> From the perspective of “an average person”, ChatGPT is delivering fantastic products.
It is a honeymoon still, enshittification is coming, who knows how that will look like given how much more expensive to run LLMs backed user experience.
Some back of the envelope calculations:
300 million US users * 20$ a month * 12 months = 72 billion $ a year.
72B$ is some spare change for AI labs. That assuming entire US will be subs which is unlikely and outside of the US there are not many rich countries consuming it, India is the next market, then Brazil and Philippines I think, not super rich counties to say the least. I believe total revenue to just pay for the capex build out by the end 2027 should be on the scale of hundreds of billions a year.
Analysis totally excludes enterprise customer demand and or paid API usage which will only increase as apps integrate this into future knowledge work workflows.
Indeed, that is where the money is. Though enterprise is more focused on efficiently than retail and I'm not sure if they won't drift away from frontier models.
Depends on whether the frontier models can keep on offering better performance. The real efficiency is getting work done faster and better.
Compared to a $100k salary, a few hundred dollars a month is insignificant. If you can make the employee even just a few percent more efficient, it’s worth it.
> If you can make the employee even just a few percent more efficient, it’s worth it.
Are/were you in a position to make such decisions or it is a guess? I'm not but given certain evidence I doubt that few percent will cut it. I know some of the richest companies on the planet from SF Bay Area who won't give lunch for free to their engineers. So I'm not sure about "few percent" :-D 10x we were promised, now that is more interesting but we all know that 10x engineers is nonsense.
On the other hand enterprises are gearing up to pay for shit like $99/user Agent 365, or paying for huge PTU reservations that go almost completely unused on weekends and holidays.
> Investing in alternatives has led to massive new industry that is improving the economy of those countries that do it
> That's a baseless claim. For example, Germany has invested massively in solar but its electricity prices went up, not down.
> This price of electricity is high because gas, which is still expensive, sets the price of electricity most of the time [1].
1) Am I missing something or the link you provided contradicts your claim? On a chart #2 in the article you can see Germany has only 24% of the times price of electricity set by gas, 24% is not "most of the time", right?
2) Even if that is true, and electricity prices in Germany are set by the price of gas most of the time, it seems like you didn't address the point in a previous message. If the goal is to have lower prices and the goal(outcome) is what really matters not just the process and renewables is the path to get there then why Germany electricity prices rose at the end? And were not all of those because of this ... because of that ... supposed to be a part of that path(plan)? They did the thing, invested in solar, what have they missed and why?
> - Current events show that energy security is dominated by decoupling from fossil fuels. This weakens the US strategically and continues to set it up to be manipulated by exceptionally hostile actors.
Is not Germany an example of the opposite? I mean their decision to shut down nuclear plants while getting dependant on Russian supply of energy sources?
What type of roles "AI employees" play, can it be any position in your company or you limit it to something specific?
What is your goal, are you trying to find out if fully autonomous bots are more efficiently help to deliver projects than when people drive them or is it something else?
Hmm, what a coincidence both OpenAI and Anthropic suggest to slow down. I think the signal it sends in plain English sounds something like: We burn too much money atm and shit is about to hit the fan with all that compute capacity starting to rapidly come online 2027, we are not seeing enough demand to justify all of those data centers we already agreed to pay for, let's do a damage control and lower expectation of the plebs.
Many of those points assume LLMs will become amazing in many things very quickly like in a quantum leap, it doesn't seem reasonable to assume that imo. We are actually seeing a confirmation of that atm, LLMs's capability of finding zero days are growing across few months/years, and as you can see concerns are raised about that, that feedback will be taken into account. Well, if AI labs start to hide frontier models or/and lobotomize them for external users then we might be in trouble at some point but I'm not sure if that is possible. They are under pressure to release them due to money incentives, lobotomizing while preserving usefulness for customers might be impossible, hiding internally might spill out in different ways such as Hugging Face incident so not sure hiding is possible neither.
Maybe instead of creating cool stuff try to go and solve real problems? It seems to me that we are lacking in that department since all that LLM fuss has started 3 or so years ago.
It is a subset of something of a value to somebody else and enough so that they are willing to pay you for it, a product, a service. Preferably to pay enough to justify your spent time of course, maybe not right away but at least long term. Even better if not purely digital as it seems we have quite enough of those already.
I believe the original point was that we shouldn't be wasting our gifts on creating silly toys but rather going back to basics and finding the real problems, whether that involves software or not.
we need to find real solvable problems. Those you listed are mostly not solvable in society with current governance process. AI got lots of abilities suddenly emerged, and can be applied on solving problems and not silly toys.
Do you actually think a person using an llm is going to start curing diseases and solve the obesity epidemic (in America) in lieu of creating fun personal software projects?? Or as another commenter said solve climate change? Surely you don’t actually believe this right? Am I missing something?
Just tried Gemini 3.8 Flash on these 2 consecutive prompts at gemini.google.com:
1
what is tesla cybercab plan to address legal implications of accident that will happen? who is going to be responsible for them when they happen?
are they covered by tesla insurance or some other insurance? are there any official plan/statements around that?
2
what was the name of the experiment they started in san antonio tx when some cars didn't have a driver? what was the results of it? did they expand the operations? it was much smaller than waymo, is it growing? how it is related to robotaxi?
It is not able to connect the dots that I keep asking about Tesla in 2nd prompt and spit out some unrelated stuff. Really? How it can be that bad? Gemini 3.1 Pro model works fine in this case btw. I thought maybe it is about knowledge cut over date and it doesn't know about those events from 2025 but it seems it has the knowledge up to March 2025. Top 10 in Intelligence on artificialanalysis ladies and gentlemen.
It is a honeymoon still, enshittification is coming, who knows how that will look like given how much more expensive to run LLMs backed user experience. Some back of the envelope calculations: 300 million US users * 20$ a month * 12 months = 72 billion $ a year. 72B$ is some spare change for AI labs. That assuming entire US will be subs which is unlikely and outside of the US there are not many rich countries consuming it, India is the next market, then Brazil and Philippines I think, not super rich counties to say the least. I believe total revenue to just pay for the capex build out by the end 2027 should be on the scale of hundreds of billions a year.
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