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GitHub cuts AI deals with Google, Anthropic

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Re: GitHub cuts AI deals with Google, Anthropic

#281

Post by dbmikus »

olivermuty wrote: post #242
MangoCoffee wrote: post #229

Earlier quoted context omitted.

Time will tell. As a GitHub Copilot user, I still review the code. SpaceX's advancements are impressive, from rocket blow up to successfully catching the Starship booster. Who knows what AI will be capable of in 5-10 years? Perhaps it will revolutionize code assistance or even replace developers

Except cursor is the fireworks based on black powder here. It will look good, but as a technology to get you to the moon it seems to look like a dead end. NOTHING (of serious science) seems to indicate LLMs being anything but a dead end with the current hardware capabilites. So then I ask: What, in qualitative terms, makes you think AI in the current form will be capable of this in 5 or 10 years? Other than seeing th…

If you look at LLM performance on benchmarks, they keep getting better at a fast rate.[1]

We also now have models of various sizes trained in general matters, and those can now be tuned or fine-tuned to specific domains. The advances in multi-modal AI are also happening very quickly as well. Model specialization, model reflection (chain of thought, OpenAI's new O1 model, etc.) are also undergoing rapid experimentation.

Two demonstrable things that LLMs don't do well currently, are (1) generalize quickly to out-of-distribution examples, (2) catch logic mistakes in questions that look very similar to training data, but are modified. This video talks about both of these things.[2]

I think I-JEPA is a pretty interesting line of work towards solving these problems. I also think that multi-modal AI pushes in a similar direction. We need AI to learn abstractions that are more decoupled from the source format, and we need AI that can reflect and modify its plans and update itself in real time.

All these lines of research and development are more-or-less underway. I think 5-10 years is reasonable for another big advancement in AI capability. We've shown that applying data at scale to simple models works, and now we can experiment with other representations of that data (ie other models or ways to combine LLM inferences).

[1]: https://www.anthropic.com/news/3-5-models-and-computer-use [2]: https://www.youtube.com/watch?v=s7_NlkBwdj8

Re: GitHub cuts AI deals with Google, Anthropic

#282

Post by pavelboyko »

I mentored junior SWE and CS students for years, and now using Claude as a coding assistant feels very similar. Yesterday, it suggested implementing a JSON parser from scratch in C to avoid a dependency -- and, unsurprisingly, the code didn’t work. Two main differences stand out: 1) the LLM doesn’t learn from corrections (at least not directly), and 2) the feedback loop is seconds instead of days. This speed is so convenient that it makes hiring junior SWEs seem almost pointless, though I sometimes wonder where we’ll find mid-level and senior developers tomorrow if we stop hiring juniors today.

Re: GitHub cuts AI deals with Google, Anthropic

#283

Post by nrclark »

Nevermark wrote: post #273
enneff wrote: post #266

Earlier quoted context omitted.

That’s the thing, isn’t it? The craft of programming in the small is one of being intimate with the details, thinking things through conscientiously. LLMs don’t do that.

Perhaps it should be prompted to then? Ask it to review its own code for any problems? Also identify typical and corner cases and generate tests? Question marks here because I have not used the tool. The size & depth of each accepted code step is still up to the developer slash prompter

I use Chatgpt for coding / API questions pretty frequently. It's bad at writing code with any kind of non-trivial design complexity.

There have been a bunch of times where I've asked it to write me a snippet of code, and it cheerfully gave me back something that doesn't work for one reason or another. Hallucinated methods are common. Then I ask it to check its code, and it'll find the error and give me back code with a different error. I'll repeat the process a few times before it eventually gets back to code that resembles its first attempt. Then I'll give up and write it myself.

As an example of a task that it failed to do: I asked it to write me an example Python function that runs a subprocess, prints its stdout transparently (so that I can use it for running interactive applications), but also records the process's stdout so that I can use it later. I wanted something that used non-blocking I/O methods, so that I didn't have to explicitly poll every N milliseconds or something.

