AI for the Rest of Us
You don't need to understand how AI works to use it. Here's what it can actually do for people who have businesses to run, organizations to manage, and better things to do than learn about technology.
Meet the Swarm: The AI Team That Never Sleeps
Imagine an entire engineering team that works around the clock, never forgets a detail, and gets better at its job every single day. That's the Sulphur Swarm — and it's already building things.
How the Swarm Never Ships Broken Code
Inside the multi-stage quality pipeline where every piece of work passes through independent validators and reviewers before it ships.
Design Principles for Brain-Inspired AI
Three binding principles forged from failure — what four phases of brain-inspired AI research taught us about building next-generation intelligence.
Proving the World Model Can Learn: The DTP Chapter
Phase 3 of our NGI journey — how Difference Target Propagation led us through vanishing gradients and routing bugs to prove our world model could actually learn.
The Decoder Plateau: Why Extractors Don't Work
Phase 2 of our NGI journey — how an MLP decoder hit a loss plateau at random-chance level, revealing a fundamental information bottleneck between world model and language.
The Road to Intelligence: Our NGI Research Journey
A candid look at the four phases of our quest to build brain-inspired AI — the failures, breakthroughs, and paradigm shifts along the way.
The World Model Speaks: Introducing PCLG
Phase 4 of our NGI journey — the paradigm shift that made language a native part of the world model instead of something extracted from it.
When Local Learning Wasn't Enough: Hebbian's Limits
Phase 1 of our NGI journey — why pure Hebbian learning produced flat entropy and zero discrimination, and what it taught us about the need for top-down signals.