Gustavo Lacerda

mathemajician reminded me (i.e. I reminded myself by reading him) to write up my notes about intelligence, since he is trying to write a philosophical paper on intelligence at the moment.

Don't pay attention to the circularity: it's a necessary part of the philosophical process.

intelligence: the ability to create and use abstraction.
abstraction: a central feature of intelligence, whose purpose is to economize computational resources by reusing similar structures.
redundancy: randomness deficiency. Redundancy is the property of, for example, structures with similar parts. Data without redundancy is simply random noise. Redundancy is a prerequisite for meaningfulness: without redundancy, language would be unlearnable. Nature herself is highly redundant: if it weren't, science wouldn't work. See: Information Theory, Kolmogorov Complexity, Learning as Compression.

Hardcoding is the lack of abstraction. It is more efficient for specialized behavior. So it's a trade-off. However, abstraction, being a conscious process, allows a greater degree of control and flexibility; not to mention the freedom to use one's intelligence & knowledge on novel applications. Abstraction allows true "creativity".


SOME DOMAINS:

behavior type--> domain	intelligent	unintelligent
language is known to be an area in which our processing (including some "reasoning") is largely automatic and unconscious.	Abstract thought away from language. Try to generate utterance from the abstract thought.	Think in their mother tongue. Translate word by word. Sometimes even translate things like: "het weer" => "the again".
music	Solfège: map songs to sequence of abstract notes relative to the key. Once a song has been learned, a solfeger can play it in any key and on any instrument. Solfege taps into the efficient language-processing module by encoding notes as syllables (we can process language representations), which may aid not only memorization, but also improvisation and composition (after enough solfeging in a musical idiom, the musician learns a language of syllable patterns, which he can use to create novel phrases and decode them back into music).	map: songs -> sequence of finger positions
science and mathematics	* meta-science * applying proof theory to analysis (see Kohlenbach). * A good design of Mathematical Concepts may reduce cognitive burden (i.e. economize computational resources)
programming	meta-programming, modular design of code AND data, intelligent design patterns, high-level languages: code is close to specifications	hardcoding, low-level languages

intelligence (refined definition): the ability to represent abstract structures on their own. This is extremely difficult in some cases, if only because of the computational load. But abstract imagination seems inherently difficult: how can one imagine a structure which is inherently abstract? How can one picture a tree which could have either 3 or 4 branches, no more, no less? This can perhaps be done by imagining a flickering picture.

reflection and self-improvement

humans seem to be happy as long as they are learning optimally. If challenges are too hard or too easy, they will get bored.