1 hourI expect that many companies will realize that an LLM is a tool that can help with certain tasks, but cannot fully replace most workers because there is a ton of context in people’s jobs that cannot be condensed into language. Similarly, many companies are now realizing with token-based pricing that frontier LLMs are not cost effective in many applications. You shouldn’t have a natural gas fired data center in Tennessee running a model to proofread your emails. You can have a local model do so MUCH more cheaply. This will leave the speculative data center companies holding the bag on a lot of hardware and capacity that is not actually needed.
Who did not know this already?
The real issue is that nobody seems to care… I mean, the biggest IPO in history just took place, valuing SpaceX (which was in reality a tiny bit of SpaceX, entirely composed of Grok) at almost 2 TRILLION dollars after they showed a 5 BILLION loss in the last quarter
Reality is for suckers I guess
- ColeSloth@discuss.tchncs.deEnglish1 hour
IKR? Was it supposed to be a secret? The game plan is to bleed out the competition, make businesses dependent on AI, and then raise prices sky high.
- XLE@piefed.socialEnglish4 hours
It’s not news that they are losing money, but it is news that they are losing tremendously more money than they were previously losing.
- 🌸𝓯𝓵𝓸𝔀𝓮𝓻🌸@sh.itjust.worksEnglish3 hours
It does weaken the argument that scaling up is the path to profitablity, but of course they’ll just claim more money and scaling is the way to go. If the market remains manic they can get away with it.
- BigMacHole@thelemmy.clubEnglish4 hours
Losing BILLIONS a Year? That sounds like TRILLION Dollar Status!
-Wall Street!
- SoupBrick@pawb.socialEnglish3 hours
“Actually, this is good news, as the amount of money lost shows how much money they have gotten. This means they are very good at getting money.”
All aboard the hype train 🚂. Next stop hypeville. Final destination… Who gives a shit.
- Not_mikey@slrpnk.netEnglish57 minutes
Hate on openai all you want but 4xing your revenue over a year is no small feat.
Not as bad as I thought honestly. Looks like they’re making a profit on inference, it’s just training the models is costing them a shit ton in R&D.
If we hit a plateau and training new models isn’t worth it and they scale back there R&D the business could be profitable. Not enough to justify there absurd evaluation, but not a money pit that some people in this thread would have you believe.
- BassTurd@lemmy.worldEnglish23 minutes
It’s not a small feat, but they also 4x’d their expenses, which made them lose significantly more. Long term as you mentioned, if they could entirely drop their R&D, which they’ll never get to $0, but if they did, they’d still be almost -$2 billion in profit. Business modes can change to help accommodate that at that point theoretically though.
I just don’t see them ever getting there. How many years can you lose $20 billion and stay solvent? They’ll raise prices like everyone, but they may lose customers offsetting the gains made, or even if they get more, operating costs will go up too. With all of the DCs being built, I also don’t see R&D going down anytime soon either.
- Korhaka@sopuli.xyzEnglish4 hours
I always thank the LLM and ask if it wants a cup of tea. Is this my fault?
