Tuesday, July 16, 2024

Model decomposition efforts

 An (isolated) world model is required for a number of AI applications. So we would like to separate world model* from  agent** model, action model, any pre and post processors, etc. Specialist A.s.a. agents do this to some (limited) degree and even (partially) decompose the world model into specialized submodels*** (i.e., knowledge organization). The mechanisms at play in that case are the specialized (and limited) training curriculum plus the subsequent tasks and work environment selection.

* "laws of nature"?

** observer?

*** scientific fields?

Sunday, July 14, 2024

GPT passes minimum Turing test

Although I have been critical of both LLMs and Turing tests it is still interesting to see Jones and Bergen's paper.* I generally do not think science is about tests, benchmarks, and metrics. A number of specialists and organizations have been rather premature in switching from doing science to doing engineering. Work done in industry tends to be rushed, seeking a product and a profit. Pure science is then best done in academic institutions. Of course the capitalists are trying to turn everything into a business including universities. This is not helpful.

* Does GPT-4 pass the Turing test?, arXiv:2310.20216, v2, 20 April 2024.

Tuesday, July 9, 2024

Tingling sensation

Vibration can cause Lego bricks to separate enough* to allow pain sensor contacts to lose connection. Continued vibration then causes bouncing contacts, a "tingling" sensation is recorded. 

* a "crack" forms

Monday, July 1, 2024

US Supreme Court opinion

 So let me get this straight. Aren't they saying that Joe Biden can have seal team 6 assassinate Donald Trump tomorrow and he (Biden) will be insulated from criminal prosecution because he is the current president? That's nuts. The GOP has a lot to answer for. I fear for the future of my children and grandchildren.

Is this a new Gesetz zur Behebung der Not von Volk und Reich?

Concept grounding*

What sensors are needed to ground the core concepts learned by an intelligent robotic agent**? For some time I simply added sensor types as soon as they were available for use***. But in retrospect I believe that essential ones were:

force sensors, accelerometers, temperature sensors, light sensors, color sensors, gas sensors, anemometer, gps sensor, rain/water sensor, microphone and speaker, humidity sensor, voltage sensors, current sensors, ultrasonic and/or IR range finders, line sensor, servo/motor encoders, and neural network preprocessors****.

Combinations and sequences of these raw input signals together form primitive core concepts.

* Rather than symbol grounding.

** Or society of agents. 

*** For example, my blog of 1 October 2015.

****Possibly classifying input from cameras.

A.s.a.'s values

In our early publication* A.s.a.'s value module was placed at the top of the case/concept hierarchy. This can be true early in training and/or for small agents**. But as training proceeds more and more concepts are acquired/created and these are chained and the hierarchy grows upward. I.e., our values need not be our deepest/most abstracted concepts**.

Furthermore, in the light version of A.s.a. H. 2.0 published in our 10 February 2011 blog we value pattern occurrence frequency and pattern size on each level of the hierarchy.   

* Trans. Kan. Acad. Sci., vol. 109, pg 159, 2006.

** Or by use of pass through across layers.


Friday, June 28, 2024

Another argument for vector utility

Diversity. There are multiple niches, multiple ways to improve a creature's fitness and increase its chances of survival and spread. Beneficial traits, different adaptions, like protective coloration, larger brains,  etc.  Different creatures may find very different ways to improve.