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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#731

Post by TheRealPomax »

ahoka wrote: post #189
TheRealPomax wrote: post #68

Earlier quoted context omitted.

You mean waste a few billion on buying a company that couldn't compete with the market anymore because the iphone made "even an idiot should be able to use this thing, and it should be able to do pretty much everything" a baseline expectation with an OS/software experience to match? Nokia failed Nokia, and then Microsoft gave it a shot. And they also couldn't make it work. (sure, that glosses over the whole Elop saga…

I can see why people would think that, but Microsoft did not buy Nokia.

time to revisit the news from back in the day, because they very much did, and the details are an exercise in "wow, how much do you want to split hairs?".

Re: GitHub cuts AI deals with Google, Anthropic

#732

Post by th0ma5 »

elliotto wrote: post #707
simonw wrote: post #704

Earlier quoted context omitted.

Did you dismiss two years of my accumulated writing about LLMs as "tutorial regurgitation"? Maybe you clicked the link to my series of posts that are in chronological order - https://simonwillison.net/series/using-llms/ - looked at the very first one about trying out GPT-3 from June 2022 and stopped reading. I probably shouldn't share that link any more!

I'm a big fan of your blog simonw, and it's interesting to see how a few of the people you've responded to here aren't receptive at all to your responses. I have become somewhat convinced that the 'ai doesn't help with programming crowd' is a little bit obtuse / entirely unwilling to experiment with new tools. It seems too much of a coincidence to see the same crowd that you've responded to struggle to perform basic…

I keep experimenting because of comments like this and they still always have the same problems:

- Inability to stay self-consistent

- Random extra unused and unreachable code

- Constant wack a mole with issues they have

- Random opposite or adjacent thinking

- Assuming that how things work in one library or language must work the same in another

I then had someone say well... Just break up the work, but, that's also not what people say works for them, and also, you still have to side-eye the smaller stuff and it just gets exhausting.

A ton of studies show that if you know less than 80 about a field it'll get you to that 80 percent. And if you know more than that it'll bring you back down to 80% due to randomness, lack of data in the training, incompleteness in the model that your incomplete prompt amplifies, and just automation bias errors where you trusted something it did that you shouldn't have.

I would say that anyone claiming these things do everything are just simply new to systems.

Re: GitHub cuts AI deals with Google, Anthropic

#733

Post by nwienert »

anonzzzies wrote: post #552
nwienert wrote: post #487

Earlier quoted context omitted.

It’s really far from mid level. It’s a weird mix of expert at things it trained on, and complete misleading idiot at anything outside. For a bash script or the first steps of something simple it’s great. For anything complex at all it’s worse than nothing.

Works well for us nonetheless, also on more complex things. It's not worse than most (including seniors) humans I worked with in the past 40 years, but it is faster and cheaper. On HN it is sometimes forgotten that by far most programmers do not like it; they need money. If you see what comes out of them, you have to puke; yet it's running billion$ businesses and works surprisingly well considering the bad code quali…

It's quite literally incapable of solving many very mid-level things, no matter how much you help it. It's not a reasoning machine, it's basically a different way to search existing answers.

Re: GitHub cuts AI deals with Google, Anthropic

#734

Post by scubbo »

mikeshi42 wrote: post #514
scubbo wrote: post #479

Earlier quoted context omitted.

> Me reviewing AI code is no different from me reviewing anyone else's code. I take your point, and on the whole I agree with your post, but this point is fundamentally _not_ correct, in that if I have a question about someone else's code I can ask them about their intention, state-of-mind, and understanding at the time they wrote it, and (subjectively, sure; but I think this is a reasonable claim) can _usually_ dete…

I'm assuming by bullshitting you mean differentiating between LLM hallucinations and a human with low confidence in their code. I've found that LLMs do sometimes acknowledge hallucinations. But really the check is much easier than a PR/questioning an author - just run the code given by the copilot and check that it works, just as if you typed it yourself.

