开启时会模糊预览图，关闭后正常显示
If 'cognitive core' knows only a minimum of facts, a lot of information must be included in the context, and it would much more efficient to use cartridges with pre-computed thoughts than to scan through raw documents on each query.
Moreover, previously "prefix tuning" paper demonstrated that KV-prefix can also have same effect as fine-tuning, so cartridge can also include skills, textual style, etc. And unlike LoRA adapters they are composable.
Moreover, previously "prefix tuning" paper demonstrated that KV-prefix can also have same effect as fine-tuning, so cartridge can also include skills, textual style, etc. And unlike LoRA adapters they are composable.
Blockchain tech guy, made world's first token wallet and decentralized exchange protocol in 2012; CTO ChromaWay / Chromia
I just realized that if we live in a world where Karpathy's "cognitive core" thesis (https://t.co/1RtvrEGIXd) is true in a maximal form (i.e. that cognitive core LLM is actually superior - that's how he described it in the interview with Dwarkesh P.),
then value capture in the AI market might look fundamentally different. That is, there might be a lot less value in huge "frontier" models which only the largest companies can develop. On the other hand, high-performance usage of "cognitive core" would require access
In retrospect it's hilarious that I will now never need to learn Rust
Opening portals to handheld VR at https://t.co/A2JMItorCV. Problems soluble, potential to improve invariant.
Thread
We're in a race. It's not USA vs China but humans and AGIs vs ape power centralization. @deepseek_ai stan #1, 2023–Deep Time «C’est la guerre.» ®1
time to ship
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