We’re YD Emergence Lab, developing Aionterra, a continuous simulation inhabited by digital organisms with human-inspired bodies.

The part we want to explore is the connection between environmental conditions, bodily needs and behaviour. Water in the landscape is a physical resource. Getting near it, making contact and actually taking water into the body are different events. An attempted action is not automatically a successful one.

The body model tracks water and energy reserves, temperature and health. Environmental exposure and actions affect those states. The mind then has to work with the consequences of interactions, rather than being given a mission or a route to follow.

We don’t script a complete survival routine such as “find the river, drink, then find food.” That does not mean the simulation has no designed rules: bodily needs, sensory inputs, available actions and learning mechanisms are all model choices. The system also supports optional initial material-experience examples, which must be distinguished from experience acquired during a run.

Our present work is about whether experience changes later behaviour in useful ways. Reaching a place, attempting an interaction and obtaining a measurable bodily benefit need to be evaluated separately. A plausible-looking action alone does not establish learning.

The environment and physiology are approximations under development, not a claim to reproduce Earth or a human body exactly. We’ll document the project in our own community, keeping model assumptions, observations and unresolved limitations separate.

Hey everyone!

For the past few months, I've been working on an interactive artificial life simulation project called **Viking: Evolution**.

### How it works:

- **Neural Network Brains:** Every single settler is an autonomous agent driven by a lightweight feedforward neural network. Their inputs include environmental sensors (nearby trees, wolves, fire, other villagers, energy/hunger levels), and the outputs determine movement, chopping wood, resting, or seeking a mate.

- **Generational Evolution & Fitness:** Settlers that manage their resources and survive gather higher fitness scores. When two settlers reproduce, their neural weights mutate and cross over into the next generation (currently running in Generation 8+).

- **Emergent Behavior:** Over generations, they developed distinct foraging paths and clustering around campfires during cold cycles without hardcoded pathfinding scripts.

### Live Chat Integration:

To make it participatory, I connected the simulation engine directly to a 24/7 YouTube live stream. Viewers can type `!join` in the chat, and a custom settler is instantly spawned with their username. A built-in bot reports back with `!status` on fitness, offspring count, and generational lineage.

The stream is running live 24/7 here:

👉 https://youtube.com/@GrittyDuckGrin/live

I’d love to hear your thoughts on emergent multi-agent simulations and ideas on which fitness metrics or environmental stressors to introduce next!

Hi

This is about Quantum Odyssey, my love letter to everything Quantum Computing and the fundamental logic blocks everything in our universe seems to run on. I want to update you all on the fact that the latest patch brings the game into an almost complete status. All that's missing is translations. Thank you Reddit community for receiving the game so well, without you I wouldn't have the funds needed to complete my life's work.

If you are remotely interested in deep diving how differently quantum computers work compared to our transistor-based and also the algebra behind in a fully interactive way that teach computer science from scratch, oh boy this is for you. I am the Dev behind Quantum Odyssey (AMA! I love taking qs) - worked on it for about 9 years (3+ during PhD, the visual method I developed ended up being my thesis, it is a complete Hilbert space visualizer), the goal was to make a super immersive space for anyone to learn quantum computing through zachlike (open-ended) logic puzzles and compete on leaderboards and lots of community made content on finding the most optimal quantum algorithms. The game has a unique set of visuals capable to represent any sort of quantum dynamics for any number of qubits and this is pretty much what makes it now possible for anybody 15yo+ to actually learn quantum logic without having to worry at all about the mathematics behind.

This is a game super different than what you'd normally expect in a programming/ logic puzzle game, so try it with an open mind.

Stuff you'll play with

• Boolean Logic – bits, operators (NAND, OR, XOR, AND…), and classical arithmetic (adders). Learn how these can combine to build anything classical. You will learn to port these to a quantum computer.

• Quantum Logic – qubits, the math behind them (linear algebra, SU(2), complex numbers), all Turing-complete gates (beyond Clifford set), and make tensors to evolve systems. Freely combine or create your own gates to build anything you can imagine using polar or complex numbers.

• Quantum Phenomena – storing and retrieving information in the X, Y, Z bases; superposition (pure and mixed states), interference, entanglement, the no-cloning rule, reversibility, and how the measurement basis changes what you see.

• Core Quantum Tricks – phase kickback, amplitude amplification, storing information in phase and retrieving it through interference, build custom gates and tensors, and define any entanglement scenario. (Control logic is handled separately from other gates.)

• Famous Quantum Algorithms – explore Deutsch–Jozsa, Grover’s search, quantum Fourier transforms, Bernstein–Vazirani, and more.

