Category Archives: Science

Final States

Over the last three posts I’ve been exploring the idea of system states and how they might connect with computational theories of mind. I’ve used a full-adder logic circuit as a simple stand-in for the brain — the analog flow and logical gating characteristics of the two are very similar.

In particular I’ve explored the idea that the output state of the system doesn’t reflect its inner working, especially with regard to intermediate states of the system as it generates the desired output (and that output can fluctuate until it “settles” to a valid correct value).

Here I plan to wrap up and summarize the system states exploration.

Continue reading


Intermediate States

I left off last time talking about intermediate, or transitory, states of a system. The question is, if we only look at the system at certain key points that we think matter, do any intermediate states make a difference?

In a standard digital computer, the answer is a definite no. Even in many kinds of analog computers, transitory states exist for the same reason they do in digital computers (signals flowing through different paths and arriving at the key points at different times). In both cases they are ignored. Only the stable final state matters.

So in the brain, what are the key points? What states matter?

Continue reading


State of the System

State DiagramIn the last post I talked about software models for a full-adder logic circuit. I broke them into two broad categories: models of an abstraction, and models of a physical instance. Because the post was long, I was able to mention the code implementations only in passing (but there are links).

I want to talk a little more about those two categories, especially the latter, and in particular an implementation that bridges between the categories. It’s here that ideas about simulating the brain or mind become important. Most approaches involve some kind of simulation.

One type of simulation involves the states of a system.

Continue reading


Full-Adder “Computing”

Full Adder Logic TableImagine the watershed for a river. Every drop of water that falls in that area, if it doesn’t evaporate or sink into the ground, eventually makes its way, through creeks, streams, and rivers, to the lake or ocean that is the shed’s final destination. The visual image is somewhat like the veins in a leaf. Or the branches of the leaf’s tree.

In all cases, there is a natural flow through channels sculpted over time by physical forces. Water always flows downhill, and it erodes what it flows past, so gravity, time, and the resistance of rock and dirt, sculpt the watershed.

The question is whether the water “computes.”

Continue reading


Interpreting AND as OR

Previously, I wrote that I’m skeptical of interpretation as an analytic tool. In physical reality, generally speaking, I think there is a single correct interpretation (more of a true account than an interpretation). Every other interpretation is a fiction, usually made obvious by complexity and entropy.

I recently encountered an argument for interpretation that involved the truth table for the Boolean logical AND being seen — if one inverts the interpretation of all the values — as the truth table for the logical OR.

It turns out to be a tautology. A logical AND mirrors a logical OR.

Continue reading


Interpret This!

My illusion of free will decided the month of May must be made for Mind (and maybe a dash of Mandelbrot). Lately, online discussions about consciousness have me pondering it again. I never posted on topics such as Chinese Rooms or Philosophical Zombies, largely because sensible arguments exist both ways, and I never decided exactly where I fell in the argument space.

It’s not that I’ve decided[1] on the topics so much as I’ve decided to write about them (and other topics). I’ve found that writing about a topic does a lot to clarify my mind about it. (Trying to teach a topic does that even more.)

I’ll start today with some personal observations and points of view.

Continue reading


Our Inner Screen Vector Space

I’d planned a different first post for May Mind Month, but a recent online conversation with JamesOfSeattle gave me two reasons to jump the gun a bit.

Firstly, my reply was getting long (what a surprise), and I thought a post would give me more elbow room (raising, obviously, the possibility of dueling posts). Secondly, I found the topic unusual enough to deserve its own thread.

Be advised this jumps into the middle of a conversation that may only be of interest to James and me. (But feel free to join in; the water’s fine.)

Continue reading


31D Ice Cream

Last time we considered a cube-shaped room where we could indicate our opinion about Neapolitan ice cream with a single marker. That worked well because we were dealing with three flavors and the room has three dimensions: east-west, north-south, up-down.

Later I’ll explore other examples of a 3D “room” but while we’re talking ice cream, I want to give you an idea where this goes, I want to jump ahead for a moment and consider good old Baskin-Robbins, who famously featured “31 flavors!”

So now the question is, can we set a marker for all 31 flavors?

Continue reading


3D Ice Cream

Have you ever had (or at least seen) Neapolitan ice cream? It’s the kind with chocolate, vanilla, and strawberry, usually as separate layers in one package. As a kid, I didn’t care for the strawberry. I loved the chocolate and was fine with the vanilla (wouldn’t usually choose it, but don’t disdain it).

That’s just my take on it: one flavor liked, one not liked, and one that’s just okay. Someone else might have the same pattern with different flavors. Or love them all equally or want just the strawberry. Some might not like ice cream at all — any combination is possible.

What if we wanted to describe our feeling about Neapolitan as a whole?

Continue reading


Sideband #65: 4D Rotation

This is a Sideband to the previous post, The 4th Dimension. It’s for those who want to know more about the rotation discussed in that post, specifically with regard to axes involved with rotation versus axes about which rotation occurs.

The latter, rotation about (or around) an axis, is what we usually mean when we refer to a rotation axis. A key characteristic of such an axis is that coordinate values on that axis don’t change during rotation. Rotating about (or on or around) the Y axis means that the Y coordinate values never change.

In contrast, an axis involved with rotation changes its associated coordinate values according to the angle of rotation. The difference is starkly apparent when we look at rotation matrices.

Continue reading