Human-robot interaction

 It is usually argued that robots with a humanoid form factor will more readily adapt to the existing human environment. But I find that in most applications we modify the environment to be more robot friendly*. In making use of Roomba, for example, I reduced the clutter and set up virtual walls. Robot lawn mowers typically have a boundary wire. Similarly, factories and warehouses are modified to accommodate the robots that work there. As robots get smarter they may do more of the adapting and we may do less. But if we cohabitate with robots I expect the result will be a compromise, not our current environment, just as factories have long been tailored to both men and machines.

* I think we also modify our activities/behavior in adapting to the use and limitations of software.

Do you use what you studied in college?

For some careers you will use what you learned in college. For others you may not. In becoming a plasma fusion research scientist I certainly used my undergraduate physics major. When I taught at the National University of Singapore I saw that businesses were eager to hire physics majors because they knew our graduates must be smart, worked hard, and were 4 years more mature than high school graduates. The college degree filtered out the better candidates for the employers.

Pluralism

 Kant argued that one can not know the thing in itself (das ding an sich). Rather, we all create models of the world. I have previously noted* 5 such alternate realities.** 

1. materialism  

2. idealism

3. dualism

4. theism

5. multiverses

In my pluralism I most frequently employ #1. Next most frequently I employ #5. I infrequently use #3 and hardly ever use #4. I never seem to employ #2. I could probably keep detailed statistics on this but it's surely dependent upon what's being studied.

* See my blog of 15 June 2022.

** There are, of course, variations*** and combinations**** of these 5.  (Neither do I insist upon keeping the number to 5.)

*** If ultimate reality was composed of simply quantum fields or the wave function that would be a variation of #1 (provided "materialism" refers to any of the concepts defined and employed by modern physics).  There are, of course, many variations of #4.

**** #3 and #4 are frequently combined, for example.                                                                                                                                                      

Robot disconnecting randomly

I was trying to transfer files from one computer (onboard the robot) to another (external, fixed) computer. My system was disconnecting but apparently only when the robot is moving. Seems to be (USB) connectors. I could hard-wire everything but that makes (subsequent) reconfiguring of things so much harder. Maybe some kind of clips/clamps on the connections to reinforce them, hold them tight? Or something like the old RS232 screw connectors.

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.