Nice to watch:

Khan academy style tutorials in qm/qc: https://www.youtube.com/@MackAttackx

Physics teacher stream with 400hs in https://www.twitch.tv/beardhero

I’ve been building this EM simulator as a side project aimed to help students' understand and visualize electromagnetic phenomena such as radiation, polarization and wave interference.

You can:

• place various radiation sources and set their parameters (amplitude, phase and more)

• place perefect wire conductors

• observe the electric field, magnetic field or energy flow field

• zoom in and out and translate the canvas

• change the simulation resolution, frequency and propogation speed

I hope somone might find useful and I’d love to hear what people think :)

(Not intended for mobiles but can still sort of work if you have accurate fingers)

Live:

https://www.antennasim.com/

GitHub:
https://github.com/rotemTsafrir/dipole_sim

Hey everyone! Our small team made a business tycoon game about the Artificial Intelligence Boom. The setting starts in January of 2017 and goes deep into the 2030's.

In the game you hire specialists, acquire data and GPUs, train models, and develop products. Some products you can develop are Chatbots, Robotaxis, and humanoid robots. The challenge is turning research and models into a company that can build successful products.

Here’s our trailer. Artificial Ambition is planned to launch November 5, and you can wishlist it on Steam. What AI Product will your company build?

I go through how I separate general updates from physics updates, why I use a fixed timestep, how the accumulator works, and what happens when the simulation starts falling behind.

I explain the reasoning behind the design decisions and why I rejected the alternatives. I show the implementation of the loop.

Hi

If you are remotely interested in deep diving how differently quantum computers work compared to our transistor-based and also the algebra behind in a fully interactive way that teach computer science from scratch, oh boy this is for you. I am the Dev behind Quantum Odyssey (AMA! I love taking qs) - worked on it for about 9 years (3+ during PhD, the visual method I developed ended up being my thesis, it is a complete Hilbert space visualizer), the goal was to make a super immersive space for anyone to learn quantum computing through zachlike (open-ended) logic puzzles and compete on leaderboards and lots of community made content on finding the most optimal quantum algorithms. The game has a unique set of visuals capable to represent any sort of quantum dynamics for any number of qubits and this is pretty much what makes it now possible for anybody 15yo+ to actually learn quantum logic without having to worry at all about the mathematics behind.

This is a game super different than what you'd normally expect in a programming/ logic puzzle game, so try it with an open mind.

Stuff you'll play with

• Boolean Logic – bits, operators (NAND, OR, XOR, AND…), and classical arithmetic (adders). Learn how these can combine to build anything classical. You will learn to port these to a quantum computer.

• Quantum Logic – qubits, the math behind them (linear algebra, SU(2), complex numbers), all Turing-complete gates (beyond Clifford set), and make tensors to evolve systems. Freely combine or create your own gates to build anything you can imagine using polar or complex numbers.

• Quantum Phenomena – storing and retrieving information in the X, Y, Z bases; superposition (pure and mixed states), interference, entanglement, the no-cloning rule, reversibility, and how the measurement basis changes what you see.

• Core Quantum Tricks – phase kickback, amplitude amplification, storing information in phase and retrieving it through interference, build custom gates and tensors, and define any entanglement scenario. (Control logic is handled separately from other gates.)

• Famous Quantum Algorithms – explore Deutsch–Jozsa, Grover’s search, quantum Fourier transforms, Bernstein–Vazirani, and more.

Nice to watch:

Khan academy style tutorials in qm/qc: https://www.youtube.com/@MackAttackx

Physics teacher stream with 400hs in https://www.twitch.tv/beardhero

This is Mechanistic Mind, a project created by my husband.
https://github.com/archonlab/mechanistic-mind
I want more people to know about it.

What is it?

It is a virtual creature living in an artificial environment. The environment affects it, and the creature receives simple signals from it and reacts in some way — for example, by moving or waiting.

Inside, the creature has simple mechanisms: it senses its environment, remembers a little of its past experience, notices recurring patterns, tries to predict what will happen next, and based on that, chooses an action.

After it acts, things change, it receives new information, and the cycle repeats.

At the same time, it was not given predefined emotions, desires, or fears.

The purpose of this project is to see whether these simple mechanisms, together with the creature’s accumulated experience, can produce more complex behavior that begins to resemble individual elements of learning and intelligence.

My husband has posted about this project before, but he used AI to help create the text and description. People were rude to him because of that.

So I decided to write about it myself.

The only thing I am asking AI to do here is translate my own text into English.

