Interviews by celebrities predicting AI will revolutionize the economy: 2837191001747
Software and online things I've used that seem to be better than they were before ChatGPT was introduced: 0
- searching: better
- photo edit/enhance/filter: easier and acessible
- text summarization: better
- quick scripts/tools: faster
- brainstorming/iterating ideas: faster
- generating list of names: faster
- rephrasing text: better
- researching topics: faster
- stackoverflow: i'm finally free. won't be missed by me
- coding: debatable but for me LLMs made possible projects that weren't before due to scope or lack of expertise
Still, this "making something worse so you can have more of it" shows up pretty much everywhere in human experience. Sometimes it's depressing, other times amazing to see what was achieved with that mentality, and it seems AI is just accelerating it.
My comment was pointed at people who use AI specifically with the goal of making anything easier and faster. Doesn't matter what it is. "Faster and easier is better". as though doing more of the same shit are primary goals in themselves.
If you're using AI to explore better technical decisions, you're doing it right! AI can be a catalyst for engineering and science. But not if we treat it like a mere productivity tool. The quality of the thing enabled by the AI very much matters.
Because I have limited time and energy. Take learning as an example:
I couldn't afford to spend a weekend learning the tradeoffs made by the top 5 WebGL JavaScript game engines AND generate the same demos for all of them to compare DX, and performance on my phone. And as I had more questions about their implementation I would have to scavenge their code again, for each question.
A sample of the questions I had (and as I asked it would suggest new question for things I didn't know I should ask):
- Do they perform sorting or are their drawing immediate? sort on z? z and y? z/y and layers? immediate'ish + layers? Frustum culling supported? What's their implementation for it if any?
- What are their GPU atlas strategies? fixed size? multiple with grouping by drawing frequency to reduce atlas switching? 2048? 4096? How many atlases? Does it build the atlas at boot or does it support progressive atlas sprite loading? How does it deal with fragmentation? What does it use for packing algo? Skyline ir something more advanced? How is their batch splitting behaviour and performance characteristics?
- Does it help with ECS? How is their hierarchical entity DX, if any? Does it math with matrices for transformations or simpler math? Shaders support? Do they use an Uber shader for most things? And what about polygons? Also, how do they help with texture bleeding? What's their camera implementation? Do they support spatial audio?
...and so on. Multiply the number of questions by at least 10.
And I asked LLM to show me the code for each answer, on all 5 engines.
This kind of learning just wasn't feasible for me before with my busy life.
So when I say "easier" it often means "made possible".
Finally let's not forget most of us in HN are incredibly privileged and can afford to learn futile things on the weekend. But for a great part of the less privileged population, having access to easier learning is LIFE CHANGING.
> And I asked LLM to show me the code for each answer, on all 5 engines.
They same way I would have done without AI, but it sped up finding the relevant parts to a velocity that made it viable in my limited time.
And I think the same is true for quite a lot of people. It’s a thing I said a few months ago while discussing with someone about AI. “If AI was to go away, would you care? Compare with if smartphones were to go away.”
Most people would not blink twice if AI were to be removed. Try to remove their phones, would not be the same!
The AI mode does at least attempt to list it's sources, but it's extra hoops to jump through.
Google lens image search used to be amazing, I tried a repeat of a search I did before of a piece of art, it showed the same piece but confidently listed the artist and year wrong by about 300 years.
I’ve had relatives do “research” about things I mentioned I needed to do, and they’ve just sent screenshots of the incorrect AI answer.
It’s made google almost entirely useless, there is zero incentive for them to try to make search better (vs incentive to make it worse) and even if they did want to make it better the sheer volumes of slop have made that even harder.
We’ve completely sabotaged out ability to collate information at scale as a civilization, for the benefit of a few companies that were already the largest in the world to begin with. And it turns out, very few people notice or even care about this.
I would not know if they have gotten better or worse cause I don’t use them anymore.
I don't think you can really get any sort of a signal on this?
Nobody is all that sensitive to the amount of features that get shipped in any project, and nobody really perceives how many people or how much time was needed to ship anything. As a user, unless that means a 5x difference in price of some service, you don't really see or care about any of that - and even if there were savings on the part of any developer/company, they'd probably just pocket the difference. Similarly, if there's a product or service that exists thanks to vibe coding and wouldn't have existed otherwise, you probably don't know that particular detail.
Even when fuckups and bugs do happen, there's also no signal whether it's explicitly due to AI (or whether people are scapegoating it), or just management pushing features nobody wants and enshittifying products and entire industries for their own gain.
Well, maybe StackOverflow is a bit easier to host now: https://blog.pragmaticengineer.com/stack-overflow-is-almost-...
A bunch of things got obsolete with emergence of good LLMs, especially in research and working with text tasks. See usage graphs of Stackoverflow, Grammarly and others.
LLMs put the information from StackOverflow into an arguably more helpful format, but they're still heavily dependent on human input. The LLM must periodically harvest info from human communities to stay up-to-date with technological progress. If those communities die, the LLM will not compensate, and other communities will arise to replace them. Those communities may have different attitudes towards the LLMs that killed their ancestors.