>OpenAI and its partner Microsoft investigated accounts believed to be DeepSeek’s last year that were using OpenAI’s application programming interface (API) and blocked their access on suspicion of distillation that violated the terms of service, another person with direct knowledge said. These investigations were first reported by Bloomberg.
If Deepseek trained off OpenAI, then it wasn't trained from scratch for "pennies on the dollar" and isn't the Sputnik-like technical breakthrough that we've been hearing so much about. That's the news here. Or rather, the potential news, since we don't know if it's true yet.
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When you take both of these points and put them back to back, a natural answer seems to suggest itself which I'm not sure the authors intended to imply: R1 attempted to use o1 to make its answers seem more human, and as a result it accidentally picked up most of it's reasoning capabilities in the process. Is my reading totally off?
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Another issue I have is the reliance on reflection. In general, I think if you have to rely on reflection to do something, that usually means you're working around some inherent limitation in the normal language - and the resulting code is often far less readable than the code would be in a more expressive language. Lots of Go libraries and frameworks are forced to use it in a lot of cases because there's just no other way to express some really basic things without it.
I really want to like Go. There's a lot I like - the "only one way to do something" approach means that code always feels consistent. Errors as values is a far superior approach to exceptions. I had to write some for a job interview project a while back and it felt really refreshing, but every time I try to use it for a personal project, I don't feel like I'm getting anything out of it that I couldn't get out of say, Rust, or modern, typed Python.