The current conflict resolution is fairly simple: always trust humans, and trust recent human info more than old human info. We're very aware that as the knowledge system gets more complex, we'll need more sophistication, including: - Human-in-the-loop verification - Role-based ranking, i.e. be more skeptical when an intern contradicts the CEO

Unlike many other memory systems, Hyper never actually deletes memories. It constantly reranks them based on confidence, which factors into how they're retrieved. So every statement has a full history and system of record for how it got there, and you can trace (with attribution) why Hyper gives the answers it does. If there's something that Hyper misses, we provide tools in-app and in-terminal-plugin that let a human explicitly correct what Hyper knows.

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andy_ppp 10 days ago | parent | next [-]

The intern probably knows more about their work than the CEO in 99% of orgs. The leaf nodes who do the work know more about anything than their managers (who think they know everything but, in most organisations, understand very little). Your system must keep the managers happy to be successful, which could prove a tricky circle to square.

	▲	kanyesrthaker 9 days ago \| parent [-]
		fair enough :) that's why it's a hard problem! different people have different levels of "trustworthiness" and this is exactly the kind of implicit mental model that employees form over years of working at a company. Hyper aims to learn these things by being an active listener, and make decisions based on that knowledge.

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BillStrong 9 days ago | parent | prev [-]

That is a relatively simple system. It cuts out use cases.

For instance, history, newer information is mixed with older authoritative information.

The same thing for religious institutions, where the older items may be the more authoritative for the purposes.