Literally was in a presentation at work the other day where they said someone used 2 million tokens and the next person used 1 million and they were so excited by it.
I didn’t get it. I asked went 2 million was better than 1 million. The VP basically said it’s not, just costs us more money.
So why the hell is the presentation acting like it’s a fucking victory?
Because it’s a proxy metric for adoption. Currently you generally want your engineers to be using it as much as you can afford to so that they all learn and improve and adapt existing processes etc
It’s just managers who have long since abandoned retaining any practical knowledge in the field, if they even had any at all, and pushing what their boss wants to hear and what they have all convinced themselves to be true in the world of management and linkedin lunatics, because that’s how you get promoted in management. Because everyone from the top down is all in on AI because those at a high enough level are all chasing a seat at the table of the ownership class holding the keys to the AI kingdom and the stock valuations that come from it.
So if their company or their company’s AI model or AI usage makes them an important client of someone that the stock market has deemed important, or if they think their company is the special chosen one that will figure out the secret to AI productivity that none of the other thousands of companies will, that is all that matters. They know nothing about its actual usage, just that more tokens = more usage and therefore must be good, because more usage means their company stock goes up and it that means a bigger golden parachute.
The problem is that either they are genuinely ignorant of the fact that it is a bubble, or they believe that they will be able to time their exit right. The worst part is that a lot of them will, but all the people and the organizational chaos that the burst of the bubble will create that they are knowingly contributing to, well that’s some other sucker’s problem. And that someone else is everyone, whose power and water bills will go up, whose ram and hard drive prices go up, and whose 401k will tank when the bubble collapses.
But why force adoption? If it’s really good people would adopt it naturally like we do with every other tool. Why for this really expensive one, do we now flip the whole system on its head?
It’s kinda like the push to return to office. It was driven by corps having invested in the “can’t fail (ignoring the last previous crash)” real estate market and buying their offices. If everyone suddenly works from home instead of in the office, then those investments go bad because demand for office space is way down. So they tell people to go back to the office, hoping to return to that “every business needs offices!” status quo and save their investments. Though the demand is false (especially combined with layoffs), so it won’t necessarily cause any new corp to want that office space. If they don’t have the sunk cost, then they don’t need to accept the rest of the fallacy.
With AI, it’s the same but just replace building investment with R&D as well as data centre investment. A lot of the companies really pushing AI are the ones that will profit from people going along with that. They really want to build a dependence amongst users as well as a good reputation for execs so they can get a return on the investment. Then there’s also the True Believers (who think LLMs are brilliant AIs that can solve anything if given the right prompts) and the FOMOs (who don’t know much about it but see the world moving towards it and don’t want to miss it because if it was a real AI, missing it could be a massive mistake). There’s also some people who just don’t have various skills and want the AI agents to fill those gaps (and probably don’t have a very good idea about what the LLMs are actually doing in those gaps).
At this point, I think it’s a mistake to go all in on this tech. LLMs aren’t reliable, and their ability to “perform” is more about their flexibility than being well-suited for any task. They’ll go directly from saying things that seem “insightful” (they have no insight) to making the dumbest “mistake” (a mistake requires intent, which they lack, they just predict tokens). But there’s all kinds of false and true (albeit misguided IMO) demand right now and it’s still in early pricing mode (remember the intent is to make that investment money back).
Oh and there’s also China which has been making more efficient models and open sourcing some of them. If they continue to do this, there’s a decent chance those investments will never give the desired returns, at least not to those who are trying to sell tokens. Or those who depend on those selling tokens, like any hardware companies selling hardware under the assumption that it will then make the money to pay for itself (which I believe both nVidia and AMD have done).
It’s mirroring the dotcom bubble with that last bit because network cable companies started loaning the money to pay for their cables to ISPs, expecting returns that never came.
