111–120 of 239 posts
>For the first time since the 2000s, technology companies are confronting the limits of their supply chain. I thought there'd been a shortage of cheap GPUs since ChatGPT took off and also before that in various crypto booms. I'm not sure it's a new thing.
Earlier quoted context omitted.
Is foo a pointer in your example? Is free(NULL) not a valid operation?
Yes `foo` is a pointer. `free(NULL)` is harmless in C89 onwards. As I said, programmers freeing NULL caused so many issues they changed the API. It doesn't help that `malloc(0)` returns NULL on some platforms. If you are writing code for an embedded platform with some random C compiler, all bets on what `free(NULL)` does are off. That means a cautious C programmer who doesn't know who will be using their code never a…
If your compiler chokes on `free(NULL)` you have bigger problems that no LLM (or human) can solve for you: you are using a compiler that was last maintained in the 80s!
If your C compiler doesn't adhere to the very first C standard published, the problem is not the quality of the code that is written.
> If they aren't avoiding passing NULL to `free()`, they haven't suffered long enough to be good.
I dunno; I've "suffered" since the mid-90s, and I will free NULL, because it is legal in the standard, and because I have not come across a compiler that does the wrong thing on `free(NULL)`.
Earlier quoted context omitted.
I used LLMs to write what seems like far too many lines of code now. This is an example Opus 4.6 running at maximum wrote in C: if (foo == NULL) { log_the_error(...); goto END; } END: free(foo); If you don't know C, in older versions that can be a catastrophic failure. (The issue is so serious in modern C `free(NULL)` is a no-op.) If it's difficult to get a `FOO == NULL` without extensive mocking (this is often the c…
C is fundamentally a bad target for LLMs. Humans get C wrong all the time, so we can not hope the nascent LLM, which has been trained on 95% code that does automatic memory management, to excel here. I always found myself writing verbose copypasta code first, then compress it down based on the emerging commonalities. I think doing it the other way around is likely to lead to a worse design. Can you not tell the LLM t…
I found it exceptionally good, because:
a) The agent doesn't need to read the implementation of anything - you can stuff the entire projects headers into the context and the LLM can have a better birds-eye view of what is there and what is not, and what goes where, etc.
and
b) Enforcing Parse, don't Validate using opaque types - the LLM writing a function that uses a user-defined composite datatype has no knowledge of the implementation, because it read only headers.
This notion that "we don't have enough compute" does not cleanly reconcile with the fact that labs are burning cash faster than any cohort of companies in history. If I am a grocery store that pays $1 for oranges and sells them for $0.50, I can't say, "I don't have enough oranges."
There is a major logic flaw in what you're saying. 'If I am a grocery store that pays $1 for oranges and sells them for $0.50, I can't say, "I don't have enough oranges."' How about 'if I'm a grocery store and I see no limit on demand for oranges at $.50 but they are currently $1, I can say 'if oranges were cheaper I could sell orders of magnitude more of them'. Buying oranges for $1 and selling for $0.5 is an invest…
It's a delusion that customers are going to remain with the behemoths when a Qwen model run by an independent is $10/m, unlimited usage.
This is not a market that can be locked-in with network effects, and the current highly-invested players have no moat.
We just had a realization during a demo call the other day: The companies that are entirely AI-dependent may need to raise prices dramatically as AI prices go up. Not being dependent on LLMs for your fundamental product’s value will be a major advantage, at least in pricing.
We just had a realization during a demo call the other day: The companies that are entirely AI-dependent may need to raise prices dramatically as AI prices go up. Not being dependent on LLMs for your fundamental product’s value will be a major advantage, at least in pricing.
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.
It's artificial scarcity. LLM inference will soon be commodity as cloud. There is a 2-3years still before ASIC LLM inferences will catch up.
I don't think so. GB200 prices are GOING UP. A100s are still expensive. This implies massive utilization and demand, no? These machines are not sitting idle, or prices would drop in the very competitive hyperscaler environment.
Infra is always limited, even at hyper scalers. This leads to a bunch of tools dfofr caching, profiling and generally getting performance up, not to mention binpacking and all sorts of other "obvious" things.
We just had a realization during a demo call the other day: The companies that are entirely AI-dependent may need to raise prices dramatically as AI prices go up. Not being dependent on LLMs for your fundamental product’s value will be a major advantage, at least in pricing.
No shit. People are just figuring this out now? This is the “Building my entire livelihood on Facebook, oh no what?” all over again. Oh no sorry I forgot, your laptops LLM can draw a potato, let me invest in you.