Physical theories of everything

 Each of our concepts typically has some limited range of applicability.* Are there suitable** concepts that are universally valid? If not, then it might not be possible to create a single physical theory of everything. Rather, one might need a network of more limited theories, each of which has its own range of applicability. Perhaps a concept hierarchy (like the one A.s.a. H. creates) with theories summarizing the patterns that are seen in various portions of the concept (knowledge) web.

* See, for example, my blog of 30 May 2018.

** Physical? (As opposed to mathematical for example.)

Why should you learn to code?

Jensen Huang, CEO of Nvidia, is claiming that we should no longer learn to code. Suppose he is right. Is writing a specification easier than coding? Some computer scientists will tell you that "Formal specifications are often just as hard to read, and almost as hard to write, as code." I then must ask, is writing prompts easier than coding? Do you get what you intended in each case?

As for me, I needed to know some coding for the same reason I needed to know some digital electronics. I wanted to better understand how the computation actually occurs and in some adequate degree of detail.

Understanding occurs over various levels of abstraction. For some purposes it is sufficient to have a broad overview. For other purposes one needs to deal with finer details on a less abstracted level. I.e., there is a concept hierarchy. Some things can only be understood by working on/at the right level of abstraction using the right concepts.  And concepts that work on one level of abstraction may not be valid on another level.

Embodied AI

 Some researchers believe that embodiment is essential for AGI while others believe it imposes a bottleneck. In providing an AI with some specific sense or a particular concept I have sometimes found simulation to be easier.* In other cases I have found embodiment to be easier.**

Simulations are always an imperfect model of reality. Ultimately we want an AI to have contact with and operate in the real world. It can sometimes be faster to begin AI training on simulations, however.

* Recharging ("feeding") was one example.

** For examples see my blog of  1 Oct. 2015.

Conscious of

 My A.s.a. embodied robots learn concepts like "touch", "smell", "hunger", "pain", "bump", etc.* When one or more of these concepts becomes sufficiently activated** A.s.a. is "aware of"*** their presence. The robot is "conscious of" the sensation. More complex concepts become activated higher up in the concept hierarchy.

* See my blogs of 1 Oct. 2015 and 5 Nov. 2015 for examples.

** By sufficiently strong sensory input.

*** i.e., May react to as appropriate.