I don’t favor forced adoption… but your second sentence just isn’t true of individual people. It is ture of the industry in general. But individual people tend to stick with what they know and shy away from new things until something forces them out of that state. Usually it is someone else who tried a new tool and is suddenly able to do things easier or what not. It only takes a few power users to turn the tide. So forcing shouldn’t be needed. Just enabling those power users.
Also, I’ve been noticing more and more APIs are adopting a policy where they get rid of any unused credits that you’ve paid for at the end of the month, creating a ‘use it or lose it’ FOMO mentality.
Because they believe that AI will replace payroll, which is generally a businesses highest expense. The more AI usage, the more likely they can eliminate jobs and give themselves bonuses.
They are excited the way a farmer is excited when his pigs are gorging themselves on grain and getting really, really fat. The farmer is glad to pay for grain because its much cheaper than the money he makes from selling them for meat.
They are giddy because its almost time for payday.
Huh, it’s been an operating expense since, let me check, the dawn of business?
“Investing in” your employees doesn’t make a ton of sense when they could just hop over to the next company after a year, much like loyalty in a company doesn’t make sense. It’s all a business transaction in the end so if you can get a better deal, you should.
The unfulfilled promise of AI is to reduce the expense to a minimum so the few remaining people can accomplish the same work. That’s more of an investment than paying people to work for you until they find a better job ever was. In theory.
To solve the turnover issue, sure. It’s not like the employees had that many other places to go to that could afford to do the same, he could just double or triple everyone’s salary and nobody’s going anywhere. It was a necessary business expense. EXPENSE. He could’ve made more money if he didn’t have to pay it. Similarly to the raw materials, electricity, and every other unavoidable business expense.
It’s also not the same for software engineers, for an example. Too many companies hiring, or at least there used to be until a few years ago. You have to not just pay a lot of money, you also have to have a large bonus 3 or 4 years down the line, often in the form of stock options. Otherwise your engineer making 300k will just take the next job for 400k in half a year to a year.
In normal companies that can’t afford bonuses that are more or less life-changing windfalls, there’s no “investing” in employees. You can pay the market rate for a new grad and they disappear in a year or two to another company that doesn’t take new grads at all but rather poaches employees once they’ve gotten some initial work experience and thus they waste less money than the companies hiring and training juniors and can afford to pay more. The company that doesn’t “invest” in employees, gets more bang for its buck.
He could’ve made more money if he didn’t have to pay it. Similarly to the raw materials, electricity, and every other unavoidable business expense.
Citation needed with data. Because I’d argue pay on the factory is also proportional to quality output. So would they have still made the money with a worse product?
I wonder at what point government will tax AI use by companies similarly to payroll taxes and incomes taxes.
If they pay an AI company $150,000 a month to replace $50,000 in salaries, the government then loses all that income tax from the previous employees as well as the payroll tax on $600k a year.
Uh they’ll just claim the AI is being used in another country then?
There’s really no way to definitively decide the tax jurisdiction of an AI agent.
Good luck figuring this one out without a tax on unrealized gains in companies and good luck figuring that one out for companies if they can just scheme around it by reinvesting all their profit indefinitely.
Oh no! What if they took all their fucking datacenters and their pollution and their buying all RAM and their pulling all electricity out of the grid with them?
Literally was in a presentation at work the other day where they said someone used 2 million tokens and the next person used 1 million and they were so excited by it.
I didn’t get it. I asked went 2 million was better than 1 million. The VP basically said it’s not, just costs us more money.
So why the hell is the presentation acting like it’s a fucking victory?
Because AI use is up! The FUTURE!
Because it’s a proxy metric for adoption. Currently you generally want your engineers to be using it as much as you can afford to so that they all learn and improve and adapt existing processes etc
Which is a stupid mindset.
“Go forth and burn tokens and your performance will be measured on that”
Looks like I’m going to make a for to ask for a for every word in /usr/share/dict/words. Look at all the tokens I burned.
It doesn’t reflect upon business value, performance, or education.
