I wouldn't have expected there to be enough text from before 1913 to properly train a model, it seemed like they needed an internet of text to train the first successful LLMs?
Readit Newsarikrak commented on History LLMs: Models trained exclusively on pre-1913 texts github.com/DGoettlich/his... · Posted by u/iamwil
I recently wrote a short post on something similar: while AI is able to solve increasingly longer tasks, people's attention spans are getting shorter.
https://www.zappable.com/p/ai-vs-human-attention-spans
Hopefully people can learn to use AI to help them, while still thinking on their own. It's not like that many of the assignments in school were that useful anyways...
Before advanced AI, "essential complexity" was a bottleneck and Brooks was right that there couldn't be continuous exponential gains in software productivity. However advanced AI will handle essential complexity as well, which can end up making it 10x or 100x faster to develop software. We still need humans currently, but there's no area that one can point to and say we'll always need people for this aspect of software development. The latest coding agents are already reasoning with requirements before they write code, and they will only improve...
arikrak commented on Mozilla to shut down Pocket and Fakespot support.mozilla.org/en-US... · Posted by u/phantomathkg
I've used Pocket from back when they were called "Read it later" and have saved just shy of 30k articles. They've gotten worse recently, but when I tried other apps (instapaper, getmatter, raindrop, paperspan, omnivore) they all had their own issues. Now I have to give those apps another try...
I tried giving this to ChatGPT. (Just by uploading the image to the base OpenAI interface.) I expected to either (a) have the model already know the question and give the right answer, (b) hallucinate an answer or (c) refuse to engage with the problem at all.
Instead, this happened:
https://chatgpt.com/share/682cce62-c53c-8003-be2c-2929395868...
Basically, the model confidently outputs a guess, then calculates it, determines it to be incorrect, and repeatedly tries again, even repeating the same guesses over and over. It does not recognize any symmetry and acts like a completely unstructured agent. In the end, the model vehemently asserts there to be no solutions to this puzzle. I really did not expect this and will update my beliefs accordingly if the models behave as badly with future puzzles.
Here's gemini https://g.co/gemini/share/ab287b25648f
I also asked Chat GPT o3 and it thought for 11.5 minutes! https://chatgpt.com/share/682d0993-db4c-8004-a66c-3908ef7203...
arikrak commented on The 70% problem: Hard truths about AI-assisted coding addyo.substack.com/p/the-... · Posted by u/mooreds
Again one of the few advantages of having been round the sun a few more times than most is this isn’t the first time this has happened.
Packages were supposed to replace programming. They got you 70% of the way there as well.
Same with 4GLs, Visual Coding, CASE tools, even Rails and the rest of the opinionated web tools.
Every generation has to learn “There is no silver bullet”.
Even though Fred Brooks explained why in 1986. There are essential tasks and there are accidental tasks. The tools really only help with the accidental tasks.
AI is a fabulous tool that is way more flexible than previous attempts because I can just talk to it in English and it covers every accidental issue you can imagine. But it can’t do the essential work of complexity management for the same reason it can’t prove an unproven maths problem.
As it stands we still need human brains to do those things.
AI is a potential silver bullet since it can address the "essential complexity" that Fred Books said regular programming improvements couldn't address. It may not yet have caused an "order of magnitude" improvement in overall software development but it has caused that improvement in certain areas, and that will spread over time.
Clicking the link opens the Ticketmaster app on my phone.
arikrak commented on A chemist explains the chemistry behind decaf coffee theconversation.com/retai... · Posted by u/BerislavLopac
The decaf process seems expensive so you might expect the end result to cost more, but it never does. Which means either the producers are making less profit on decaf, or they are using lower quality beans. If the latter is true, which seems more likely, that might explain why decaf sometimes tastes less good, separately from the effect of the process itself on taste.
They use higher-caffeine beans for decaf coffee - Robusta instead of Arabica. Robusta beans aren't considered as good so they're cheaper, and they sell the caffeine they extract to e.g. soda companies.