Keep on to blur preview images; turn off to show them clearly
Fourth, it might really solve the issue with AI and copyrighted content: If cognitive core does not contain representations of copyrighted works, control will be back in hands of IP owners. E.g. they can sell "cartridges" or content licenses if they choose.
Blockchain tech guy, made world's first token wallet and decentralized exchange protocol in 2012; CTO ChromaWay / Chromia
pre-processed thoughts verifiable. As a user might not want a "brain implant" for their AI which gives it skill but also shills specific products (or ideology).
Fourth, it might really solve the issue with AI and copyrighted content: If cognitive core does not contain representations of copyrighted works, control will be back in hands of IP owners. E.g. they can sell "cartridges" or content licenses if they choose.
What if we live in a world where optimal AI is a small "cognitive core" which can dynamically acquire knowledge and skills needed to perform a task? That have been suggested by Andrej Karpathy, Sam Altman and others. I tried to outline future AI landscape under condition
"small but very powerful AI" vision is fully realized, here: https://t.co/mRCG9J8A7F First, Karpathy described it as "the race for LLM "cognitive core"", but it would likely make big AI labs weaker as it's much more feasible to work with smaller AI models.
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