21–30 of 91 posts
There are so many useless cases such as people bragging about their token consumption that has no product and no value add, or those with OpenClaw doing useless automation that could be a Python script.
I see at least two potential positives in this: - The frontier AI companies have realized they won't be able to count on gaining ground and earning more in the future through sheer moat. They have to start earning right now. - The playing field on the market got a whole lot more even as a result. Now everyone is competing on cost and quality - while there are still a lot of competition. AI suppliers can't easily get…
I don't think you're missing anything, but I am surprised that the forces behind the AI companies did. They do need to start making money, but I don't think anyone has a plan as to how they are going to do this. As for enshittification, that was always on the table for the free tier, it was also going to be the drug deal strategy, were the first hit is free.
The cost of AI is still to high, datacenters aren't being completed, the hardware is to expensive, electricity is to expensive, the technology is good, but requires hand-holding. We're going to see AI being deploy more sparingly and more targeted, so the cost is justified.
Perhaps advanced AI isn't cheaper than humans. Assuming the intelligence of a model continuously improves with scale, the token price of the best model will become increasingly expensive. I know that tokens are currently experiencing rapid price drops, but they will eventually encounter physical limitations.
it's simple, how much dollars you get out for every dollar put into tokens as Jensen said, get ready for $1000 per mil token those for which this price makes sense will push out those for which it doesn't - to lower models or to local models but those who want to run local models need to compete for hardware with the data centers, which have strong scale effects thus will always be able to out price local hardware al…
I see at least two potential positives in this: - The frontier AI companies have realized they won't be able to count on gaining ground and earning more in the future through sheer moat. They have to start earning right now. - The playing field on the market got a whole lot more even as a result. Now everyone is competing on cost and quality - while there are still a lot of competition. AI suppliers can't easily get…
and we are fast approaching limits which will be hard to overcome - electricity, chips
The linked Reddit thread is quite hilarious. Earlier this year my company hired a new CEO and his first company address was solely to tell everyone to use AI or they’d lose their job and become unemployable in general. I knew right there and then that he was a moron. There’s something about American companies where the best and brightest rarely show up in senior management. It seems to be populated by some weird clas…
For the long time this worked oh right: get to know right people, wipe some asses, lick some other, play some golf and be sociopath. But right now it does not cut it anymore. You have to be either smart, skilled or know your business and IT somewhat to now how and to what extent or if at all you can use so called AI in your company. People like you described are out of their league entirely.
Musk. Zuck. Bezos.
All three are buddying up with government officials, all three routinely embarrass themselves when they try to talk shop.
Only difference is they're much more socially awkward and less superficially charming than the stereotype would suggest.
If you're following a bunch of people who are from LLM labs, you're going to be more incentivised to tokenmaxx because it's in the Lab's best interest tonget you to behave that way.
Practically, many companies aren't labs with endless runway. Companies hopefully follow a PnL model. And when you look at things with that lens, many of the times the LLM use case falls apart.
You're seeing a bunch of companies starting to realise that tokenmaxing yields very little ROI.
Even the LLM labs, the guy that spent $1+mil tokens has nothing to show for it in terms of revenue to the company. And you have to keep sinking that much into AI for ... "features".
There are some good use cases for AI. I ended up with a positive ROI on a greenfield project myself, albeit on a small scale.
The way that AI has been making people have totally irrational decisions on executive, pure business and technical standpoints is simply mindblowing. I don't understand how people can't take a step back and see what's actually happening from a macro perspective.
it's simple, how much dollars you get out for every dollar put into tokens as Jensen said, get ready for $1000 per mil token those for which this price makes sense will push out those for which it doesn't - to lower models or to local models but those who want to run local models need to compete for hardware with the data centers, which have strong scale effects thus will always be able to out price local hardware al…
But that will tank literally all AI companies immediately as, sure, some will pay it, but by far most won't. Anthropic will be gone in 1 day, so will OpenAI.