Yes! The "-ness" implies some degree of spectrum already, and from what I know and understand, one can talk about different degrees/classes of randomness. "decreasing entropy" would work too, I guess (Intuitively: If one would open a bet on a system outcome, how high would the quotas be? If there is some degree of randomness in the system, it would make sense to put money on multiple different outcomes to minimize ones losses. Only if there is no randomness at all, it would be rational to bet all money on the one option we expect).
Another further distinction would be between "true randomness" and "We do not know all input factors yet, hence, the outcome appears random to us". The former is something that genuinely exists in the universe as far as I understand physics (i.e. even if all input parameters are known, it is not possible to predict the outcome reliably, which seems to be the case for quantum physics, which I have the surfacest or surface levels of understandings about), the later boils down to reducing "unknown unkowns".
In practise, this means stuff like using seeds for random number generators, fixing things that look random like day of the week of a DateTime.now(), and so on. Depending on what you do, it might be never possible to get rid of all randomness, but I am 100% convinced that you can always contain it into a well-defined cage, and control everything else down to the last bit.
That also made me think of the opposite: "Increasing predictability" would be acceptable for me too, and a deterministic process/component/system/whatever is one that is at maximum possible predictability for me then.
I hate the marketing-selling-linkedn style as much as anyone, but I don't think it's an LLM thing in particular. It's a style that existed before LLMs and it's very easy to make LLMs avoid it with one or two prompt paragraphs.
For what it's worth, I didn't get that vibe reading this post.
>The strike by Alibaba is described as a "distillation" effort, which Anthropic has said involves training a less capable model on the outputs of a stronger one.
Claude used TB of content without permission to train their model and it was ok for them.
Now someone else uses the output of a Claude model to train model and they cry foul.
Legally obtaining a book for reading it yourself is different from legally obtaining a book for copying and republishing/reselling. If I buy a book for $5 at a sale I can read it myself or even sell it for $10 on craigslist, but I can't scan it and make a million copies and sell each of those.
They aren't republishing or reselling. In fact, they buy huge amounts of books and then destroy them, which is better for the rights holders than to resell them.
Since whole chunks of these books can be recited verbatim by these models, to which they sell access, they absolutely are republishing and reselling these books' content in a way.
Like I remember a research paper that managed to recreate the whole of a Harry Potter book from a model?
> Since whole chunks of these books can be recited verbatim by these models, to which they sell access, they absolutely are republishing and reselling these books' content in a way.
They are absolutely not "republishing" in any meaningful sense of the term. A chunk is not a whole book, and even getting a modern LLM to reproduce such a large chunk of an arbitrary book is not a trivial task. I have never heard of anyone who actively used LLMs for book piracy.
> Like I remember a research paper that managed to recreate the whole of a Harry Potter book from a model?
Even if that is true (it may well be false), this is likely far too difficult for any normal person to exploit, and moreover, even less likely to succeed for the great majority of other books who aren't nearly as famous.
Just because it's not a reasonable way to pirate stuff, doesn't make it legal -- just try your luck with Disney and let's see when they bite. Why would we let one company ignore the law, while rudelessly enforcing it in other cases? That's just state sponsorship with extra steps.
If we assume on average $20 per legally obtained book, 1.5 billion dollars are enough for 75 million books. That's approximately every non-fiction book in existence.
Latinamerican here.
When you talk about "adversarial country" I think of the USA (they can kidnap a president, kill people on boats without a trial, etc) and not China.
YMMV for different regions.
I'm a housekeeper skeptic. While I concede that a professional housekeeper would probably do a better job than me on most domestic tasks, I still think everyone should clean their own home, cook their own dinner, and write their own code.
For me the distinction is that your rice only needs to be edible once, while your code may need to last for decades. Using AI to code anything I could comfortably throw away if needed is a lot less fraught than letting it make choices that I and anybody who inherits the code is gonna have to live with, especially if by outsourcing those choices I reduce my understanding of the implications of those choices.
I don't let the AI make any choices. I have a lot of instructions and sample code for it to follow. It is basically a glorified code generator at that point.
I think the idea that code should last decades is now questionable, if not problematic. If we can now produce code at 10x the rate, that means we can have 10x more code (probably not desirable) or we can have 10x as many revisions. Whoever inherits the code can have it rewritten to their liking and understanding. Nothing helps better in understanding a system than to rebuild it, even if just by handholding an LLM.