It’s even worse than the disastrous lines of code metric.
Their problem is they have no idea what to expect, so to signal affinity to hype, they just measure tokens.
It’s just managers who have long since abandoned retaining any practical knowledge in the field, if they even had any at all, and pushing what their boss wants to hear and what they have all convinced themselves to be true in the world of management and linkedin lunatics, because that’s how you get promoted in management. Because everyone from the top down is all in on AI because those at a high enough level are all chasing a seat at the table of the ownership class holding the keys to the AI kingdom and the stock valuations that come from it.
So if their company or their company’s AI model or AI usage makes them an important client of someone that the stock market has deemed important, or if they think their company is the special chosen one that will figure out the secret to AI productivity that none of the other thousands of companies will, that is all that matters. They know nothing about its actual usage, just that more tokens = more usage and therefore must be good, because more usage means their company stock goes up and it that means a bigger golden parachute.
The problem is that either they are genuinely ignorant of the fact that it is a bubble, or they believe that they will be able to time their exit right. The worst part is that a lot of them will, but all the people and the organizational chaos that the burst of the bubble will create that they are knowingly contributing to, well that’s some other sucker’s problem. And that someone else is everyone, whose power and water bills will go up, whose ram and hard drive prices go up, and whose 401k will tank when the bubble collapses.
Engineers under such incentives should ask AI how to most easily and speedily consume as many credits as possible, I bet it knows a great way
Only if it’s been trained on discussions about it.
Probably just ask it for the seahorse emoji or something idk
But why force adoption? If it’s really good people would adopt it naturally like we do with every other tool. Why for this really expensive one, do we now flip the whole system on its head?
It’s kinda like the push to return to office. It was driven by corps having invested in the “can’t fail (ignoring the last previous crash)” real estate market and buying their offices. If everyone suddenly works from home instead of in the office, then those investments go bad because demand for office space is way down. So they tell people to go back to the office, hoping to return to that “every business needs offices!” status quo and save their investments. Though the demand is false (especially combined with layoffs), so it won’t necessarily cause any new corp to want that office space. If they don’t have the sunk cost, then they don’t need to accept the rest of the fallacy.
With AI, it’s the same but just replace building investment with R&D as well as data centre investment. A lot of the companies really pushing AI are the ones that will profit from people going along with that. They really want to build a dependence amongst users as well as a good reputation for execs so they can get a return on the investment. Then there’s also the True Believers (who think LLMs are brilliant AIs that can solve anything if given the right prompts) and the FOMOs (who don’t know much about it but see the world moving towards it and don’t want to miss it because if it was a real AI, missing it could be a massive mistake). There’s also some people who just don’t have various skills and want the AI agents to fill those gaps (and probably don’t have a very good idea about what the LLMs are actually doing in those gaps).
At this point, I think it’s a mistake to go all in on this tech. LLMs aren’t reliable, and their ability to “perform” is more about their flexibility than being well-suited for any task. They’ll go directly from saying things that seem “insightful” (they have no insight) to making the dumbest “mistake” (a mistake requires intent, which they lack, they just predict tokens). But there’s all kinds of false and true (albeit misguided IMO) demand right now and it’s still in early pricing mode (remember the intent is to make that investment money back).
Oh and there’s also China which has been making more efficient models and open sourcing some of them. If they continue to do this, there’s a decent chance those investments will never give the desired returns, at least not to those who are trying to sell tokens. Or those who depend on those selling tokens, like any hardware companies selling hardware under the assumption that it will then make the money to pay for itself (which I believe both nVidia and AMD have done).
It’s mirroring the dotcom bubble with that last bit because network cable companies started loaning the money to pay for their cables to ISPs, expecting returns that never came.