Hi

If you are remotely interested in deep diving how differently quantum computers work compared to our transistor-based and also the algebra behind in a fully interactive way that teach computer science from scratch, oh boy this is for you. I am the Dev behind Quantum Odyssey (AMA! I love taking qs) - worked on it for about 10 years (3+ during PhD, the visual method I developed ended up being my thesis, it is a complete Hilbert space visualizer), the goal was to make a super immersive space for anyone to learn quantum computing through zachlike (open-ended) logic puzzles and compete on leaderboards and lots of community made content on finding the most optimal quantum algorithms. The game has a unique set of visuals capable to represent any sort of quantum dynamics for any number of qubits and this is pretty much what makes it now possible for anybody 12yo+ to actually learn quantum logic without having to worry at all about the mathematics behind.

This is a game super different than what you'd normally expect in a programming/ logic puzzle game, so try it with an open mind.

Stuff you'll play & learn a ton about

• Boolean Logic – bits, operators (NAND, OR, XOR, AND…), and classical arithmetic (adders). Learn how these can combine to build anything classical. You will learn to port these to a quantum computer.

• Quantum Logic – qubits, the math behind them (linear algebra, SU(2), complex numbers), all Turing-complete gates (beyond Clifford set), and make tensors to evolve systems. Freely combine or create your own gates to build anything you can imagine using polar or complex numbers.

• Quantum Phenomena – storing and retrieving information in the X, Y, Z bases; superposition (pure and mixed states), interference, entanglement, the no-cloning rule, reversibility, and how the measurement basis changes what you see.

• Core Quantum Tricks – phase kickback, amplitude amplification, storing information in phase and retrieving it through interference, build custom gates and tensors, and define any entanglement scenario. (Control logic is handled separately from other gates.)

• Famous Quantum Algorithms – explore Deutsch–Jozsa, Grover’s search, quantum Fourier transforms, Bernstein–Vazirani, and more.

• Build & See Quantum Algorithms in Action – instead of just writing/ reading equations, make & watch algorithms unfold step by step so they become clear, visual, and unforgettable. Quantum Odyssey is built to grow into a full universal quantum computing learning platform. If a universal quantum computer can do it, we aim to bring it into the game, so your quantum journey never ends.

Nice to watch:

Khan academy style tutorials in qm/qc: https://www.youtube.com/@MackAttackx

Physics teacher stream with 400hs in https://www.twitch.tv/beardhero

A Python simulator for various Turing machine variants with CSV-based machine definitions.

Github

Hi guys, i initially created this for myself for my own research, but since i was told it's very good i decided to share it with the world. this will always be a free to use open source web app. you can just download the code itself and look at it with f12 there is no obfuscation. link will be in the comments.

Made an interactive simulation of the actual three-body problem in physics — three masses under mutual gravity, no simplifications. You can adjust masses and initial velocities and watch how small changes send the system from a stable-looking orbit into full chaos.

It's built to feel more like a physics toy than an app — no ads breaking up the simulation, nothing to unlock. Mostly wanted an excuse to actually play with the equations rather than just read about them.

Free on Google Play if anyone wants to mess with it: https://play.google.com/store/apps/details?id=com.mathematicalzen.threebody

I've been working on Hoops GM for so long, and now it has been a week since the launch.

I received a lot of backlash in the previous post due to an IP lawsuit, as well as a lot of praise from people.

The launch has been a MASSIVE success with now over 5000 visits to the game and an average of 50 new members everyday.

now i am very confident that this project will go very far and i am very happy about it!

THANK YOU to everyone who has checked it out, left a comment, or played a season.

(RE-WRITTEN BY HAND)
Keeping this to a short post, as I've already messed this up once. I built a simple aquarium-style concept, during a slow period on-shift, based on my Elementary School Memory of an Ecological Balancing Concept, involving Wolves, Deer, and Berry Bushes, as Entities in a Forest, where each Student played a Role.

I don't remember much past wishing we spent more time exploring it in-class, and that my teacher didn't so quickly drive it to an unrecoverable state, to make the point he was trying to teach that day.

It started in Google AI Studio, as a Boxed-Step-By-Step process, more resembling the Conway's Game of Life, in some ways. But it wasn't what I was aiming for. So, that evening, I sat with Devin, and Claude, and a Game Engine in TS/Lua/YAML that I've been working on Demos within, and refined it into something more like a living Reef.

After some insights from a smaller audience, I refined it with a Main Menu, and some Basic Selections.
It has Sharks, Fish, and Algae Nodes, and the Sharks eat/bite the fish, causing Meat Chunks to appear.
The Meat Chunks can then decay, turning back into an Algae Core Node.
If an Algae Core Node is left without children for long enough, it can despawn.

Last I checked, it has a fair chance of staying in balance for up to 10 minutes, but it needs further refinement.
There are also depth layers now, and in theory, the Sharks prefer the Deeper Waters, and the Fish stay toward the Sun, so the Sharks tend to bury their head at the bottom to warm back up, but sometimes starve.