Exactly, but if I start from working code with a lot of tests I don't need to remember the requirements. I just need to know my current requirement and figure out the ones I'm changing with my new requirement. It doesn't catch everything, but in most cases if I break some other requirement I find out about it and can figure out just that one more requirement and not the millions of others that still work.
I'm not getting it. OP said they are wary of letting the agent make choices for them, and outsourcing those choices lessens their understanding of them. They could interrogate the agent on why those choices were made until they have sufficient understanding, and they can also change the solution if they want to.
The thing about this is that you can choose how high level you go.
For example you can just tell it to make a website for a business with a webshop and it'll just generate thousands of lines of code and you have no control over anything. Or you can spend hours/days writing the specification and then have it generate it.
Or you can do what I do and work iteratively one feature at a time making sure everything is exactly the way you want it. I generally solve the problem myself then tell it what to do, or if I'm not sure what the best solution is I might discuss with the AI until we agree on a plan and then have it execute it. Often this leads to me learning useful things, like it will suggest a tool/feature that I didn't know about that's perfect for my usecase or it will identify a problem in my plan that I wouldn't have found until after spending hours on the implementation.
I've always been very detail oriented and I care a lot about code quality, I want my solutions to be clean, consistent and as simple as possible while solving the problem. To me, AI tools let me do that more quickly and better, it's not a compromise it's just flat out better in every dimension. It's about how you use it.
A lot of people seem to think that it's a binary choice, either hand craft a high quality bespoke solution or just vibe code a pile of trash. There's a whole spectrum in between those two, and I think there's a sweet spot where you still maintain control and understanding, it's just much faster and the result is actually better because it's not just you and the knowledge in your brain it's also the AI that practically knows everything - it will teach you things and suggest solutions you wouldn't have thought about, it makes you a better developer. It's a force multiplier and the smarter you are the better you will be at using it.
It's not a replacement it's an enhancement. It's like imagine a developer with Google vs one without, obviously the one with Google will be better because they have access to more information. The AI is like automatic google that just googles everything all the time, things you wouldn't have even thought to Google or things you couldn't possibly formulate a good search term for. With AI you can just show it a screenshot or describe an issue in detail and get a really solid answer a lot of the time. It's like having an expert on standby all the time, sure it's sometimes wrong but most of the time it's not and if you're smart you'll recognize when it isn't.
I'd say anyone who isn't using AI today aren't using their full potential. I don't see how anyone could possibly perform better without this tool than with it. I do see how someone who doesn't care could produce a lot of slop, but the people who refuse to use it aren't that guy. That guy has been using it to produce slop for years already. You can use it to produce top quality code if you choose to.
Much more complex than that. Even if it does give you a speedup at certain tasks, is it worth the cost and risks? You go faster, but now you have more code that you don't understand and so won't be as good at maintaining. There's the engergy use, the water use, the scrapers destroying the internet, the massive piles of slop, the hallucinations and bullshit, etc.
It means that even if it works for certain tasks, I think that the problems caused by use of LLMs outweigh their benefits. I think it's a bad idea to generate large piles of code that you don't understand, but due to competitive pressures, it's too tempting for people to pass up, leading to a world in which software is getting worse by the day, while pumping CO2 into the atmosphere and boiling scarce water supplies to do so, DDOSing websites to scrape the data, and polluting the internet with mountains of slop.
This isn't about using rice cookers or not, that's a personal choice for how you cook your food, and choosing to do so or not really only affects the person cooking and cleaning. A rice cooker probably uses a similar amount of energy as cooking it by hand, possibly even less.
But when people using LLMs are causing active harm, and are making it more difficult to collaborate on a team, it's a lot harder to accept that it's just a personal preference.
If you wanted to use the rice cooker analogy, imagine if rice cookers let you cook rice in just one minute. Faster, don't have to wait for the rice to be done, great! But in order to do so, you have to cook 50 pounts of rice, but throw out the majority of it, and use a thousand kilowatt hours of energy to do so. You'd better believe I'm going to be skeptical of everyone deciding that they suddenly have to use these 1-minute rice cookers that burn so much energy and generate so much waste.
Here it's important to take into account the consequences / cost of false positive vs false negatives.
If you're building a dashboard for visualizing something fun (hot dog sales in sport games) then the corner case error has low cost. I'm happy having this vibe coded dashboard that works 99/100 and my world is better with it existing.
Crypto is on the opposite scale (and I'm surprised this blog doesn't realize it): 9999/10000 isn't good enough because the corner cases have dire consequences. So, yeah, bad example for vibe coding