I don’t favor forced adoption… but your second sentence just isn’t true of individual people. It is ture of the industry in general. But individual people tend to stick with what they know and shy away from new things until something forces them out of that state. Usually it is someone else who tried a new tool and is suddenly able to do things easier or what not. It only takes a few power users to turn the tide. So forcing shouldn’t be needed. Just enabling those power users.
Also, I’ve been noticing more and more APIs are adopting a policy where they get rid of any unused credits that you’ve paid for at the end of the month, creating a ‘use it or lose it’ FOMO mentality.
All very normal and sane.
Because they believe that AI will replace payroll, which is generally a businesses highest expense. The more AI usage, the more likely they can eliminate jobs and give themselves bonuses.
They are excited the way a farmer is excited when his pigs are gorging themselves on grain and getting really, really fat. The farmer is glad to pay for grain because its much cheaper than the money he makes from selling them for meat.
They are giddy because its almost time for payday.
I can’t wait until AI replaces HR.
This is something that changed in the industry; it was a investment back then.
Huh, it’s been an operating expense since, let me check, the dawn of business?
“Investing in” your employees doesn’t make a ton of sense when they could just hop over to the next company after a year, much like loyalty in a company doesn’t make sense. It’s all a business transaction in the end so if you can get a better deal, you should.
The unfulfilled promise of AI is to reduce the expense to a minimum so the few remaining people can accomplish the same work. That’s more of an investment than paying people to work for you until they find a better job ever was. In theory.
Hi I suggest you crack open a history book and look at why ford didn’t pay his employees in peanuts.
To solve the turnover issue, sure. It’s not like the employees had that many other places to go to that could afford to do the same, he could just double or triple everyone’s salary and nobody’s going anywhere. It was a necessary business expense. EXPENSE. He could’ve made more money if he didn’t have to pay it. Similarly to the raw materials, electricity, and every other unavoidable business expense.
It’s also not the same for software engineers, for an example. Too many companies hiring, or at least there used to be until a few years ago. You have to not just pay a lot of money, you also have to have a large bonus 3 or 4 years down the line, often in the form of stock options. Otherwise your engineer making 300k will just take the next job for 400k in half a year to a year.
In normal companies that can’t afford bonuses that are more or less life-changing windfalls, there’s no “investing” in employees. You can pay the market rate for a new grad and they disappear in a year or two to another company that doesn’t take new grads at all but rather poaches employees once they’ve gotten some initial work experience and thus they waste less money than the companies hiring and training juniors and can afford to pay more. The company that doesn’t “invest” in employees, gets more bang for its buck.
Citation needed with data. Because I’d argue pay on the factory is also proportional to quality output. So would they have still made the money with a worse product?
I wonder at what point government will tax AI use by companies similarly to payroll taxes and incomes taxes.
If they pay an AI company $150,000 a month to replace $50,000 in salaries, the government then loses all that income tax from the previous employees as well as the payroll tax on $600k a year.
Uh they’ll just claim the AI is being used in another country then?
There’s really no way to definitively decide the tax jurisdiction of an AI agent.
Good luck figuring this one out without a tax on unrealized gains in companies and good luck figuring that one out for companies if they can just scheme around it by reinvesting all their profit indefinitely.
A complete ban on AI might be in order.
Just use their primary tax address in the country.
Which country?
You can’t increase taxes on companies. They’ll leave the country.
If they don’t contribute their share to taxes, why would I as a citizen want them?
Do have what they already give.
What, the 0 dollars the billionaire pay?
Too late, already happened. It’s the reason why Ireland is the home for such notable Irish tech companies as Google, MSFT, Amazon, Meta, and others.
Those are American companies
Great sarcasm!
That is sarcasm, right?
Nope
Oh no! What if they took all their fucking datacenters and their pollution and their buying all RAM and their pulling all electricity out of the grid with them?
What on god’s green Earth makes you think they would?
Damn, I wish that was true
Why?
Oh shit, you weren’t sarcastic?
Lol no
At some point capitalism will fail but it will take much longer than we think…