[deleted]
The Rise of Whatever
31–40 of 537 posts
Re: The Rise of Whatever
#32Well they even call them "content creators", is there anything more whatever? It's literally "whatever" content needed to load the ads around it. It's not painters or musicians or documentarians, it's content creators.
Re: The Rise of Whatever
#33Love this writing. One paragraph hit very close to home. I used to be the guy who could figure out obscure scripts by google-fu and rtfm and willpower. Now that skill has been completely obliterated by LLMs and everyone’s doing it- except it’s mostly whatever > I don’t want to help someone who opens with “I don’t know how to do this so I asked ChatGPT and it gave me these 200 lines but it doesn’t work”.
I use LLMs for coding everyday and agree with most of the article, even if it does attack me as an "indignant HackerNews mudpie commenter".
In the same vein, I've actually worked on crypto projects in both DeFi and NFT spaces, and agree with the "money for criminals" joke assessment of crypto, even if the technology is quite fascinating.
Re: The Rise of Whatever
#34Earlier quoted context omitted.
> LLM outputs are nondeterministic. LLM outputs are deterministic. There is no intrinsic source of randomness. Users can add randomness (temperature) to the output and modify it. > But this article is based on a model of LLM code generation from 6 months ago There hasn't been much change in models from 6 months ago. What happened is that we have better tooling to sift through the randomly generated outputs. I don't d…
There hasn't been much change in models from 6 months ago. I made the same claim in a widely-circulated piece a month or so back, and have come to believe it was wildly false, the dumbest thing I said in that piece.
I have my own test to measure performance: https://omarabid.com/gpt3-now
So far the only model that showed significant advancement and differentiation was GPT-4.5. I advise to look at the problem and read GPT-4.5 answer. It'll show the difference to other "normal models" (including GPT-3.5) as it shows considerable levels of understanding.
Other normal models are now more chatty and have a bit more data. But they do not show increased intelligence.
Re: The Rise of Whatever
#35Earlier quoted context omitted.
LLM calls make stuff up. Your compiler can't make things up. An agent iterates LLM calls. When your LLM call makes an API up, your compiler will generate errors. The errors get fed back into the iterative loop. In pretty much ever real case, the LLM corrects, but either way: the result is clear. The code may be wrong, but it shouldn't hallucinate entire APIs.
A great solution to this problem, but it doesn't seem like this approach will generalize to problems in other fields, or even to more suble coding confabulations that can't be detected by the compiler or static analysis.
I vehemently agree with this. But it doesn't change the falsity of the claim in the article.
Re: The Rise of Whatever
#36Earlier quoted context omitted.
AIs still frequently make up stuff up - there isn't really a way to get out of that. Have they improved a lot in the last six months? 100%! But they still make mistakes its quite common
You can improve on that 1. A type-strict compiler. 2. https://github.com/isaacphi/mcp-language-server LLMs will always make stuff up because they are lossy. In the same way that if I ask you to list the methods for some random object lib you'd not be able to do that; you use the documentation to pull that up or your code-complete companion. LLMs are just getting the tools for that.
Oh for sure I agree 100%! I was just saying that they will always make stuff up no matter what. Those are both good fixes but at its core it can only "make stuff up".
Re: The Rise of Whatever
#37[flagged]
Re: The Rise of Whatever
#38LLM output is crap. It’s just crap. It sucks, and is bad. Still don't get it. LLM outputs are nondeterministic. LLMs invent APIs that don't exist. That's why you filter those outputs through agent constructions, which actually compile code. The nondeterminism of LLMs don't make your compiler nondeterministic. All sorts of ways to knock LLM-generated code. Most I disagree with, all colorable. But this article is based…
> The garbage generator generates garbage, but if you run it enough times it gets something slightly-less-garbage that can satisfy a compiler! You're stupid if you don't think this is awesome!
Counter point: the brain also generates mostly garbage, just slower.
Re: The Rise of Whatever
#39Earlier quoted context omitted.
Agreed! The only silver lining I can see is that a new perspective may be forced on how well or badly we’ve facilitated learning, usability, generally navigating pain points and maybe even all the dusty presumptions around the education / vocational / professional-development pipeline. Before, demand for employment/salary pushed people through. Now, if actual and reliable understanding, expertise and quality is desir…
To be fair, LLMs are just the most recent step in a long road of doing the same thing. At any point of progress in history you can look backwards and forwards and the world is different. Before tractors a man with an ox could plough x field in y time. After tractors he can plough much larger areas. The nature of farming changes. (Fewer people needed to farm more land. ) The car arrives, horses leave. Computers arrive…
[deleted]
Re: The Rise of Whatever
#40Earlier quoted context omitted.
I keep hearing this theory, that “eventually” we will find the use cases for distributed ledgers, and I don’t buy it. Bitcoin was invented at roughly the same time as the iPhone, and the iPhone immediately found use cases. Right away the global economy reoriented itself around the smartphone, because it demonstrated real value to actual people. We did not need to wait and twiddle our fingers for years going “I think…
there are many people with many use cases for distributed ledgers. we are already aware of the flowchart of your argument path “list them” “oh I can do that in this other convoluted way that doesnt solve any of these users goals or problems” “I’m not the target audience for that so it doesnt count” “ah so financial speculation, that doesnt count despite being the largest application and sector on the planet” “marketc…
It's clear that financial speculation is a big use for crypto, probably the biggest.
But since almost all the tokens bear neither interest nor dividends, it looks a lot more like a casino.