As a layman I don’t have a clear picture of how to start doing that. How would it differ from this? Looks like you can find the paper in question here (WARNING: out-of-date 2002 content).
I’d say nobody does! But a little less glibly, I personally think the most productive strategy in biologically-inspired AGI would be to focus on tools that help quantify the unquantified. There are substantial side-benefits to such a focus on tools: what you make can be of shorter-term practical significance, and you can test your assumptions.
Chalmers and Tononi have done some interesting work, and Tononi’s work has also had real-world uses. I don’t see Tononi’s work as immediately applicable to FAI research but I think it’ll evolve into something that will apply.
It’s my hope that the (hypothetical, but clearly possible) “qualia translation function” I mention above could be a tool that FAI researchers could use and benefit from regardless of their particular architecture.
As a layman I don’t have a clear picture of how to start doing that. How would it differ from this? Looks like you can find the paper in question here (WARNING: out-of-date 2002 content).
I’d say nobody does! But a little less glibly, I personally think the most productive strategy in biologically-inspired AGI would be to focus on tools that help quantify the unquantified. There are substantial side-benefits to such a focus on tools: what you make can be of shorter-term practical significance, and you can test your assumptions.
Chalmers and Tononi have done some interesting work, and Tononi’s work has also had real-world uses. I don’t see Tononi’s work as immediately applicable to FAI research but I think it’ll evolve into something that will apply.
It’s my hope that the (hypothetical, but clearly possible) “qualia translation function” I mention above could be a tool that FAI researchers could use and benefit from regardless of their particular architecture.