Apple didn't even have an AppStore in mind until people started hacking apps onto it.
Remember back in 2007 when Apple first told developers that to develop for the iPhone, they’d need to build WebApps for Safari? Well, that really was the plan. At the time, Jobs said:
The full Safari engine is inside of iPhone. And so, you can write amazing Web 2.0 and Ajax apps that look exactly and behave exactly like apps on the iPhone. And these apps can integrate perfectly with iPhone services. They can make a call, they can send an email, they can look up a location on Google Maps.
And guess what? There’s no SDK that you need! You’ve got everything you need if you know how to write apps using the most modern web standards to write amazing apps for the iPhone today. So developers, we think we’ve got a very sweet story for you. You can begin building your iPhone apps today.
The App Store came later and apparently as a reaction to jailbreakers and developer backlash.
According to the biography, Jobs’ longstanding animus toward Adobe helped form his vision for Apple’s tightly controlled mobile environment.
In 1999, he was flatly denied when he asked Adobe to create a version of its popular Adobe Premiere digital-graphics software for the Mac. Adobe also wouldn’t rewrite Photoshop for the Mac’s operating system, even though Macs were popular with designers.
“My primary insight when we were screwed by Adobe in 1999 was that we shouldn’t get into any business where we didn’t control both the hardware and the software, otherwise we’d get our head handed to us,” Jobs said, according to Isaacson.
The two companies go back together even further. Apple invested in Adobe in 1985 and they worked together early on. But Jobs, who in Isaacson’s book comes off sometimes as vindictive and brusque as he was innovative and inspirational, told Isaacson that Adobe went downhill after founder John Warnock retired.
“The soul of Adobe disappeared when Warnock left,” he said. “He was the inventor, the person I related to. It’s been a bunch of suits since then, and the company has turned to crap.
Very OT, but can I say i’ve seen this happen at every company i’ve been? When the founder(s) get out of the picture they kinda bring the soul of the company with them.
Yeah there’s a fading halo still in the air for a while, but it’s just that: a fading halo.
For production, route requests through your own back end with .proxied. The relay at baseURL adds the Claude API credential server-side, so the app ships no key. The headers you provide are sent on every request so your proxy can authorize the caller.
I'm a strong proponent of Open Source (TM) but I disagree with this take.
The weights are the useful artifact here. You can modify them, fine tune them and do what you want with them.
Unlike binary software there is nothing limiting that.
It is also useful to have access to the training recipes and to some extent the data. But I'm of the opinion that learning on something is not copyright infringement, so there are many circumstances where distributing the raw training data will not be possible.
For me this is like Open Office: it is open source, and largely inspired by and learned from Microsoft Office. But they don't need to distribute MS Office for Open Office to be Open Source.
In addition there are models that meet the criteria you appear to propose. The AllenAI models are a good example.
The analogy falls apart very quickly. Without the training data, your modifications amount to virtually nothing compared to what these "versions" are, and the idea that you can maintain and improve on these models without the continual support of the company that owns the training data AND harnesses AND in general build instructions is not very credible. This is why it's not rare that they "dump" old versions as freeware but at some point switch to not distributing them, and mostly get away with it. As this is really not open, and the threat of an effective fork is therefore non-existent, the pressure for any one who has released freeware models to "go SaaS" is too high.
While if "Open Office" switches to a more problematic license at some point, the existing source has all you need for an organization to support the project without regard to the original company (this has happened already!). If Qwen decides to stop distributing models for download, you're basically stuck, _even_ if you have unlimited resources, it's not clear how the released weights help you; your best bet is to start almost from scratch. This has also happened...
These models are not "Open" by any definition of the word. It is just freely redistributable. You can justify yourself in whatever way you want re a cowboy approach to copyright, but this doesn't change the fact that this is not open, and has almost none of the benefits of open, and therefore it is a huge abuse of the word "Open".
Ironically about the only thing that is copyrightable here is the sum of the training data (possibly) _AND_ the software used to build the model (most definitely). The model itself most likely isn't (databases are not copyrightable), which makes it even more pointless to abuse the word "open" for it. All the value is in the former two.
> The analogy falls apart very quickly. Without the training data, your modifications amount to virtually nothing compared to what these "versions" are, and the idea that you can maintain and improve on these models without the continual support of the company that owns the training data AND harnesses AND in general build instructions is not very credible.
This is completely wrong, and sort of shows why what you are saying is not a problem at all.
You can post-train any LLM very easily without access to the original training data.
People do it all the time.
Cursor post-training Kimi K2 is a great example.
> If Qwen decides to stop distributing models for download, you're basically stuck, _even_ if you have unlimited resources, it's not clear how the released weights help you; your best bet is to start almost from scratch.
What are you talking about? You just post-train it.
There is exactly zero different before and after they stop distributing it. People don't have access to the training data now (when they are distributing it) and post train very successfully.
Not most of the time (pre-training takes a long time), but post-training is where most of the value is, yes.
Famously it is all that OpenAI did between GPT 4o and GPT 5.3 (or 5.2?) - they didn't manage to complete a pre-training run[1], and all their progress was done with post-training (!)
Post training what Cursor spends their time doing, and that has built a model that is competitive with the best coding models out there.
It isn't limited at all.
If you want to complain about something not being open source, complain about the lack of good open source RL environments (Prime Intellect excepted).
When kubernetes was released there were very few people who could run it, and even less that could run it usefully.
Right now there a few people who can run a 1T model at home, even less who can run a 5T model and probably single digits who can run a 10T model.
But if an open source 10T model was available you can be sure people would find new ways to quantize it, new ways to configure hardware and and new ways to think about problems that would make it useful.
1T+ models (Deepseek v4, Kimi K2.6 etc) are available as open weights now, and for ~$5000-$10000 you can run them usefully at home. 2 years ago no on was contemplating that.
$250K to run a 10T model might be possible now. There are many companies that will pay that, and that will push the tools and techniques downwards for the rest of us.
They have spoken publicly about how they want open models banned (they call them Chinese models).
They might not want this specific action, but they do want regulation on their own terms. That really is regulatory capture.
> Nobody is doing this intentionally. Have you not paid attention to how quickly idiot stuff gets found out
They don't think is is "idiot stuff" - they are doing it openly and shouting to everyone who will listen! Read Dario's latest essay[1]:
> Many policymakers are showing increased openness to taking action, and it's been encouraging to see our peers come around to the same positions we've been advocating for over the past few years.
[snip]
> Thus, in 2025, Anthropic supported transparency legislation, helping to pass SB 53 in California, RAISE in NY, SB 315 in Illinois (in early 2026), and advocating for a transparency standard at the federal level.
[snip]
> It is time to go beyond transparency to more serious and binding regulation of AI.
> I am grateful to see the Trump administration’s Executive Order move incrementally towards a greater role for government in AI, though Anthropic’s proposal recommends even further action.
> The government should have the power to block or deter deployment of the model if it is determined, in light of third-party assessment, to present unacceptable risks.
I'm not sure why you think they don't want to be "found out"!
https://sebastianraschka.com/llms-from-scratch/ch04/08_delta...
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