv@lemmy.zip 19 hours ago
They’re investing this much because they honestly seem to think they’re on the cusp of super intelligent AGI. They’re not, but they really seem to think they are, and that seems to justify these insane investments.
But all they’re really doing is the same thing as before but even bigger. It’s not going to work. It’s only going to make things even more expensive.
I use Copilot and Claude at work, and while it’s really impressive at what it can do, it’s also really stupid and requires a lot of hand holding. It’s not on the brink of AGI super intelligence. Not even close. Maybe we’ll get there some day, but not before all these companies are bankrupt.
DaTingGoBrrr@lemmy.world 16 hours ago
The dot com bubble 2.0 is on the horizon
merc@sh.itjust.works 14 minutes ago
Comparing the coming crash to the dot com crash is like comparing a rough landing to the various crashes on Sept 11th, 2001.
The dot com crash was mostly isolated in high tech. Because it was lead by the Japanese economy starting to fail, and followed by the Sept 11th attacks, the various combined crashes resulted in the S&P 500 falling by about 50% from its peak to the bottom, but it was already back up to the peak value in 2007, then the global financial crisis hit.
This bubble is much bigger. Some analysts say the AI bubble is 17x the size of the Dot Com bubble, and 4x the size of the 2007/08 real estate bubble. AI stocks were 40% of all US GDP growth in 2025, and 80% of all growth in US stocks.
Nvidia’s stock price has gone up 1700% in just 2 years. OpenAI is planning to go public on a valuation of $1 trillion despite losing vast amounts of money. Just 7 US tech companies make up 36% of the entire US stock market, and they’re all heavily betting on AI.
At least when the dot com bubble popped, it left some useful things behind, like huge amounts of dark fibre. But, the AI processors are so specialized they can’t be used for much of anything else. They also wear out, sometimes within months. The datacenter buildings themselves can maybe be repurposed to being general purpose datacenters, but, a lot of the contents will have to be thrown out.
artyom@piefed.social 18 hours ago
I knew it was a bubble since Computex January 2024 when Derb8uer showed an “AI PC case”. He asked “What’s AI about this PC case?” and they replied that you could put an AI PC inside it.
SSUPII@sopuli.xyz 18 hours ago
You are talking more about the term here being used everywhere out of context.
artyom@piefed.social 18 hours ago
I am talking about companies slapping “AI” on their products and systems and raising their value, in the same way that companies in the 90s slapped “dotcom” on their branding and raised their value.
Taldan@lemmy.world 10 hours ago
That is the exact opposite of my opinion. They’re throwing tons of computing at the current models. It has produced little improvement. The vast majority of investment is in compute hardware, rather than R&D. They need more R&D to improve the underlying models. More hardware isn’t going to get the significant gains we need
ferrule@sh.itjust.works 15 hours ago
The problem is there is little continuous cash flow for on prem personal services. Look at Samsung’s home automation, its nearly all online features and when the internet is out you are SOL.
To have your own Github Copilot in a device the size and power usage of a Raspberry Pi would be amazing. But then they won’t get subscriptions.
humanspiral@lemmy.ca 14 hours ago
There is absolutely massive development on open weight models that can be used offline/privately. Minimax M2, most recent one, has comparable benchmark scores to the private US megatech models at 1/12th the cost, and at higher token throughput. Qwen, GLM, deepseek have comparable models to M2, and have smaller models more easily used on very modest hardware.
Closed megatech datacenter AI strategy is partnership with US government/military for oppressive control of humanity. Spending 12x more per token while empowering big tech/US empire to steal from and oppress you is not worth a small fraction in benchmark/quality improvement.