> just run the code given by the copilot and check that it works

You've misunderstood my point. I'm not discussing the ability to check whether the code works as _I_ believe it should (as you say, that's easy to verify directly, by execution and/or testing); I'm referring to asking about intention or motivation of design choices by an author. Why this data structure rather than that one? Is this unusual or unidiomatic construction necessary in order to work around a quirk of the problem domain, or simply because the author had a brainfart or didn't know about the usual style? Are we introducing a queue here to allow for easy retries, or to decouple scaling of producers and consumers, or...? I can't evaluate the correctness of a choice without either knowing the motivation for it, or by learning the problem domain well enough to identify and make the choice myself - at which point the convenience of the AI solution is abnegated because I may as well have written it myself.

(ref: "Code only says what it does" - https://brooker.co.za/blog/2020/06/23/code.html)

And, yes, you can ask an LLM to clarify or explain its choices, but, like I said, the core problem is that they will confidently and convincingly lie to you. I'm not claiming that humans never lie - but a) I think (I hope!) they do it less often than LLMs do, and b) I believe (subjectively) that it tends to be easier to identify when a human is unsure of themself than when an LLM is.

Re: GitHub cuts AI deals with Google, Anthropic

#735

Post by mikeshi42 »

scubbo wrote: post #734
mikeshi42 wrote: post #514

Earlier quoted context omitted.

I'm assuming by bullshitting you mean differentiating between LLM hallucinations and a human with low confidence in their code. I've found that LLMs do sometimes acknowledge hallucinations. But really the check is much easier than a PR/questioning an author - just run the code given by the copilot and check that it works, just as if you typed it yourself.

> just run the code given by the copilot and check that it works You've misunderstood my point. I'm not discussing the ability to check whether the code works as _I_ believe it should (as you say, that's easy to verify directly, by execution and/or testing); I'm referring to asking about intention or motivation of design choices by an author. Why this data structure rather than that one? Is this unusual or unidiomati…

> I can't evaluate the correctness of a choice without either knowing the motivation for it, or by learning the problem domain well enough to identify and make the choice myself - at which point the convenience of the AI solution is abnegated because I may as well have written it myself.

I think I usually accept code that is in the latter - the convenience is I did not need to spend any real energy implementing the solution or thinking too deeply about it. Sometimes the LLM will produce a more interesting approach that I did not consider initially but is actually nicer than what I wanted to do (afaik). Often it does what I want or something similar enough to what I would've written - just that it can do it instantly instead of me manually typing, doc searching, adding types, and correcting the code. If it does something weird that I don't agree with, I instead modify the prompt to align closer to the solution I had in mind. Much like Google, sometimes the first query does not do the trick and a query reformulation is required.

I wouldn't trust an LLM to write large chunks of code that I wouldn't have been able to write/figure out myself - it's more of a coding accelerant than an autonomous engineer for me (maybe that's where our PoVs diverged initially).

I suspect the similarity with PRs is that when I'm assigned a PR, I generally have enough knowledge about the proposed modification to have an opinion on how it should be done and the benefits/drawbacks of each implementation. The divergence from a PR is that I can ask the LLM for a modification of approach with just a few seconds and continue to ask for changes until I'm satisfied (so it doesn't matter if the LLM chose an approach I don't understand - I can just ask it to align with the approach I believe is optimal).

Re: GitHub cuts AI deals with Google, Anthropic

#736

Post by eru »

patrickk wrote: post #520
eru wrote: post #458

Earlier quoted context omitted.

I had the opposite experience lately: I was helping translate some UI text for a website from English to German, my mother tongue. I found that usually the machine came up with better translations than me.

English and German are EU languages. Russian is not. The EU maintains a large translation service to translate most EU official texts into all EU languages. So Google Translate is using that to train on. Google gets a free gift from a multinational bureaucracy and gets to look like a smart company in the process. This is also why English-Mandarin is often poorly translated, in my opinion.

> Google gets a free gift from a multinational bureaucracy and gets to look like a smart company in the process.

Luckily, that gift is available for free to everyone. So it seems like a half-decent thing to do with tax payer money.

