Earlier quoted context omitted.
I am confident that Anthropic make revenue from that $20 than the electricity and server costs needed to serve that customer. Claude Code has rate limits for a reason: I expect they are carefully designed to ensure that the average user doesn't end up losing Anthropic money, and that even extreme heavy users don't cause big enough losses for it to be a problem. Everything I've heard makes me believe the margins on in…
I always assumed that with inference being so cheap, my subscription fees were paying for training costs, not inference.
AI adoption and Solow's productivity paradox
361–370 of 783 posts
Re: AI adoption and Solow's productivity paradox
#362Earlier quoted context omitted.
That means the system will collapse in the future. Now from bunch of people some good programmers are made. Rest go into marketing, sales, agile or other not really technical roles. When the initial crowd will be gone there will be no experienced users of AI. Crappy inexperienced developer will make more crap without prior experience and ability to judge the design decisions. Basically no seniors without juniors.
This implies that writing code by hand will remain the best way to create software. The seniors today who have got to senior status by writing code manually will be different than seniors of tomorrow, who got to senior status using AI tools. Maybe people will become more of generalists rather than specialists.
Re: AI adoption and Solow's productivity paradox
#363Earlier quoted context omitted.
When my company first started pushing for devs to use AI, the most senior guy on my team was pretty vocal about coding not being the bottleneck that slowed down work. It was an I/O issue, and maybe a caching issue as well from too many projects going at the same time with no focus… which also makes the I/O issues worse.
Ironically using Ai on records of meetings across an org is amazing. If you can find out what everyone is talking about you can talk to them. Privacy is non existent, every word said and message sent at the office is recorded but the benefits we saw were amazing.
Re: AI adoption and Solow's productivity paradox
#364Earlier quoted context omitted.
No, these people ("managers, engineers" etc.) do just not work in tech & IT but in other fields and they do not read tech news in your country etc. Most people are just "not that deep in there" as most people on HN.
> “Tech news” A guy attached Claude to his socials, groundbreaking tech.
While they were deep in software development in general, no body of them read any of the essential/required daily industrial news (also not that one related to doing software development in sector ABC)
:-)
So no, even people somehow attached to a topic are not necessarily somehow deeper involved.
Re: AI adoption and Solow's productivity paradox
#365Earlier quoted context omitted.
What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.
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Then everyone saves time, which they can spend producing more things which other people will not read and/or not reading the things that other people produce (using llms)?
Productivity through the roof.
Re: AI adoption and Solow's productivity paradox
#366Earlier quoted context omitted.
None of that is inherent to socialism. There can be good and bad management, freedom and authoritarianism in any economic system.
Socialist economies larger than kibbutzes could only be created and sustained by totalitarian states. Socialism means collective ownership of means of production . And people won't give up their shops and fields and other means of production to the government voluntarily, at least not en masse. Thus they have to be forced at a gunpoint, and they always were. All the subsequent horror is downstream from that. This is…
Yugoslavia was extremely successful, with economic growth that matched or exceeded most capitalist European economies post-WW2. In some ways it wasn't as free as western societies are today but it definitely wasn't totalitarian, and in many ways it was more free - there's a philosophical question in there about what freedom really is. For example Yugoslavia made abortion a constitutionally protected right in the 70s.
I don't want to debate the nuances of what's better now and what was better then as that's beside the point, which is that the idiosyncrasies of the terrible Soviet economy are not inherent to "socialism", just like the idiosyncrasies of the US economy aren't inherent to capitalism.
Re: AI adoption and Solow's productivity paradox
#367Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected , thanks to Solow's productivity paradox [1]. Which is that information technology similarly (and seemingly shockingly) didn't produce any net economic gains in the 1970's or 1980's despite all the computerization. It wasn't until the mid-to-late 1990's that information technology finally started to show clear benef…
Re: AI adoption and Solow's productivity paradox
#368Earlier quoted context omitted.
Casey Muratori says that every programmer should understand how computers work and if you don't understand how computers work you can't be a good programmer.
I might not be a good programmer but I've been a very productive one. Someone who is good at writing code isn't always good at making money.
Re: AI adoption and Solow's productivity paradox
#369Earlier quoted context omitted.
What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.
The thesis of Bullshit Jobs is almost universally rejected by economists, FYI. There’s not much of value to obtain from the book.
Re: AI adoption and Solow's productivity paradox
#370Once the tools help the AI to get feedback on what its first attempt got right and wrong, then we will see the benefits.
And the models people use en masse - eg. free tier ChatGPT - need to get to some threshold of capability where they’re able to do really well on the tasks they don’t do well enough on today.
There’s a tipping point there where models don’t create more work after they’re used for a task, but we aren’t there yet.