31–40 of 111 posts
Yet another blog post about how LLM can't replace people for X task. I wish there was less noise about this and more discussions on how we will (all) benefit from LLM replacing people. Like UBI, paying people to pursue their passions, etc. I personally would be fine if LLM replaced my $DAYJOB if it meant I could work on learning violin, gardening, or creating videogames.
Yet another blog post about how LLM can't replace people for X task. I wish there was less noise about this and more discussions on how we will (all) benefit from LLM replacing people. Like UBI, paying people to pursue their passions, etc. I personally would be fine if LLM replaced my $DAYJOB if it meant I could work on learning violin, gardening, or creating videogames.
don't worry, generative models are coming after music and videogames too. hope you really like gardening...
90% of frontend development is gathering the requirements. The other 90% is trying to get CSS to center a div.
90% of frontend development is gathering the requirements. The other 90% is trying to get CSS to center a div.
AI won't take of front-end dev jobs until it can start creating a new framework every week, constantly break backwards compatibility, then abandon the project and start a new one.
Just describe a average website and see if ChatGPT can reproduce it. I think the description as such will be the difficult tasks, followed by fine tuning your description if ChatGPT's result isn't correct.
But, nobody really has a job like this in the front end. They were all replaced by Squarespace/Wix/Webflow/etc years ago. Which seems to confuse people who aren't really in web development, and where Josh Comeau is mainly making the argument from (against the social media idea that "front end is dead").
T,FTFY
What we see ChatGPT being good at is largely boilerplate. The folks who are like "I am 5x more productive now with ChatGPT" raise alarm bells in my head - it suggests that they were typing the programming equivalent of pablum for most of their day.
Yeah, if you ask ChatGPT to author some simple HTML it will do so with a refreshing level of accuracy (though far from being able to do without extensive supervision) - but who is writing plain HTML? Likewise it's cool that it can generate a sort function whole cloth... but who is writing their own sort functions?
The trick with boilerplate is that the industry has already spent the past two decades automating large amounts of it away via frameworks and baking much of the functionality into programming languages themselves. If you're writing boilerplate for so much of your day that a boilerplate-spitting AI massively increases your productivity, I'd argue you've got bigger problems!
The trend - across both backend and frontend dev - is to make things more declarative and close the gap between what the developer wants and the amount of code needed to implement it. Use these technologies - it has made people dramatically more productive, but didn't require a LLM!
If you find yourself spending a significant portion of your day writing boilerplate, stop doing that! There are many options for you that allow you to more directly express what you want!
> "Fundamentally, LLMs are super-powerful text predictors. Given a prompt, they use machine learning to try and come up with the most likely set of characters that follow the prompt." I've heard this tossed around and in the old days it used to be true. BUT in the process of learning to predict text, just like with CNNs that learned to predict image types, it seems GPT learned some very interesting functions that bri…
Funnily enough this is almost exactly how human children work when they're learning to talk