You are free to not use it. You are not free to use the API provided specifically for the product, which you are not explicitly paying for, for a different product.
You can of course use OpenCode or any other project with the API, which is also offered as a separate product. People just don't want to do that because it's not subsidized, ie. more expensive. But the entire reason it's subsidized is that Anthropic can use the data to improve their product.
> But the entire reason it's subsidized is that Anthropic can use the data to improve their product.
This is grade A, absolute crap. It's subsidized because everyone else is subsidizing it, and everyone is doing it because they are trying to lock their consumer share.
The solution is quite simple. Just get the FTC to forbid tie-in sales so that we don't get the huge corporations using their infinite resources to outlive the competition. Anthropic/Amazon/Google/OpenAI/Facebook can offer any type of service they want, but if the access to the API costs $X when offered standalone, then that is the baseline price for anything that depends on the API to work.
I'm fine with this as well. I just dislike everyone here presenting it like this is Anthropic being unreasonable. Given the product that is offered and why it's being offered, this is completely reasonable to do.
I work at a D company. We tend to use OOP only for state owners with strict dependencies, so it's rare to even get cycles. It is extremely useful for modeling application state. However, all the domain data is described by immutable values and objects are accessed via parameters as much as fields.
When commandline apps were everywhere, people dreamed of graphical interfaces. Burdened by having to also do jobs that it was bad at, the commandline got a bad reputation. It took the dominance of the desktop for commandline apps to find their niche.
In a similar way, OOP is cursed by its popularity. It has to become part of a mixed diet so that people can put it where it has advantages, and it does have advantages.
Though this is still compatible with exponential or at least superlinear capability growth if you model benchmarks as measuring a segment of the line, or a polynomial factor.
it can feed into itself and improve. the idea that self-training necessarily causes deterioration is fanfic. remember that they spend massive amounts of compute on rl.
I was curious about the scale of 1TiB of text. According to WolframAlpha, it's roughly 1.1 trillion characters, which breaks down to 180.2 billion words, 360.5 million pages, or 16.2 billion lines. In terms of professional typing speed, that's about 3800 years of continuous work.
So post-deduplication, I think it's a fair assessment that a significant portion of high-quality text could fit within 1TiB. Tho 'high-quality' is a pretty squishy and subjective term.
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