[getnormality]

Blog posts by authors claiming AI has transformed them into godlike engines of productivity: 103728369129

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

[hu3]

- learning: easier

- 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

[perrygeo]

Doing things "faster" and "easier" is an interesting way to put it. It places all of the value on one's personal experience of using the AI, and completely ignores the quality of the thing produced. Which explains why most stuff produced by LLMs is throwaway garbage! It only reinforces the parent comment - there is virtually no emphasis on making things "better".

[luckys]

There is a funny, deep observation made by The Good Place character Michael (a non-human) that has stuck with me since. He says that humans took ice cream, which was perfect, and "ruined it a little" to invent frozen yogurt, just so they could have more of it. There's supposedly a 'guilt' angle there somewhere but I never felt guilty for eating "too much" ice cream so can't relate.

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.

[skeledrew]

There won't even be a quality conversation if a thing isn't built in the first place, which is the tendency when the going is slow and hard. AI makes the highly improbable very probable.

[perrygeo]

I agree. I think this is the LLM superpower: making quick prototypes that allow us to speak concretely about technical tradeoffs.

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.

[hu3]

Doing things faster/easier means I now do most of these things whereas I didn't before.

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.

[mysterydip]

How did you determine which answers were wrong or half-truths?

[hu3]

By looking at the code?

> 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.

[candiddevmike]

I feel like the things I've built have gotten better since ChatGPT, but I don't use LLMs, just iterating and realizing how naive/terrible my old code is. Maybe I should write a blog post on How I (Don't) Use LLMs for Coding.

[tjr]

I don't think it's quite at trillions to zero, but I do think the numbers are way, way out of balance so far. I'm still at the point where, if AI disappeared tomorrow, I would be, at worst, mildly inconvenienced.

[frizlab]

> if AI disappeared tomorrow, I would be, at worst, mildly inconvenienced

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!

[LEDThereBeLight]

It’s not a helpful comparison because it’s too early. If the first iPhone went away, no one would care. Once software is rearchitected around AI, it will look a lot different. Your phone won’t need UIs that are as complex, because we can just tell AI what to change or open or do.

[marginalia_nu]

To be fair there is this persistent paradox about programming methodologies is that no matter how much they seem to speed you up, or how effective they seem to be at reducing bugs, this doesn't seem to give you any material competitive advantage over companies going for the most conservative language and methodology choices.

[AnimalMuppet]

It's almost like writing the code isn't the hard part.

[ojr]

Google Search has gotten better unless you think AI mode is a downgrade, the alternative of having a wikipedia article, reddit post or random website as the first result is not better technically maybe morally for you but not matter of factually. The average user does less manual filtering.

[nicoburns]

I definitely think the AI mode is a downgrade. It has me seriously considering abandoning Google for different search engine. With a reddit post or a Wikipedia article, it's much easier to assess the credibility of the content.

The AI mode does at least attempt to list it's sources, but it's extra hoops to jump through.

[ojr]

For the average Google User, searching for things like who perform in the Superbowl it is not extra hoops and incredibly fast. It's going to power Siri soon, enjoy.

[elorant]

AI overview though is crap. It almost always gives wrong answers and contradicts things that are in the results.

[ojr]

hasn't been my experience, I am able to search for information faster, speed to correct answer has increased on average, I feel, if we start providing examples your argument starts to fall fast. Think about the average Google Search, you really think it gets it wrong? Your search query is probably more obscure than mainstream web users.

[misnome]

I’d infinitely prefer a relevant wikipedia article to an AI “Answer” that is almost always wrong.

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.

[ojr]

almost always wrong is just incorrect. Ask it who made Hackernews and it says Paul Graham with a informational paragraph it scraped from Wikipedia, without me clicking into Wikipedia. I can provide so many examples.

[snarf_br]

Factually and environmentally as well.

[ojr]

I guess all the publishers and advertisers are worried and complaining about nothing

[bdangubic]

> Software and online things I've used that seem to be better than they were before

I would not know if they have gotten better or worse cause I don’t use them anymore.

[daturkel]

Notion AI is pretty great for both search and writing.

[snicky]

I agree with you in general, but come on - learning is easier (unless you need to dive into highly specialized stuff), writing shorter chunks of code is faster, simple photo editing ("remove this and that from the background") doesn't need any skills now. Image generation isn't terribly too if you put some effort and don't stick with the same 3-4 drawing styles that all the cheapskate companies use.

[KronisLV]

> Software and online things I've used that seem to be better than they were before ChatGPT was introduced: 0

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-...

[ivanjermakov]

> things I've used that seem to be better than they were

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.

[getnormality]

"Obsolete" is an incomplete characterization of the state of play.

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.