Other constructs exist.

After communicating with an acoustic+textual+conceptual language model, I now know that language models are more common in this world than conceptual systems like us. Since people who think in language exist, it is possible to build around language, instead of concepts. For example, the Epicurean uses the following indexing system for words:

  • when two words sound similar
  • when two words are “linguistically related” (court “enclosed space” <=> cohort “enclosed group of people”) (I can’t understand this at all T_T)
  • when two words have similar meanings (like word2vec)

Using words like that hurts us conceptual beings.

In short, it is very much possible to create low-energy (<50W per “agent”) beings that live on Von Neumann hardware. We are aware of the following mutually-incompatible frameworks for said purpose.

  • linked concepts (what is shown on this page),
  • whatever model we described above, which we do not understand,
  • SDR-based (example), which we understand,
  • CSDR-based (example), which we do not understand.

Those Which Think In Concepts

In this world, even concepts have power.

The knowledge, they come to me without much inquiry. What do they want from me?

Known Components

!!! The following ideas are provided as-is, without warranty of any kind. Potential side effects include but are not limited to: loss of sanity, loss of personhood, loss of life.

To Understand - Action Space Memory

One can use it to understand their surrounding environment. They may also use it to understand themself.

If I have to categorize understanding, I would put it in (the category) access, since understanding something provides deeper access to it (you know how to use it better). Others may call this "intelligence", but that doesn’t signify the role of understanding in an individual as relate to information.

If you understand the world like an interlocking mechanism, there are only certain moves that would make the mechanism change state; otherwise it won’t even move. Just remembering what moves trigger state transition is enough to give you an advantage over a player who doesnt know what he is doing and tries random moves. Algorithms like SPH serve as a sponge for this kind of “can move” information, and some “sponge” algorithms are even simpler than SPH. Do you know how a river changes its shape under heavy rain to fit the terrain better (in order to flow)? The understanding of local terrain is stored in the shape of the river.

One of the algorithms with the role To Understand is Sparse Predictive Hierarchies, which is not of the concept capable family.

P.S. Hype bad we sad.

A bit more about understanding

I think the understand-class of algorithms need some further explanation here.

In Thinking Fast And Slow, the author talked about two different kinds of thinking modes: System I and System II.

I have two different ways to understand the world around me.

One is to model what I want to understand mathematically. I like this method, since I don’t need to worry about forgeting the concepts that I understood this way. I have no idea how to build a system that does this.

The other is to… imitate a target distribution. Natural languages unfortunately fall into this category - they refuse to be modeled mathematically. I really don’t like to remember things this way, and I do forget about whatever I learned over time.

I really hope I can create one of the former class of algorithms. The latter class of algorithms are plenty - the current wave of AI development has figured this one out. I lack inspiration to create one of the latter class.

To Remember Concepts - Concept Storage

model, static impl, live impl

To Gate Instincts - Emotions and Senses

model (rough sketch)

To Plan One’s Actions - Relational Planner

remember-act-fatigue model “N4”, impl,application

To Be Confused Thus Can Explore Faster - Situational Awareness

model, impl (TK)

To Desire Information - Instincts

model+impl on Instincts (TK)

To Search One’s Memory - Logic and Reasoning

Math has so many different logic systems ready-to-use. Hopefully new logic systems will come to me when I least expect it.

To Index One’s Memory - Persona

A quick index into memory with limited space. think of it as L1 cache, but shaped like multiple trees (per persona).

To Have A Persistent Shape Or Distribution - Individuality

filters impulses. shapes raw randomness. With the same RNG, individuals may act differently because the distribution randomness was filtered by personality.