Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI in software engineering at Google: Progress and the path ahead

research.google

Post reply on HN
Print view View original

31–40 of 245 posts

Re: AI in software engineering at Google: Progress and the path ahead

#31

Post by endisneigh »

jstarks wrote: post #30
endisneigh wrote: post #23

Earlier quoted context omitted.

This is not true. You can’t even disable AI entirely in critique (AI suggested edits), not to mention cider. Certain aspects can be disabled but you cannot entirely remove all AI affordances. It’s force feeding. It will eventually all be opt-out. This is obvious to anyone who works at google. Again, same as force feeding of gen AI search

Do you find this problematic?

It’s usually wrong. Use Gemini if you want a preview.

I don’t mind optionality, but it can’t be disabled so it’s annoying.

Re: AI in software engineering at Google: Progress and the path ahead

#32

Post by irrational »

bongodongobob wrote: post #24
jprete wrote: post #6

Earlier quoted context omitted.

This isn't a good trend. Reviewers never have the depth of knowledge or understanding of authors.

Right because it's impossible for people to learn things themselves. Knowledge must only be passed down by The Gatekeeper. I'm starting to feel like the programming community is just mad things are easier to learn now.

Are they learning? Or are they just accepting the results, as long as it appears to more or less do what they want, and moving on?

The danger seems to be code that is syntactically correct and compiles without errors, but is logically incorrect.

Re: AI in software engineering at Google: Progress and the path ahead

#34

Post by zackproser »

After reading this I'm wondering how the indy code autocomplete tools are going to be able to compete longterm with this giant feedback rich data machine Google has built...do engineering orgs of sufficient scale ultimately hoard their tooling for competitive advantage, thereby leaving independent players to cater to developers outside of Google? Feels like yes...but plenty of inventions trickle out in various forms.

Re: AI in software engineering at Google: Progress and the path ahead

#35

Post by scarmig »

bigiain wrote: post #14

I'm looking forward to the day that some spicy autocomplete regurgitates an obvious chunk of AGPL code that it's stolen without permission or attribution - and it ends up in some critical part of Googles money printing machine, and the outside world finds out about it. I'm gonna need a _lot_ of popcorn.

I wouldn't be surprised if the sole training data for autocompletes was google3. It's an absolutely massive codebase, using the libraries and patterns Googlers use, and more or less entirely safe to train on. Any training data beyond that would be whitelisted by legal.

Re: AI in software engineering at Google: Progress and the path ahead

#37

Post by refulgentis »

jprete wrote: post #28
refulgentis wrote: post #17

Earlier quoted context omitted.

Source? This is unintuitive to me, I can't come up with a rationale.

I know of no review process that produces the same level of understanding as does authorship, because the author must build the model from scratch and so must see all the details, while the reviewer is able to do less work because they're fundamentally riding on the author's understanding. In fact, in a high-trust system, e.g. a good engineering culture in a tech company, the reviewer will learn even less, because th…

So the software lifecycle ends up with a sort of Zeno's paradox, each incremental maintainer understands the system less...fascinating, ty!

Re: AI in software engineering at Google: Progress and the path ahead

#38

Post by nomel »

runlevel1 wrote: post #12

Humans have limited RAM, so we have to put our ideas into an external medium that can then be refined. I've been finding AI's suggestions -- even when rather wrong -- help me do that initial step faster. Which, I think, jives with their findings here.

First we extended the reach of our perception with language.

Then we extended the energy in our calories reserves with crops/livestock.

Then we extended the length of our memories with writing.

Then we extended the breadth of our thinking with AI?

Re: AI in software engineering at Google: Progress and the path ahead

#39

Post by gerdesj »

runlevel1 wrote: post #12

Humans have limited RAM, so we have to put our ideas into an external medium that can then be refined. I've been finding AI's suggestions -- even when rather wrong -- help me do that initial step faster. Which, I think, jives with their findings here.

"Humans have limited RAM"

I would suggest we have flexible RAM. Also, we have an awful lot of it. The analogy breaks down as soon as you look at it too seriously!

In IT we largely deal with compute, persistent storage and non-persistent storage. Roughly speaking: CPU, RAM, HDD. In humans we might be considered to have similar "abilities" but unlike IT there is a mostly a single thing that performs all of those functions - the brain. That organ is both compute and storage.

LLMs can be surprisingly useful but they are a tool. As with all tools they can be abused and no doubt you have spotted all those tech blogs that spout the same old thing and often with subtle failings (hallucinations).

Keep your tools sharp and know how to safely use sharp tools.

Re: AI in software engineering at Google: Progress and the path ahead

#40

Post by hombre_fatal »

irrational wrote: post #32
bongodongobob wrote: post #24

Earlier quoted context omitted.

Right because it's impossible for people to learn things themselves. Knowledge must only be passed down by The Gatekeeper. I'm starting to feel like the programming community is just mad things are easier to learn now.

Are they learning? Or are they just accepting the results, as long as it appears to more or less do what they want, and moving on? The danger seems to be code that is syntactically correct and compiles without errors, but is logically incorrect.

This is just how learning happens either way.

As a noob I copied code from Railscasts or Stack Overflow or docs or IRC without understanding it just to get things working. And then at some point I was doing less and less of it, and then rarely at all.

But what if the code I copied isn't correct?! Didn't the sky fall down? Well, things would break and I would have to figure out why or steal a better solution, and then I could observe the delta between what didn't work vs what worked. And boom, learning happened.

LLMs just speed that cycle up tremendously. The concern trolling over LLMs basically imagines a hypothetical person who can't learn anything and doesn't care. More power to them imo if they can build what they want without understanding it. That's a cracked lazy person we all should fear.

Post reply on HN