Giving machines the ability to communicate nonverbally has real value, and [Drew Smith] clearly thinks your robot deserves better than an emoji. He shared a very interesting approach with his project Kindalive.

Kindalive is a simulated dot-matrix robot face that responds believably to input text, modeling and expressing both short-term and long-term moods. It’s pure Python and modular enough to invite using it elsewhere, but that’s not the really interesting part.

What sets [Drew]’s project apart is the way he models eight key neurochemicals (including dopamine and cortisol) as the foundation from which to derive emotional states. That’s an approach we certainly haven’t seen before.

Conventional sentiment analysis uses a large language model (LLM) to apply discrete labels to communication, but Kindalive doesn’t do that. It even goes so far as to model the decay and interplay between its simulated neurochemicals to derive emotional states on the fly. It’s more fluid and organic, and reflects both short-term and long-term mood changes.

Physical representation of the emotional mix is done by altering twelve key facial movements (brow raise, lip corner pull, mouth open, and others of that nature) known as the Facial Action Coding System (FACS). These twelve elements combine to express emotion nonverbally with facial expressions. It’s what drives the simulated dot-matrix robot face seen in the image above, and could easily be used to drive a real LED matrix, or servos on an animatronic face.

Much of communication is nonverbal. Humans even weigh nonverbal higher when there’s a mismatch between the content of verbal and nonverbal communication. So, there’s clear value in having robots able to express themselves as such.

Importantly, a realistic and human-like face is entirely unnecessary — something every Star Wars fan already knows. Cartoon eyes and basic sounds are enough to make robots easier to relate to and work with, even if blinking is also important but hard to get just right.

Integrated electronic modules like counters and displays are convenient and space-saving, which may also make them easy to take for granted. [Nagy Krisztián] demonstrates this by making three very different digital counter designs, each breadboarded with a 7-segment LED display. Push a button, and the displayed number increments by one for each press. It was a personal project that ended up educational in more ways than one.

The first version uses discrete components only, and even though it handles the counting with CD4026B decade counter ICs instead of building counters from scratch with NAND gates, it’s still by far the largest of the three. The second version simplifies driving the display with an AT28C64B EEPROM acting as a sort of hardware lookup table translating binary counts into 7-segment digit display patterns. The third uses an ATtiny24A microcontroller, and unsurprisingly has the smallest footprint.

All of this highlights two things. One is that implementing even a simple counter and 7-segment LED readout is a nontrivial affair when one gets right down to it, even when taking advantage of purpose-built ICs. The second is that the complexity that is on full display in the first version doesn’t simply disappear as the footprint and component count goes down. Rather, it moves into software and other infrastructure, like the need for compilers and chip programmers.

The whole thing is both educational and a reminder of how good the average hardware hacker has it today. There are so many effective electronic assemblies, available to just about anyone at low cost, that it can be very easy to take it all for granted and forget just how much breadboard space and wires were needed for even simple-seeming things.

[Nagy] is certainly no stranger to dealing with a lot of wires, as we’ve seen when he fooled a 286 processor into thinking it was plugged into a functioning vintage motherboard.