Was the article edited? I don't see a reference to the phrase "three sisters" on it, it just says "corn, beans, and squash." Did the original headline mention it?
Original HN title was "1k year old 3 sisters crop farm found in Northern Michigan"
I really wish that when titles were edited there was some history, it would make it much easier to understand these little discussions based on the original title.
You're leaving out their training costs. And while you might say "well, once they're trained you don't have to spend more on that", but as we've seen they have to keep training new models on new data, such as current events and new language features and APIs. And some aspects of that training are becoming more costly, or more scarce, as companies like Reddit and Stackoverflow restrict and sell their data, less data gets produced on Stackoverflow as people switch to using LLMs instead, website operators go to more extreme measures to block AI scrapers that ignore robots.txt, etc.
Yeah, people tout RAG and fine tuning, but lots of people just use the base chat model, if it doesn't keep up to date on new data, it falls behind. How much are these companies spending just keeping up with the Joneses?
This is a terrible attitude which unfortunately is all too common in the industry right now: evaluating AI/ML systems not based on what they can do, but what they hypothetically might be able to do.
The thing is, with enough magical thinking, of course they could do anything. So that let's unscrupulous salesmen sell you something that is not actually possible. They let you do the extrapolation, or they do it for you, promising something that doesn't exist, and may never exist.
How many years has Musk been promising "full self driving", and how many times recently have we seen his cars driving off the road and crashing into a tree because it saw a shadow, or driving into a Wile E Coyote style fake painted tunnel?
While there is some value in evaluating what might come in the future when evaluating, for example, whether to invest in an AI company, you need to temper a lot of the hype around AI by doing most of your evaluation based on what the tools are currently capable of, not some hypothetical future that is quite far from where they are.
One of the things that's tricky is that we have had a significant increase in the capability of these tools in the past few years; modern LLMs are capable of something far better than two or three years ago. It's easy to think "well, what if that exponential curve continues? Anything could be possible."
But in most real life systems, you don't have an unlimited exponential growth, you have something closer to a logistic curve. Exponential at first, but it eventually slows down and approaches a maximum asymptotically.
Exactly where we are on that logistic curve is hard to say. If we still have several more years of exponential growth in capability, then sure, maybe anything is possible. But more likely, we've already hit that inflection point, and continued growth will go slower and slower as we approach the limits of this LLM based approach to AI.
Given the shift in focus from back and forth interaction with the AI to giving it a command then waiting as it reads a series self-generated inputs and outputs, I feel like we're at that inflection point - the prompts might appear to be getting smarter because it can do more, but we're just hiding that the "more" it's doing is having a long, hidden conversation that takes a bunch more time and a bunch more compute. This whole "agentic" thing is just enabling the CPU to spin longer.
What is the defining factor that makes all technologies plateau unlike evolution that seems to be open-ended? Technologies don't change themselves, we do.
What? Evolution is specifically known for getting caught in local maximums. Species have little evolutionary pressure to get better when they are doing great, like a species with no predators on an island. The only thingsdriving evolution for that creature is natural selection towards living longer and getting less diseases, dying in less accidents, stuff like that. And those aren't specific enough and don't pressure on a time basis so there isn't much pressure to improve beyond the natural lifespan. Plus, for some cases, living longer is not really the goal, it's reproducing more. It's entirely possible, likely even, that maximizing for longevity eventually starts to give a negative effect towards reproduction, and vice versa, so an equilibrium is reached.
Also technologies don't develop like evolution really so not sure why you drew that comparison.
Technologies plateau for a combination of reasons - too expensive to make it better, no interest in making it better, can't figure out any more science (key people involved leave / die / lose interest, or it's just too difficult with our current knowledge), theoretical limits (like we are reaching in silicon chips). I don't see a lot of similarity with evolution there.
100% this. Actually a lot of (younger) folks don't know that the current LLM "revolution" is the tail end of the last ~20 years of ML developments. So yeah, how many more years? In a way, looking at the costs and complexity to run them, it looks a bit like building huge computers and tvs with electronic tubes in the late 1940s. Maybe there is going to be a transistor moment here and someone recognises we already have a deterministic algorithms we could combine for deterministic tasks, in place of the Slop-Machines...? I dont mind them generating bullshit videos and pictures, as much as the potential they have to completely screw up the quality of software in completely new ways.
The attitude is typical of crypto grifters or any other grifters. Or if not malign it tends to come from someone who has literally zero experience in the space.
The amount of exposure to reliably fully erase it, and the amount to flip one bit, are likely different. Flip the wrong bit and you can easily cause a crash. Yes, if you wanted to be sure to clear every bit you'd need that 20 minutes of exposure, but I wouldn't be surprised if flipping a single bit or a few of them was much easier.
Two different effects being confused here. The EPROMs had a transparent window to the whole die. Bright flashes of light could disrupt the normal reading of memory, without permanently changing it. The sticker covering the window (usually with a description and version of the firmware) served multiple purposes.
Transient disruption of normal reads seems plausible to me. Any sort of erasure by flashes of light (visible or UV) that did not injure the humans, much less so!
The paper itself is behind a paywall so I can't see it, but it looks from the references like they provided proper attribution.
It's unfortunate that some of the articles around it don't mention that, but it seems like the main point of this is discussing the process for building the transistors, and then showing that can be used to build a complete CPU, not the CPU design itself which they just used an off-the-shelf open source one, which is designed to use a very small number of gates.
While others certainly have a financial interest in it, it is not publicly traded and Musk solely controls it. For instance, he just unilaterally sold it to another of his privately held companies, xAI, for a valuation he made up.
Musk's privately held companies, and to a large degree Tesla as well, are all things he treats as effectively one big company that he controls; he'll take employees from one to another at will, he sells them to each other or spins them out at will in all stock transactions, etc.
The EU regulations allow seeing through such sham company boundaries that are all controlled by a single entity, and treating them as a single company.
"Musk did not ask investors for approval but told them that the two companies had been collaborating closely and the deal would drive deeper integration with Grok, the investor said."
Now, he may have only been talking about xAI investors here, but it seems pretty clear from his actions that Musk pretty much demands full control of his companies, and if he does involve the other investor's they're likely rubber-stamping without much opportunity to push back.
This is the best and most obvious example of successful anti-advertising legislation, NYC as well prohibits billboards in most places which is a blessing.
The fact that the MTA is now plastered in flatscreen ads is an example of huge overreach, and also an example of how better funding for public utilities like the subway eliminate the "need" for advertising that the MTA claims.
Unfortunately, this is the system working as designed per the capitalists. Underfund public utilities to make the public more dependent on the for-profit private sector. Banning ads is communism for this mindset.
Would you be able to parse it in a streaming fashion and just store the structure of the document in memory, with just offsets for all of the string locations, and then re-read those from disk as needed?
With modern SSDs and disk cache, that's likely enough to be plenty performant without having to store the whole document in memory at once.
No, not in the archived version: https://web.archive.org/web/20250612153046/https://www.smith...
Oh, was this mentioned in the original HN title? Has that been edited?
Yes, it was. https://web.archive.org/web/20250615154352/https://news.ycom...
Original HN title was "1k year old 3 sisters crop farm found in Northern Michigan"
I really wish that when titles were edited there was some history, it would make it much easier to understand these little discussions based on the original title.