In my experience LLMs mimic human thought, so they don't "copy" but they do write from "experience" -- and they know more than any single developer can.
So I'm getting tired of the argument that LLMs are "plagiarism machines" -- yes, they can be coaxed into repeating training material verbatim, but no, they don't do that unless you try.
Opus 4.6's C compiler? I've not looked at it, but I would bet it does not resemble GCC -- maybe some corners, but overall it must be new, and if the prompting was specific enough as to architecture and design then it might not resemble GCC or any other C compiler much at all.
Not only do LLMs mimic human thinking, but also they mimic human faults. Obviously one way in which they mimic human faults is that there are mistakes in the LLMs' training materials, so they will evince some imperfections, and even contradictions (since there will be contradictions in their training materials). Another way is that their context windows are limited, just like ours. I liken their hallucinations to crappy code written by a tired human at 3AM after a 20 hour day.
If they are so human-like, we really cannot ascribe their output to plagiarism except when prompted so as to plagiarize.
Do they really think they will get some money from the AI ponzi scheme ?
Well, at least they might still have a product to sell once the AI bubble pops, unlike with NVIDIA which does seem to kinda forgot to design new consumer GPUs after getting high on AI money.
There's clearly easy/irrational money distorting the markets here. Normally this wouldn't be a problem: prices would go up, supply would eventually increase and everybody would be okay. But with AI being massively subsidized by nation-states and investors, there's no price that is too high for these supplies.
Eventually the music will stop when the easy money runs out and we'll see how much people are truly willing to pay for AI.
I bought 6x refurbished ultrastars for ~$100/ea Black Friday 2024. They were over $200/ea 2025. Samsung T7 (and shield) SSD’s have 2x-3x. Can’t get 1TB for less than like $180 right now. It’s ridiculous
This is all basically a textbook example of irrational market decisions. There’s clearly a bubble and not enough money coming in to pay for the AI bonanza.
It’s building materials being in short supply when there’s obviously more houses than buyers. That’s just masked at the moment because of all the capital being pumped in to cover for the lack of actual revenue to pay for everything. The structural mismatch at the moment is gigantic, and the markets are getting increasingly impatient waiting for the revenue to materialize.
Mark this post… in a few years folks will be coming up with creative ideas for cheap storage and GPUs flooding the market after folks pick up the pieces of imploded AI companies.
(For the record, I’m a huge fan of AI, but that doesn’t mean I don’t also think a giant business and financial bubble is about to implode).
I built a new server this time last year. My board does 6 channel RAM so I bought 6x32GB ECC DDR5. $160 a stick at the time. Just for grins I looked up the same product number at the same supplier I originally bought from. $1300 apiece. One of the VMs running on that server is TrueNAS, with 4 20TB WD Red Pros. God help me if I have to replace a drive.
I was recently involved in a large server purchase for work, where we wanted 72 hard drives of 24TB each for a server. They were available last year, but last month the largest we could get were 20TB drives.
It's interesting to see here that spending is irrational, but actually even if AI improvements slow down it's more rational for companies to spend more and underutilize the machines than to underspend and get disrtupted.
On the otherhand lots of people here are even more uncomfortable of the other option, which is quite possible: AI software algorithms may scale better than the capacity of companies that make the hardware. Personally I think hardware is the harder to scale from the two and this is just the beginning.
What are companies needing all of these hard drives for? I understand their need for memory, and boot. But storing text training data and text conversations isn't that space intensive. There's a few companies doing video models, so I can see how that takes a tremendous amount of space. Is it just that?
I console myself with knowledge of the economics maxim that every supply shortage is usually, eventually, followed by a supply glut.
One can only hope that that's the principle at work here, anyway. It could also be a critically damped system for all I know. Unfortunately I studied control systems too...
Better stock up with used laptops. I'm going to buy another one this year. Those used ones usually don't last very long.
What if in the near future it is simply too expensive to own "personal" computers? What if you can no longer buy used computers from official channels but have to find local shops or sharpen up on soldering skills and find parts from dumps? The big techs will conveniently "rent out" cloud computer for us to use, in exchange of all of your data.
I'm not against subsidies but the concentration is a problem. This money could have spurned grass roots participation in these emerging industries, but instead they chose to go with the most heinous of monocultures, leaving billions of people out of the loop.
I listed some hard drives on Friday on eBay.. most of them refurbished... within 5 minutes got a message from a person who wanted them all... shipped them an hour later
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[ 3.3 ms ] story [ 49.2 ms ] threadYes, AI is nice, but I also like to be able to buy some RAM and drives…
So I'm getting tired of the argument that LLMs are "plagiarism machines" -- yes, they can be coaxed into repeating training material verbatim, but no, they don't do that unless you try.
Opus 4.6's C compiler? I've not looked at it, but I would bet it does not resemble GCC -- maybe some corners, but overall it must be new, and if the prompting was specific enough as to architecture and design then it might not resemble GCC or any other C compiler much at all.
Not only do LLMs mimic human thinking, but also they mimic human faults. Obviously one way in which they mimic human faults is that there are mistakes in the LLMs' training materials, so they will evince some imperfections, and even contradictions (since there will be contradictions in their training materials). Another way is that their context windows are limited, just like ours. I liken their hallucinations to crappy code written by a tired human at 3AM after a 20 hour day.
If they are so human-like, we really cannot ascribe their output to plagiarism except when prompted so as to plagiarize.
Is the profitability of these electronics manufacturers more likely than the companies that are buying up all their future inventory?
Well, at least they might still have a product to sell once the AI bubble pops, unlike with NVIDIA which does seem to kinda forgot to design new consumer GPUs after getting high on AI money.
Eventually the music will stop when the easy money runs out and we'll see how much people are truly willing to pay for AI.
It’s building materials being in short supply when there’s obviously more houses than buyers. That’s just masked at the moment because of all the capital being pumped in to cover for the lack of actual revenue to pay for everything. The structural mismatch at the moment is gigantic, and the markets are getting increasingly impatient waiting for the revenue to materialize.
Mark this post… in a few years folks will be coming up with creative ideas for cheap storage and GPUs flooding the market after folks pick up the pieces of imploded AI companies.
(For the record, I’m a huge fan of AI, but that doesn’t mean I don’t also think a giant business and financial bubble is about to implode).
On the otherhand lots of people here are even more uncomfortable of the other option, which is quite possible: AI software algorithms may scale better than the capacity of companies that make the hardware. Personally I think hardware is the harder to scale from the two and this is just the beginning.
I'd have thought HDDs aren't at the top of the list for AI requirements, are other component manufacturers struggling even more to meet demand?
One can only hope that that's the principle at work here, anyway. It could also be a critically damped system for all I know. Unfortunately I studied control systems too...
What if in the near future it is simply too expensive to own "personal" computers? What if you can no longer buy used computers from official channels but have to find local shops or sharpen up on soldering skills and find parts from dumps? The big techs will conveniently "rent out" cloud computer for us to use, in exchange of all of your data.
"Don't you all have cellphones?"