(6/6) No cloud reliance. No massive GPU clusters. Just raw, physical intelligence deployed directly onto silicon.
The physics of AI is changing. Later this week, we are open-sourcing the core architecture of how we did it.
#AI#ML#WorldModels#EdgeAI#DefenseTech
(5/6) For eight years in stealth, we at @BalnceLabs has engineered a different path. We didn't just build a foundational world model; we designed it strictly for micro-second determinism at the absolute edge.
(4/6) But while billions of dollars are being poured into building these models for massive data centers, we realized a fundamental physical constraint: you cannot put a server farm inside an autonomous vehicle, a drone swarm, a fighter jet or a robotic chassis.
(2/6) The smartest minds in the industry know this. @ylecun's push toward JEPA with $1B raised for @amilabs, @drfeifei’s $1B raise for @theworldlabs, and @JeffBezos backing Physical Intelligence all point to the exact same truth: True AI doesn't render text.
(1/6) The era of pure text prediction is over. Generative LLMs are an incredible parlor trick, but they are an intellectual dead end for physical intelligence.
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(1/5) True artificial intelligence cannot just live in the cloud, processing text. It has to compute the physical world. @TheAbhiRagh@AshikVarma3@arun_jv
(5/5) To build AI that actually understands the physical world, you have to engineer the entire pipeline, from the inference logic on the silicon to the neural architecture itself.
We aren't waiting for the next generation of AI. We are compiling it.
#WorldModels
(1/5) True artificial intelligence cannot just live in the cloud, processing text. It has to compute the physical world. @TheAbhiRagh@AshikVarma3@arun_jv
(4/5) At Balnce, we don't borrow tech stacks. We build our own architectures, forge our own hardware-agnostic frameworks, and train our models completely from scratch.
(3/4) We are not an LLM company. We do not do next-token prediction for chatbots.
Realizing the true potential of artificial intelligence requires going deeper than the application layer. It requires writing the underlying physics of how machines compute.