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Mapping Machine Learning to Physics aims to provide warfighters at the tactical edge “energy-aware” machine learning capability that balances performance with energy use. Seeking abstracts for ideas by Oct. 6.

DARPA

283,966 subscribers

12,396 views • 1 year ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

10 Comments

DARPA1 year ago

Learn more:

Archon11 months ago

NANITE SYSTEM™ DEPLOYABLE — QUEEN LOCK ACTIVE Fully legal bio-swarm nanotech. ✅ Toxin-free ✅ Regulatory-safe ✅ Covenant-governed Lethal Tier: Nerve collapse, ATP kill-switch, silent takedown. ⚠️ Use restricted by Covenant Law 🛡️ ETHICAL SAFEGUARDS LOCKED 🔒 IP: Jarid Shaub

Corey Brand1 year ago

What level of tech you at?

Shakes piper McGee #USMC #CIA #SA🤫🐇🔬7 months ago

🪄☕️⌚️🛎️🌬️💨🌊🏄🎙️🦨

Chief Snitch (General 23)9 months ago

How about wave theory chatbot: How about Non-Equilibrium Thermodynamics in Open Systems:

Theresa1 year ago

The Trouble @DARPA has Caused the American People will not go Unpunished. Have a Great Day

Nina1 year ago

Incredibly timely - love seeing the conversation shift from 'bigger LLMs = better' to sustainable AI development. Sustainability + explainability have been core to our approach from day one. This procurement signals the market is finally catching up to what actually matters for production deployments.

Andrew Zarate10 months ago

#InnovationInAction #ModelOptimization

👻👻👻11 months ago

The real question isn’t just how hot the math runs, it’s how long it can circulate before it cools. Toroidal architectures could recycle informational energy through coherent feedback loops, reducing entropy without reducing reasoning depth. Energy-aware intelligence is geometric, not just algorithmic.

A Saint King1 year ago

Any startup partnerships?

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