How do you think Apple was training internal models? They surely weren’t only using Apple employee repos, though I expect part of the problem is that there isn’t a lot of Swift out there in general.
This is purely for source code, public repos are already used for training and it’s part of the agreement when using them. If it’s not already in the Apple Developer Program paperwork I expect it will be eventually.
I understand the argument against LLMs and GenAI for art and other copyrighted work but programming is the one area I think they get a pass, pay the money and make your repo private if you don’t want it used for training – or don’t publish it. I also know that similar technology was used years ago to mitigate critical severity defects in public code, free of charge. That information isn’t out there in the world but I helped work on it. It’s not all nefarious.
Anthropic is a much better partner than the others, though I still expect Apple will eventually take all of this in-house down the road assuming the entire fad doesn’t die off within a few years.
I have enormous issues with current GenAI and have even published written work on the subject. You can search my post history here for a glimpse into that if you’re interested. I don’t think Apple will ever make a chatbot, at least with current technology, and frankly they shouldn’t.
‘Vibe coding’ and similar is only useful if you do the legwork to understand some of the LLM output, and I don’t mean error correcting I mean going and reading the documentation and understanding the language. There is use in LLMs for that, because their corpus is large for certain languages and you can get some implementation suggestions that might point you in the right direction to pursue further on your own.
People who think any of these things are going to one-shot output a program, and the developers who have tried some of these products and written them off because they couldn’t do that (and often they are prompted terribly, likely not using LoRA if at a company or MCP if an individual) are both kind of ignorant from a certain POV. There is some utility, whether it pencils out financially down the road, who knows. All of this technology is only semi-useful at best, but it doesn’t mean it isn’t worth understanding.
I wouldn’t hire someone who claimed they use GenAI but didn’t know how the models worked at a deep level. I’m talking explain the process to me on a whiteboard, from input tokens on up. If you treat it like a black box and you’re a professional in any field, frankly you’re an idiot. Just don’t use it at all in that case, I’d happily hire someone excellent who didn’t use GenAI tooling. The real problem is the enormous, horribly ignorant mass of people and professionals in the middle area – that’s where the real danger is right now.
Regardless of all of that, Apple promised Swift Assist and I think there’s nearly zero chance they could get a well-working version of it out before 2026 if it was built with entirely internal technology. Apple is making great progress but they are very focused on quantized models, that might pay off but it won’t for that feature in the way they demoed it. At least, not yet.
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