Re: GitHub cuts AI deals with Google, Anthropic

#737

Post by bastardoperator »

creata wrote: post #726
bastardoperator wrote: post #721

Earlier quoted context omitted.

Some? So you're not even aware. They're the largest OSS company in the history of OSS even if you don't like it. That's the link you're obviously missing.

I'm going to pretend for my sanity's sake that you're joking.

Who's bigger, I'll wait.

Re: GitHub cuts AI deals with Google, Anthropic

#738

Post by tripzilch »

patrickk wrote: post #520
eru wrote: post #458

Earlier quoted context omitted.

I had the opposite experience lately: I was helping translate some UI text for a website from English to German, my mother tongue. I found that usually the machine came up with better translations than me.

English and German are EU languages. Russian is not. The EU maintains a large translation service to translate most EU official texts into all EU languages. So Google Translate is using that to train on. Google gets a free gift from a multinational bureaucracy and gets to look like a smart company in the process. This is also why English-Mandarin is often poorly translated, in my opinion.

> Google gets a free gift from a multinational bureaucracy and gets to look like a smart company in the process

it would have cost you exactly nothing to not make an unnecessary dig at Europeans, here

Re: GitHub cuts AI deals with Google, Anthropic

#739

Post by tripzilch »

dools wrote: post #452
0xFACEFEED wrote: post #329

Earlier quoted context omitted.

As a programmer of over 20 years - this is terrifying. I'm willing to accept that I just have "get off my lawn" syndrome or something. But the idea of letting an LLM write/move large swaths of code seems so incredibly irresponsible. Whenever I sit down to write some code, be it a large implementation or a small function, I think about what other people (or future versions of myself) will struggle with when interactin…

> But the idea of letting an LLM write/move large swaths of code seems so incredibly irresponsible I heard a similar thing from a dude when I said I use it for bash scripts instead of copying and pasting things off StackOverflow. He was a bit "get off my lawny" about the idea of running any code you didn't write, especially bash scripts in a terminal. It is obviously the case that I didn't write most of the code in t…

> if I'm working on a team and people are writing code how is it any different? Everyone makes mistakes, I make mistakes.

because your colleagues know how to count

and they're not hallucinating while on the job

and if they try to slip an unrelated and subtle bug past you for the fifth time after asking them to do a very basic task, there are actual consequences instead of "we just need to check this colleague's code better"

Re: GitHub cuts AI deals with Google, Anthropic

#740

Post by tripzilch »

Cthulhu_ wrote: post #627
scubbo wrote: post #479

Earlier quoted context omitted.

> Me reviewing AI code is no different from me reviewing anyone else's code. I take your point, and on the whole I agree with your post, but this point is fundamentally _not_ correct, in that if I have a question about someone else's code I can ask them about their intention, state-of-mind, and understanding at the time they wrote it, and (subjectively, sure; but I think this is a reasonable claim) can _usually_ dete…

> Asking AI for explanations tends to lead to extremely convincing and confident false justifications rather than an admission of error or doubt. Not always true, AI can realise their own mistakes and they can learn. It's a feedback loop system, and / but as it stands this feedback of what is good and bad is provided by end-users and fed back into e.g. Copilot.

> AI can realise

wait did AGI happen? which AI is this?

stop anthropomorphizing them

No they can't. They can generate text that indicates they hallucinated, you can tell them to stop, and they won't.

They can generate text that appears to admit they are incapable of doing a certain task, and you can ask them to do it again, and they will happily try and fail again.

Sorry but give us some examples of an AI "realizing" its own mistakes, learning, and then not making the mistake again.

Also, if this were even remotely possible (which it is not), then we should be able to just get AIs with all of the mistakes pre-made, so it learned and not do them again, right? So it has already "realized" and "learned" which tasks it's incapable of, so it will actually refuse or find a different way.

Or is there something special about the way that _you_ show the AI its mistakes, that is somehow more capable of making it "learn" from those mistakes than actually training it?

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