81–90 of 1001 posts
So we replace the task of writing tedious boilerplate with the task of reading the AI's tedious boilerplate. Which takes just as long. And leaves you with less understanding. And is more boring.
This has never once been my experience. Its definitely less fun but it takes way less time.
I have one very specific retort to the 'you are still responsible' point. High school kids write lots of notes. The notes frequently never get read, but the performance is worse without them: the act of writing them embeds them into your head. I allegedly know how to use a debugger, but I haven't in years: but for a number I could count on my fingers, nearly every bug report I have gotten I know exactly down to the l…
What this boils down to is an argument for slop. Yeah, who cares about the quality, the mediocrity, the craft... get the slop, push it in, call it done. It mostly works in the golden path, it's about 6 or 7 orders of magnitude slower than hand-written software but that's ok, just buy more AWS resources, bill the client, whatever. I can maybe even see that point in some niches, like outsourcing or contracting where yo…
Just about no-one in the F100 unless they are on very special teams.
If you care about the craft you're pushed out for some that drops out 10x LOC a day because your management has no ability to measure what good software is. Extra bonus points for including 4GB of node_modules in your application.
> "For art, music, and writing? I got nothing. I’m inclined to believe the skeptics in those fields." You've already lost me, because I view programming as an art form. I would no more use AI to generate code than I would use it to paint my canvas. I think the rest of the article is informative. It made me want to try some things. But it's written from the perspective of a CEO thinking all his developers are just sal…
If you do that, I'll swallow my AI skepticism.
I would love to have an LLM that I can turn loose on an unfamiliar codebase that I can ask questions of. I would love to have an LLM that will fill in my Vulkan boilerplate. etc.
I use emacs and Mercurial. You can demonstrate magic to me and I can be convinced even if it's not mainstream.
Rewriting Javascript slop to StackOverflow standards is not convincing me.
Get to it.
(The OAuth stuff posted earlier certainly moved my needle, but the fact that they needed a gaggle of reviewers as well as hand holding when the LLM got stuck mutes the impact significantly.)
Machine translation and speech recognition. The state of the art for these is a multi-modal language model. I'm hearing impaired veering on deaf, and I use this technology all day every day. I wanted to watch an old TV series from the 1980s. There are no subtitles available. So I fed the show into a language model (Whisper) and now I have passable subtitles that allow me to watch the show. Am I the only one who remem…
For example, for automatic speech recognition (ASR), see: https://huggingface.co/spaces/hf-audio/open_asr_leaderboard
The current best ASR model has 600M params (tiny compared to LLMs, and way faster than any LLM: 3386.02 RTFx vs 62.12 RTFx, much cheaper) and was trained on 120,000h of speech. In comparison, the next best speech LLM (quite close in WER, but slightly worse) has 5.6B params and was trained on 5T tokens, 2.3M speech hours. It has been always like this: With a fraction of the cost, you will get a pure ASR model which still beats every speech LLM.
The same is true for translation models, at least when you have enough training data, so for popular translation pairs.
However, LLMs are obviously more powerful in what they can do despite just speech recognition or translation.
I have a very simple counter argument: I've tried it and it's not useful. Maybe it is useful for you. Maybe even the things you're using it for are not trivial or better served by a different tool. That's fine, I don't mind you using a tool far away from my codebase and dependency tree. It has not been useful for me, and it's very unlikely it's ever going to be. Except that's not the argument people are making. They…
Indeed but the tedious naysaying that this is arguing against is that AI isn't good full stop. They aren't saying "I tried it and it's not for me but I can see why other people would like it".
You keep using that tool, to your advantage. I’d you’re really altruistic you post some videos of how productive you can be like DHH did with his blog in 15 minute videos.
If you’re really that much more productive, the skeptics won’t be able to keep up and it should only take 6 months or some for that to become self evident.
The privacy aspect and other security risks tho? So far all the praise I hear on productivity are from people using cloud-hosted models. Claude, Gemini, Copilot and and ChatGPT are non-starters for privacy-minded folks. So far, local experiements with agents have left me underwhelmed. Tried everything on ollama that can run on my dedicated Ryzen 8700G with 96GB DDR5. I'm ready to blow ~10-15k USD on a better rig if I…
Question: If everyone uses AI to code, how does someone become an expert capable of carefully reading and understanding code and acting as an editor to an AI?
The expert skills needed to be an editor -- reading code, understanding its implications, knowing what approaches are likely to cause problems, recognizing patterns that can be refactored, knowing where likely problems lie and how to test them, holding a complex codebase in memory and knowing where to find things -- currently come from long experience writing code.
But a novice who outsources their thinking to an LLM or an agent (or both) will never develop those skills on their own. So where will the experts come from?
I think of this because of my job as a professor; many of the homework assignments we use to develop thinking skills are now obsolete because LLMs can do them, permitting the students to pass without thinking. Perhaps there is another way to develop the skills, but I don't know what it is, and in the mean time I'm not sure how novices will learn to become experts.