Self knowledge in Asa H

A robot embodied Asa H has inputs from its physical senses.  On the lowest level in the concept/memory hierarchy Asa feels things like its level of battery charge, temperature, pain/damage, sight, sound, touch, acceleration, etc.
Asa can also have access to internal/software features. On the various levels in the concept hierarchy it can accept as input things like the size of the current casebase, the current learning rate ("L"), how often it is attempting case extrapolation ("skip"), etc.  (see my blog of  10 Feb. 2011 for an example of "L" and "skip" )  We can also measure,  record, and input the time spent in any of Asa's algorithmic processes. Asa can then learn to adjust/optimize any of these quantities. (See my book Twelve Papers, chapter 1, page 15, self monitoring) In this way Asa can sense its own thought processes. Is this the nature of qualia?

Nengo

I now have the University of Waterloo's Nengo spiking neural network software package running in my computer lab.

Giving Asa H names for the concepts it learns

It is easy to associate a word/name with the lowest level concepts that Asa (or a human infant) learns, things like:

collision=(sense near, bump, accelerate, hear sound "collision")

approach=(sense far, move forward, sense near, hear sound "approach")

When running Asa H we frequently watch the signals being sent from one level of the memory hierarchy to the next (see my blog of 26 Aug. 2013) which makes it possible to supply names for the higher level concepts as they become activated.  This is not possible for humans of course. Humans probably do not share exactly the same higher level (i.e. more abstract) concepts.

Does AI really need biological plausibility?

Eliasmith has criticized Markham's recent Blue Brain paper (Cell, 163, pg 1, 2015) saying "But you can get all those results with a way less complicated model."  But if your interest is in modeling general intelligence then I fear that I might say the same thing about Eliasmith's own model of the brain, Spaun. (Science, 338, 30 Nov. 2012) The very limited short term memory that humans have is something I certainly don't want to duplicate in any AI.

Numerics of promotion and tenure

If you publish a paper with a coauthor sometimes you should receive half the credit because you may have done only half as much work. On the other hand if you publish the paper with Einstein sometimes you should receive more credit (than for a single author paper) since Einstein's name suggests the paper is more valuable. Even if the coauthor is just Joe Physicist it may be important that someone, anyone, agrees with your ideas. Each paper really must be evaluated on its own merit. No fixed weighting scale is as good.

New work on focus of attention in Asa H

Each level in the Asa H hierarchy learns a set of cases and the components/features that make up the case. Each case is a vector and the features are the vector's components. In my blog of 7 Oct. 2015 I noted that we can use things like statistical measures of independence to prune features.  We can also use standard statistical measures in order to determine the relative importance of each feature in identifying a case it is found in.  Such statistical measures can then be used as weights in the (dot product or other) similarity measure that Asa uses when it compares cases.

(In other case-based reasoning systems it is not real common to see the dot product used as the similarity measure.  I have tried other similarity measures in Asa H but coming out of a physics background I have probably shown a bias toward the dot product.  It is worth noting that Jannach et. al in Recommender Systems, Cambridge Univ. Press, 2011 on page 19 say "In item-based recommendation approaches cosine similarity is established as the standard metric as it has been shown that it produces the most accurate results.")

Administrative work

I was head of physics at ESU for 4 years (and associate chair of the division of physical sciences for a part of that).  I found that I did not like administrative work. Things like scheduling, organizing, report writing, staff meetings, personnel decisions, office politics, etc.  I found this was all just a distraction from S.T.E.M. work.