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Comment on Microsoft seemingly just revealed that OpenAI lost $11.5B last quarter

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.

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Taldan@lemmy.world ⁨5⁩ ⁨months⁩ ago

what really is lacking is now more hardware dedicated to single user sessions to improve quality of output with the current models

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

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humanspiral@lemmy.ca ⁨5⁩ ⁨months⁩ ago

more development on offline services

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.

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ferrule@sh.itjust.works ⁨5⁩ ⁨months⁩ 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.

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artyom@piefed.social ⁨5⁩ ⁨months⁩ 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.

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- SSUPII@sopuli.xyz ⁨5⁩ ⁨months⁩ ago
  You are talking more about the term here being used everywhere out of context.
  
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  - artyom@piefed.social ⁨5⁩ ⁨months⁩ 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.
    
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mcv@lemmy.zip ⁨5⁩ ⁨months⁩ 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.

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- DaTingGoBrrr@lemmy.world ⁨5⁩ ⁨months⁩ ago
  The dot com bubble 2.0 is on the horizon
  
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  - merc@sh.itjust.works ⁨5⁩ ⁨months⁩ 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.
    
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    bobo@lemmy.ml ⁨5⁩ ⁨months⁩ ago
    Have you seen any comparisons to the previous AI bubbles and winters?
    
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