openflukeINDEPENDENT RESEARCH. OPEN POSSIBILITIES.
Artificial life.
Real possibilities.
What if intelligence could grow with you?
OpenFluke explores the space between AI, living worlds and the devices we call our own. Built from the engine up. Shared along the way.
Steam · Windows, Linux, macOS · iPhone & iPad
Meet ALife: Becoming.
Official trailer Watch on YouTube
EXPLORE. BUILD. TEACH.
A game about small worlds and the helpers you teach.
Explore tiny planets, gather resources and build paths between worlds. When a job needs repeating, show a little helper called a Spark what to do by walking the route yourself.
Download now on Steam for Windows, Linux and macOS. Available on iPhone and iPad; Android is in internal testing.
View the full gallery IN DEVELOPMENT · APP 0.1.0+1
The Welvet app is now in development.
A cross-platform program for running and serving AI models on the devices you already own — Linux, Windows, macOS, iOS and Android, with CUDA, Metal, Vulkan and more.
Round 1 demos show working paths on real hardware. That means it runs — not that it is fastest or best yet. The baseline improves with every round.
Welvet app · round 1 baseline THE BIG PICTURE
One vision. Three connected parts.
You do not need to know AI to understand
what we are building.
OpenFluke.
The independent practice asking what AI and artificial life could become. A place to build, test and follow an idea wherever it leads.
Meet the mind behind it STEAM · IPHONE & IPADALife: Becoming.
An exploration and building game of tiny planets, connected worlds and Sparks you teach through your own actions. On Steam for Windows, Linux and macOS, plus iPhone and iPad.
Explore the game 03 / THE ENGINEWelvet.
The AI engine underneath, and a cross-platform app for running models on Linux, Windows, macOS, iOS and Android. Explore how intelligence works on your own hardware.
See the Welvet appNOT A STRAIGHT LINE. A CONNECTED JOURNEY.
Every experiment
brought us here.
From Primecraft and Biocraft to Birdkit and SoulGlitch, each project asked where a chaos simulation engine might fit. ALife OS was the prototype. ALife: Becoming is the actual game growing out of those experiments.
Alongside them, Paragon and Loom shaped the engine that became Welvet.
Follow the research journeyOPEN THE NOTEBOOK
The ideas. The code. The detail.
Start with a question.
Follow it all the way down.
108 chapters, from the big picture to the inner workings of the engine.
Read the book THE EXAMPLE LIBRARYSee what happens
when ideas run.
94 documented examples, with source code and recorded outputs to explore.
Browse examples RESEARCH & EXPLORATIONThe thinking behind
the next experiment.
Reports and research notes tracing the questions that shaped the work.
Explore the researchA FEW GOOD QUESTIONS
Let’s make it simple.
New here? Start here.
What is OpenFluke?+
OpenFluke is the independent AI and artificial-life research practice of Samuel Watson in Australia. It brings together the Welvet AI engine, the Welvet cross-platform app now in development, ALife OS (the earlier prototype), and ALife: Becoming, the game available on Steam and iPhone/iPad.
What is Welvet?+
Welvet is two connected things. First, the AI engine underneath the work: Go software (v1.7) for running and training neural networks on CPU tiled, Plan 9 SIMD, and WebGPU, with optional NativeCPU, Qualcomm Hexagon HTP, Apple Metal, Apple MLX (forward-only), NVIDIA CUDA, AMD ROCm, and Vulkan backends. Second, the Welvet app (0.1.0+1, v0.1 Foundation): a cross-platform program in development for running and serving models on Linux, Windows, macOS, iOS and Android. Round 1 demos show working paths on real hardware; working means it runs, not that it is fastest or best. Paragon and Loom are earlier engine designs whose lessons continue in Welvet.
What is the Welvet app?+
The Welvet app (version 0.1.0+1, milestone v0.1 Foundation) is OpenFluke’s cross-platform program for running and serving AI models on devices you already own. It is in active development. The On-Device AI Demos series shows shared models across Fedora Linux (CUDA/Vulkan), Windows x86-64 and ARM64, macOS, iOS and Android. Fifteen models are currently approved in the app matrix. Demo results are engineering baselines that improve each round, not claims of maximum performance. See /welvet/app and /welvet/models.
Does Welvet support Qualcomm Windows NPU acceleration?+
Yes, as of Welvet v1.2 / welvet.qnn 1.0.0. On Windows ARM64 with Snapdragon X (or similar), opt-in BackendQNN plus SyncToQNN / PrepareQNN can run supported layers on Qualcomm Hexagon HTP. It is never the Prefer default. Other OS/arch report unavailable. Published large-shape timings are in the Welvet book §81 and w2a go_v_qnn RESULTS.
Does Welvet support Apple Metal acceleration?+
Yes, as of Welvet v1.3 / welvet.metal. On Apple silicon macOS, opt-in nativemetal.Mount runs supported layers on the independent Metal GPU library with explicit train, SyncToGo, and JSON Go/C++/Metal routing. It is never the Prefer default and is not Apple Neural Engine. Book chapters §82–88 cover the API and captured Mamba results.
