Genesis Startup Competition Pitch
summary
Literal Labs presents a logic‑based AI stack that binarizes data and uses propositional logic plus settling machines to cut compute complexity, retrofit to existing silicon, and run on CPUs without GPUs. Benchmarks show 250x faster than XGBoost and versus an FC autoencoder achieve 52x lower power; models have tiny memory footprints and can run 10 years on a coin cell (one prediction every 5.8s) or one per second on AA. A training tool booleanizes datasets, selects and deploys models; £4.6M pre-seed and live pilots in water, automotive and food supply chains.
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chapters (6)
- 0:00Introduction to AI at the edge
- 1:55New AI architecture for edge
- 3:59Performance results and real-world impact
- 5:25Product offering and business model
- 6:51Market traction and team
- 7:33Q&A session
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