There is a third mode that requires combination of greenhouse and lens modes, and I did not see AI that is every remotely good working at that third mode. Unfortunately, many real applications are actually require the third mode, and I suspect this is one of key reasons why adoption of AI is so low.
> These tools came about because the cost of trying things out has dropped to nearly zero.
What an obscenely disconnected and privileged notion. "Nearly zero" still currently equates to thousands of dollars of subscription expense per year that normal, workaday people can't afford.
Not to mention the fact that even at this untenable "introductory" level of expense, you're really burning hundreds of thousands of dollars of tokens to do, what was that again?
"Just let the LLM run wild for a while and see what come out the other end?"
"Generate ten solutions to one targeted problem and throw nine of them away because this garbage technology still can't get it right on even the 9th try?"
No wonder the rich bastards of the world love this stuff so much. It encourages so much wanton, indiscriminate, pointless waste in its users.
> What an obscenely disconnected and privileged notion. "Nearly zero" still currently equates to thousands of dollars of subscription expense per year that normal, workaday people can't afford.
You seem disconnected from the very public pricing tiers? Hate to break it to you buddy but these tools are mainstream for regular consumers. And very few people (outside of enterprise) are paying thousands of dollars per year. Not to mention all the things happening with increasingly capable oss models.
You seem very angry, in a very misdirected way. The fact you can't seem to grasp the reality of what these things are costing the average consumer suggests this misdirection is rather severe. Hope you are able to channel your resentment into a more reasonable set of grievances, or at least, ones more resembling reality. While I am sympathetic to your general notions, the basic inaccuracy makes it extremely hard to take you seriously.
$100/month * 12 months is 1200/year. Yeah, normal working people even in the USA don't have that extra money to spend. And let's be realistic: anyone doing the "greenhouse" method probably has both Anthropic and OpenAI $200/month subscriptions, otherwise, this is going to use up your tokens pretty fast. So $4800/year to have this as a normal practice that you do.
The median household income in the US is $64000/year.
Why start at $100? Why ignore the ~$20/month offerings?
I've run a broad `/goal` on a $20 subscription. Sure it will time out faster than on a $100 one. Just as $100 vs $200. But it can still quite surprisingly achieve "greenhouse" like effects.
Given the credit boosts and other promotions this can at times be extra effective. It is still an amazing capability for a pretty low price point. Some people if they really get going will chain $20 subscriptions together while avoiding the $100. Still relatively affordable.
It just isn't true these tools or even the "greenhouse" method is out of reach. You simply went up to the most expensive consumer model to try to make a point that is belied by something many of us have noticed - the amount of non-coders (people who don't have $4800 a year to spend) iterating on ideas using these tools. Using capabilities that for a long time would have been completely out of their reach.
It's a pretty weak argument to claim something is unaffordable while arbitrarily picking the most expensive version of said thing as your baseline, without any real justification beyond your own sense of "and let's be realistic". Basing this on nothing more than "their tokens/session will run out faster" sounds like the sort of "disconnected and privileged notion" someone who thinks they can only get by with the $200 would say. The glaring nature in which you levied your criticism, coupled now with this sort of logic, is again suggestive of pretty severe misdirection.
Let's assume advances in harnesses, models and efficiency continue to rapidly improve. Let's say we only run on solar power.
The concept of "waste" completely shifts. Like in 1990, I had to decide if dow loading an image was worth it, because it would take 5 minutes or more. Now, it isn't even a remote concern, even though images are clearly "wasting" bandwidth sending a 12mb image to my tiny phone screen.
It is much more interesting to think about the cultural impact of that shift. You can be concerned about the impact of AI on various fronts, but worrying about "waste" is tilting at windmills.
Let's say that Trump was pretty ambivalent about AI until Sam Altman and co informed him that they would have to build a ton of new fossil fuel infrastructure to power the data centers that would be necessary to scale the technology.
Wouldn't you know that, now we're all in on AI, poisoning poor neighborhoods with natural gas turbines, and driving up GHG emissions to do ... Uh, what again?
There is a third mode that requires combination of greenhouse and lens modes, and I did not see AI that is every remotely good working at that third mode. Unfortunately, many real applications are actually require the third mode, and I suspect this is one of key reasons why adoption of AI is so low.