Does Welvet support Apple MLX acceleration?+
Yes, as of Welvet v1.7.0 / welvet.mlx 1.0.0. The independent forward-only MLX engine lives at github.com/openfluke/welvet.mlx. On Apple silicon macOS, opt-in BackendMLX / PreferMLX plus SyncToMLX / SyncFromMLX runs supported layers on Metal via libmlx through nativemlx. It is never the Prefer default. No TrainMSE on MLX. Caps reject unsupported layer×dtype. Book chapters §110–113 cover SyncToMLX, caps, Dense/Sequential forward, and go_v_mlx suite pointers.
Does Welvet support NVIDIA CUDA acceleration?+
Yes, as of Welvet v1.4 / welvet.cuda 0.79. On Linux x86_64 and Windows amd64 with an NVIDIA GPU, opt-in nativecuda.Mount runs supported layers on the independent CUDA library with explicit train and SyncToGo (two weight copies until you sync). JSON Go/C++/CUDA routing via EnableRouting is Linux amd64. It is never the Prefer default. Book chapters §89–95 cover the API and suite pointers.
Does Welvet support AMD ROCm acceleration?+
Yes, as of Welvet v1.5 / welvet.rocm 0.79. The independent AMD engine lives at github.com/openfluke/welvet.rocm. On Linux x86_64 and Windows amd64, opt-in nativerocm.Mount runs supported layers with explicit train and SyncToGo. JSON Go/C++/ROCm routing via EnableRouting is Linux amd64. It is never the Prefer default. Library build/load is validated; GPU compute remains untested until a ROCm-capable HSA device is available. Book chapters §96–102 cover the API and suite pointers.
Does Welvet support Vulkan acceleration?+
Yes, as of Welvet v1.6.1 / welvet.vulkan 0.79.1. The independent Vulkan engine lives at github.com/openfluke/welvet.vulkan. On Linux x86_64, opt-in nativevulkan.Mount runs supported layers with explicit train and SyncToGo. JSON Go/C++/Vulkan routing via EnableRouting is Linux amd64. It is never the Prefer default. There is no silent host fallback labeled as Vulkan. Book chapters §103–109 cover the API and suite pointers.
Where can I find the Welvet 1.7 technical research?+
On the Welvet page and at the top of the research archive: YouTube youtu.be/f9UBcRNHj4Y, technical research PDF files.openfluke.com/1_7/Welvet 1.7_Technical_Research.pdf, interactive architecture dashboard, feature book v1.7.0 PDF, architecture slides (PDF/PPTX), Standard QAT vs Welvet paradigm infographic, and the continuous on-device training MP3. Earlier Welvet 1.3 deep dive remains in the archive.
Where can I find the Welvet 1.3 deep research?+
In the research archive (historical): deep-dive PDF at files.openfluke.com/archive/welvet_1_3/Welvet_1.3_Update_Deep_Dive.pdf, audio How_Welvet_Trains_AI_On_Edge_Devices.mp3, and YouTube youtube.com/watch?v=_JHZk1A-J6Q. For the current release, use the Welvet 1.7 technical research pack on /welvet and /research.
Where is the medical AI continual-learning research?+
In the research archive: Why medical AI cannot stay frozen. The PDF is files.openfluke.com/archive/polymorphic_play/Medical_AI_Techniques_Research.pdf, the audio briefing is Why_Medical_AI_Cannot_Stay_Frozen.mp3, and the YouTube explainer is youtu.be/dqNkzD_dzPA. It covers locked diagnostic drift, continual learning, federated hospital setups, FDA/TGA adaptive-AI regulation, and OpenFluke’s experimental MORPH controller as a systems testbed.
What is ALife: Becoming?+
An exploration and building game where you visit tiny planets, gather resources, connect worlds, and teach Sparks by showing them what to do. It is available on Steam for Windows, Linux and macOS, and on iPhone and iPad, with Android in internal testing.
What happened to ALife OS?+
ALife OS was the prototype. ALife: Becoming is the actual game that grew from it. The older design notebook is preserved as history, rather than a list of completed features.
How do you teach a Spark?+
Record a trail by doing the job yourself, then train a Spark to follow the route you demonstrated. The goal is useful automation that stays physical enough to produce surprising outcomes.
Is Becoming available now?+
ALife: Becoming is available on Steam for Windows, Linux and macOS, and on the App Store for iPhone and iPad. Android is in internal testing. Email [email protected] to ask about Android testing.
What happened to the earlier projects?+
Primecraft, Biocraft, Birdkit, and SoulGlitch explored different places and configurations for the chaos simulation engine. Those experiments and pivots led through the ALife OS prototype to ALife: Becoming. Paragon and Loom sit on the engine side of that history, leading into Welvet.
Do I need to understand AI to explore this work?+
No. Start with the game and engine overviews. The book and examples are there when you want the technical detail, including source code, recorded outputs, and the limitations documented in the original work.