We’ve been working on something big… 📘
The Intelligence Shift is out now—Kindle & paperback!
It’s not just a book. It’s a new path for AI: faster, leaner, more human.
Follow along as we highlight key ideas in coming posts.
📖 https://t.co/VwI4NYebpw
#AIReform#BrainCA
What if AI could run on a watch battery? No cloud. No server farm.
Brain-CA is rethinking intelligence from the ground up — sensors, drones, industrial systems. Anywhere a sensor can go.
CEO Steve Brunker explains 🎥 https://t.co/XyOvsGN8Vi
#AI#EdgeAI#DeepTech#BrainCA
The human brain doesn't retrain overnight.
It observes. Adjusts. Updates incrementally from experience.
AI doesn't have to work the other way either.
#AI#StochasticAI#BrainCA#TechThoughts
Frozen models can't adapt. Retraining cycles eat compute.
Most ML problems trace back to one cause: a model that stopped learning at deployment.
Brain-CA's Estimator never stops. 👇
https://t.co/mqsBgTa6nt
#EdgeAI#StochasticAI#MLEngineering#BrainCA
The human brain runs on 20 watts.
A single AI query can use the energy of 10 Google searches.
We built something incredible. We just didn't build it to run forever.
That's the gap Brain-CA is closing — one inference at a time.
#AI#SustainableAI#EnergyEfficientAI#BrainCA
80% of AI's energy moves data — not thinking.
That's the round trip no one planned for at scale.
Brain-CA's Estimator eliminates it. 👇
#EfficientAI#AIInfrastructure#EdgeAI#BrainCA
The AI energy conversation just shifted.
In 2025, inference passed training as the dominant cost for the first time. By 2026: 63% inference, 37% training.
The problem was always inference. 👇
https://t.co/IQ47iL6vnC
#AIInfrastructure#EnergyEfficientAI#Inference#BrainCA
The first intelligent organisms weren't doing math.
They were storing states and flipping them.
The AI industry built systems that work the opposite way. It works.
But the energy cost is enormous.
#StochasticML#AI#SustainableAI#DeepTech#BrainCA
Does learning require math?
A poker player reads opponents with no calculations. Observation and a flip.
Brain-CA's Estimator: no arithmetic. Bayesian-quality results.
Math is implied. Doesn't have to be performed.
https://t.co/6nc3pXa7j9
#StochasticML#EnergyEfficientAI#BrainCA
Most AI learns by being wrong about everything first.
Billions of random parameters. Millions of corrections.
Brain-CA starts from zero. Builds only what the data justifies.
Think poker player, not calculator. 👇
https://t.co/6nc3pXa7j9
#StochasticML#EnergyEfficientAI#BrainCA
We built AI that can write poetry and solve equations.
We also built AI that's draining reservoirs.
The industry's answer: replenishment pledges.
What if the architecture didn't need so much water?
#GreenAI#AIWaterConsumption#Sustainability#DeepTech#BrainCA
90% of AI training energy goes to moving data. Not computing. Moving.
That movement generates heat. Heat needs cooling water. Better cooling towers don't fix that.
The architecture does.
https://t.co/3zcnd9IrsC
#AIWaterConsumption#VonNeumannBottleneck#EnergyEfficientAI#BrainCA
Most people know AI uses energy. But it's draining reservoirs.
100-word prompt = ~519ml of water. Texas data centers could hit 399B gallons by 2030.
Root cause isn't cooling. It's the architecture.
👇 https://t.co/r9N1dM3ocx
#AIWaterConsumption#GreenAI#SustainableAI#BrainCA
A device that can't function without a cloud connection isn't autonomous.
It's a remote terminal with good branding.
The real AI challenge isn't scale. It's self-sufficiency.
#EdgeAI#AI#Autonomy#DeepTech#BrainCA
Most "edge AI" is just cloud AI with a longer cable.
Frozen models can't adapt. When things change, the device fails or phones home.
Real-time endpoint inference is different. Here's how 👇
https://t.co/IpS2YN7Vre
#EdgeAI#AIInference#EndpointAI#MachineLearning