Re: GitHub cuts AI deals with Google, Anthropic

#284

Post by gkbrk »

metalliqaz wrote: post #172
SV_BubbleTime wrote: post #133

Earlier quoted context omitted.

I asked Claude a physics question about bullet trajectory and it refused to answer. Restricted too far imo.

couldn't you s/bullet/ball/ ? or s/bullet/arrow/ ?

You could, but you could also use a model that's not restricted so much that it cannot do simple tasks.

Re: GitHub cuts AI deals with Google, Anthropic

#285

Post by fullstackwife »

thih9 wrote: post #221

I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…

One of the reasons for that may be the price: large code changes with multi turn conversation can eat up a lot of tokens, while those tools charge you a flat price per month. Probably many hacks are done under the hood to keep *their* costs low, and the user experiences this as lower quality responses.

Still the "architecture and core libraries" is rather corner case, something at the bottom of their current sales funnel.

also: do you really want to get equivalent of 1 FTE work for 20 USD per month?:)

Re: GitHub cuts AI deals with Google, Anthropic

#286

Post by hypeatei »

pavelboyko wrote: post #282

I mentored junior SWE and CS students for years, and now using Claude as a coding assistant feels very similar. Yesterday, it suggested implementing a JSON parser from scratch in C to avoid a dependency -- and, unsurprisingly, the code didn’t work. Two main differences stand out: 1) the LLM doesn’t learn from corrections (at least not directly), and 2) the feedback loop is seconds instead of days. This speed is so co…

Years of experience doesn't correlate to a good developer either. I've seen senior devs using AI to solve impossible problems, for example asking it how to store an API key client side without leaking it...

Re: GitHub cuts AI deals with Google, Anthropic

#287

Post by ianeigorndua »

candiddevmike wrote: post #126
ianeigorndua wrote: post #86

Earlier quoted context omitted.

How many OSS repositories do I personally have to read through for my own code to be considered stolen property? That line of thought would get thrown out of court faster than an AI would generate it.

Can I copy you or provide you as a service? To me, the argument is a LLM learning from GPL stuff == creating a derivative of the GPL code, just "compressed" within the LLM. The LLM then goes on to create more derivatives, or it's being distributed (with the embedded GPL code).

That’s what my employers keep asking.

Re: GitHub cuts AI deals with Google, Anthropic

#289

Post by azemetre »

sebzim4500 wrote: post #109
mmaunder wrote: post #108

History has shown being first to market isn't all it's cut out to be. You spend more, it's more difficult creating the trail others will follow, you end up with a tech stack that was built before tools and patterns stabilized and you've created a giant super highway for a fast-follower. Anyone remember MapQuest, AltaVista or Hotmail? OpenAI has some very serious competition now. When you combine that with the recent…

Claude is better than OpenAI for most tasks, and yet OpenAI has enormously more users. What is this, if not first mover advantage?

Honestly I think the biggest reason for this is that Claude requires you to login via an email link whereas OpenAI will let you just login with any credentials.

This matters if you have a corporate machine and can't access your personal email to login.

Re: GitHub cuts AI deals with Google, Anthropic

#290

Post by samatman »

hi41 wrote: post #249
gregschlom wrote: post #211

Earlier quoted context omitted.

I'm assuming you're not a native speaker? (I'm not) - "to cut a deal" is a fairly common idiom that means to reach and agreement.

That’s correct. Not a native speaker. I am not well versed with slang words. I am sometimes embarrassed because I speak as if they are words from a book instead of sounding like spoken words. Do you know how cuts came to mean that it’s a deal. For a non-native speaker it means the exact opposite thing as in “he cut a wire”. Language evolves in strange ways.

"Cut a deal" is an idiom, not slang: it's appropriate language to use in a business context, for example.

The origin is hazy, of the theories I've seen I consider this the best one: "deal" means both "an agreement" and "to distribute cards in a card game". The dealer, in the latter sense, first cuts the card deck then deals the card. "Cut and deal" -> "cut a deal".

It could also be related to "cut a check", which comes from an era before perforated paper was widespread, when one would literally cut the check out of a book of checks.

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