Sometimes you have a goal & clarity about what you want; others you're just exploring.
Just as non-assisted work: an undisciplined mind will wander. But when there's also an assistant, you're prone to having the wandering done for you.
> These tools came about because the cost of trying things out has dropped to nearly zero.
What an obscenely disconnected and privileged notion. "Nearly zero" still currently equates to thousands of dollars of subscription expense per year that normal, workaday people can't afford.
Not to mention the fact that even at this untenable "introductory" level of expense, you're really burning hundreds of thousands of dollars of tokens to do, what was that again?
"Just let the LLM run wild for a while and see what come out the other end?"
"Generate ten solutions to one targeted problem and throw nine of them away because this garbage technology still can't get it right on even the 9th try?"
No wonder the rich bastards of the world love this stuff so much. It encourages so much wanton, indiscriminate, pointless waste in its users.
> What an obscenely disconnected and privileged notion. "Nearly zero" still currently equates to thousands of dollars of subscription expense per year that normal, workaday people can't afford.
You seem disconnected from the very public pricing tiers? Hate to break it to you buddy but these tools are mainstream for regular consumers. And very few people (outside of enterprise) are paying thousands of dollars per year. Not to mention all the things happening with increasingly capable oss models.
You seem very angry, in a very misdirected way. The fact you can't seem to grasp the reality of what these things are costing the average consumer suggests this misdirection is rather severe. Hope you are able to channel your resentment into a more reasonable set of grievances, or at least, ones more resembling reality. While I am sympathetic to your general notions, the basic inaccuracy makes it extremely hard to take you seriously.
$100/month * 12 months is 1200/year. Yeah, normal working people even in the USA don't have that extra money to spend. And let's be realistic: anyone doing the "greenhouse" method probably has both Anthropic and OpenAI $200/month subscriptions, otherwise, this is going to use up your tokens pretty fast. So $4800/year to have this as a normal practice that you do.
The median household income in the US is $64000/year.
Why start at $100? Why ignore the ~$20/month offerings?
I've run a broad `/goal` on a $20 subscription. Sure it will time out faster than on a $100 one. Just as $100 vs $200. But it can still quite surprisingly achieve "greenhouse" like effects.
Given the credit boosts and other promotions this can at times be extra effective. It is still an amazing capability for a pretty low price point. Some people if they really get going will chain $20 subscriptions together while avoiding the $100. Still relatively affordable.
It just isn't true these tools or even the "greenhouse" method is out of reach. You simply went up to the most expensive consumer model to try to make a point that is belied by something many of us have noticed - the amount of non-coders (people who don't have $4800 a year to spend) iterating on ideas using these tools. Using capabilities that for a long time would have been completely out of their reach.
It's a pretty weak argument to claim something is unaffordable while arbitrarily picking the most expensive version of said thing as your baseline, without any real justification beyond your own sense of "and let's be realistic". Basing this on nothing more than "their tokens/session will run out faster" sounds like the sort of "disconnected and privileged notion" someone who thinks they can only get by with the $200 would say. The glaring nature in which you levied your criticism, coupled now with this sort of logic, is again suggestive of pretty severe misdirection.
That's a cable subscription, or a carton of cigarettes, or a couple of bar tabs, or a tank of gas.
Let's assume advances in harnesses, models and efficiency continue to rapidly improve. Let's say we only run on solar power.
The concept of "waste" completely shifts. Like in 1990, I had to decide if dow loading an image was worth it, because it would take 5 minutes or more. Now, it isn't even a remote concern, even though images are clearly "wasting" bandwidth sending a 12mb image to my tiny phone screen.
It is much more interesting to think about the cultural impact of that shift. You can be concerned about the impact of AI on various fronts, but worrying about "waste" is tilting at windmills.
Let's say that Trump was pretty ambivalent about AI until Sam Altman and co informed him that they would have to build a ton of new fossil fuel infrastructure to power the data centers that would be necessary to scale the technology.
Wouldn't you know that, now we're all in on AI, poisoning poor neighborhoods with natural gas turbines, and driving up GHG emissions to do ... Uh, what again?