Earlier quoted context omitted.
GitHub Copilot is already $10 and I don't even use up the requests every month, it's the most bang for buck LLM service I've used.
Until May
What’s happening in May?
The beginning of scarcity in AI
211–220 of 239 posts
Re: The beginning of scarcity in AI
#212Re: The beginning of scarcity in AI
#213Earlier quoted context omitted.
When you go to the command line and type “Claude”, there is an LLM, and everything else is the harness
I'm having an hard time getting my mind to see this. > Users should re-tune their prompts and harnesses accordingly. I read this in the press release and my mind thought it meant test harness. Then there was a blog post about long running harnesses with a section about testing which lead me to a little more confusion. Yes, the word 'harness' is consistently used in the context as a wrapper around the LLM model not as…
I understood this concept with this simple equation:
Agent = LLM + harness
Re: The beginning of scarcity in AI
#214Earlier quoted context omitted.
Performance per dollar may be more important than performance per watt here, though
A dollar is an entirely fictional unit and trillions of it can be manufactured at no cost, while watts are constrained by the laws of physics, photons/electrons, supply chain of electricity and all that fun stuff in the real world.
>dollar is an entirely fictional unit and trillions of it can be manufactured at no cost
If the abstraction works better for you this way, call them interchangeable units of American and Chinese insolvency. Or incremental forfeiture of domestic ownership.
Re: The beginning of scarcity in AI
#215Re: The beginning of scarcity in AI
#216Earlier quoted context omitted.
Really? Not challenging you, genuinely asking for more details. If that is true, I think AI is counterproductive from the bean counter's standpoint.
Not counterproductive because people aren't just sitting back in the rest of the time while AI does work. They do more work. $3k per head on Claude is nothing if your devs get 2x more work done.
Do they review the code? Because in my experience using Claude Opus 4.6 generates code that would be buggy and the tests would be written agains that buggy code with wrong assumptions that certainly would pass with flying colors.
It is only when you look closed you get to know what the hell has happened!
Re: The beginning of scarcity in AI
#217This isn't the first time they've dealt with scarcity, there's been supply chain scarcity four times since 2000. Post-dotcom boom, CDMA scarcity, HDD/flash scarcity, Pandemic scarcity. The scarcity isn't long-term. Like all manufactured products, they'll ramp up production and flood the market with hardware, people will buy too much, market will drop. Boom and bust. We're also still in the bubble. Eventually markets…
> In 5 years consumer chips and model inference will be so good you won't need a server for SOTA.
Naw man, you crazy. If you tell me that in 5 years, consumer chips will be so good that I can run GPT-5.4-level AI on my phone, I'd find that plausible (I buy cheap phones). If you're telling me that in 5 years we won't need _servers_ because our _phones and/or desktops_ will be powerful enough to run the biggest newest LLMs in existence, I question your judgment, I think that prediction shows a deep uncreativity about how massively compute-hungry SOTA models will get.
The valuable things to do with inference will keep being a server niche because they'll keep being 1-2 OOM more compute-hungry than whatever consumer hardware can handle. Like gaming: my laptop can run games from 2015 at max settings no problem but the games actually worth getting excited about in 2026 still melt a $2k GPU, because whatever headroom the hardware gains, developers immediately spend on ray tracing and Nanite and modelling individual skin cells or whatever. I don't see any plausible reason to expect that the ceiling on "valuable server-side compute" or "inference capacity" will rise any more slowly than the on-device capability is rising.
My assumption is that in 2031, SOTA top-intelligence AI will be hosted on cloud servers like it is today, offering dirt-cheap access to capabilities we can't even dream of today, while your Android will be running some open-source GPT-5+ equivalent.
Re: The beginning of scarcity in AI
#218Earlier quoted context omitted.
The decline of independent thoughts for one. As people become reliant on LLMs to do their thinking for them and solve all problems that they stumble upon, they become a shell of their previous self. Sadly, this is already happening.
There is no decline. Human assets were always too expensive to process some additional information. We are simply processing lot more of low signal data. Actually some of our analysts are empowered by the tools at their disposal. Their jobs are safe and necessary. Others were let go. Clients are happy to get fuller picture of their universe, which drives more informed decissions . Everybody wins.
You are free to believe what you want, but what you describe does not match what I’ve seen from society as a whole. I’m just going to leave this here: https://www.media.mit.edu/projects/your-brain-on-chatgpt/ove...
Re: The beginning of scarcity in AI
#219Earlier quoted context omitted.
I also can’t wait for the time when few know how to code. Just like how many folks don’t know html from css when the homebrew website went away. Their might always be llms, but the dependence is an interesting topic.
Look no further to be honest; look at older generation programming languages like COBOL and how sought-after good developers for that language are. But I'm also afraid / certain that LLMs are able to figure out legacy code (as long as enough fits in their context window), so it's tenuous at best. Also, funny you mentioned HTML / CSS because for a while (...in the 90's / 2000's) it looked like nobody needed to actuall…
How are COBOL developers "sought after"? That's an oft-repeated but woefully incorrect meme.
FAANG new grads make more. If the COBOL devs had upskilled throughout their career they'd be Senior Staff/Principal+ and making 5-10x more than they do today.
Re: The beginning of scarcity in AI
#220Earlier quoted context omitted.
> The companies that are entirely AI-dependent may need to raise prices dramatically as AI prices go up. It's not that clear. Sure, hardware prices are going up due to the extremely tight supply, but AI models are also improving quickly to the point where a cheap mid-level model today does what the frontier model did a year ago. For the very largest models, I think the latter effect dominates quite easily.
There's only so far engineers can optimise the underlying transformer technique, which is and always has been doing all the heavy lifting in the recent ai boom. It's going to take another genius to move this forward. We might see improvements here and there but the magnitudes of the data and vram requirements I don't think will change significantly
I’ve read and heard from Semi Analysis and other best-in-class analysts that the amount of software optimizations possible up and down the stack is staggering…
How do you explain that capabilities being equal, the cost per token is going down dramatically?