21–30 of 393 posts
I’ve been using DeepSeek v4 pro for a month now in Kilo Code and its great. Fast, reliable, large context window and cheap as… Did 1,5B tokens this month and cost me 40usd (majority cached, but still).
Is there a way to see how many tokes one does with claude code (pro)?
I second ccusage, it's nice
DeepSeek continues to not only push the boundaries but also publish these incredible papers explaining how they achieved their gains - something the American labs no longer do unfortunately. Chinese labs are doing the most interesting work in AI right now.
Publishing by necessity I wonder? American labs on the cutting edge pioneering the way forward, so Deepseek open sourcing what they’ve got is to help even the playing field. Hopefully the experts here can offer insight. The above is just my hunch and I’m not a specialist in this field.
Earlier quoted context omitted.
Probably because American AI companies are on the hook for quite a lot of investment money. I think they are trying to find the magical moat to justify their valuation. Revealing optimizations similar to these would pretty much reduce their competitive position.
Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. I suspect their tune will change if they ever take the lead..
Earlier quoted context omitted.
Probably because American AI companies are on the hook for quite a lot of investment money. I think they are trying to find the magical moat to justify their valuation. Revealing optimizations similar to these would pretty much reduce their competitive position.
Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. I suspect their tune will change if they ever take the lead..
US labs in Google, Meta and SpaceX are not leading, none of them managed to build something on par with GLM 5.2.
Care to explain to me why they still don't collaborate and still choose to do it in private?
Earlier quoted context omitted.
Probably because American AI companies are on the hook for quite a lot of investment money. I think they are trying to find the magical moat to justify their valuation. Revealing optimizations similar to these would pretty much reduce their competitive position.
Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. I suspect their tune will change if they ever take the lead..
Earlier quoted context omitted.
Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. I suspect their tune will change if they ever take the lead..
> Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. US labs in Google, Meta and SpaceX are not leading, none of them managed to build something on par with GLM 5.2. Care to explain to me why they still don't collaborate and still choose to do it in private?
DeepSeek continues to not only push the boundaries but also publish these incredible papers explaining how they achieved their gains - something the American labs no longer do unfortunately. Chinese labs are doing the most interesting work in AI right now.
Probably because American AI companies are on the hook for quite a lot of investment money. I think they are trying to find the magical moat to justify their valuation. Revealing optimizations similar to these would pretty much reduce their competitive position.
Must be wonderful to be on the board of OpenAi et al & their PE investors whilst China keeps blowing up these mines under their feet lmao. Luckily Korean pension funds will buy all the trash as usual but goddamn you gotta start moving quick or you are gonna need some serious AGI to show you how to offload those bonds
"We will build the machine-god and pray for it to pay for itself."
Earlier quoted context omitted.
Probably because American AI companies are on the hook for quite a lot of investment money. I think they are trying to find the magical moat to justify their valuation. Revealing optimizations similar to these would pretty much reduce their competitive position.
Chinese labs are also still behind, so they’re incentivized to collaborate and have no reason to do it in private. I suspect their tune will change if they ever take the lead..