Luffy AI funding news – UK-based Luffy AI Secures an Investment from Momenta
Jun 7, 2024 | By Team SR
Luffy AI, a company which specializes in adaptive AI for industrial control, secures an investment from Momenta. The deal's total value was not made public.
SUMMARY
- Luffy AI, a company which specializes in adaptive AI for industrial control, secures an investment from Momenta.
- Luffy AI has developed ultra-efficient, adaptive neural networks that enable true learning and adaption at the edge.
The funds will be used by the corporation to improve operational results and industrial processes. Luffy AI, under the direction of CEO Dr. Matthew Carr, develops adaptable neural networks that enable control and adaptation at the edge.
Their AI control systems are able to maintain optimal process efficiency over time by adapting to changes and learning the subtleties of the process they are controlling. Driven by neuroplasticity, its Adaptive Intelligence Framework provides edge deployments of optimised industrial control applications with computing efficiency.
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Control systems can now continuously learn and adapt thanks to technology, which gives them an advantage over classic AI models in terms of resilience and effectiveness. Luffy's approach combines self-optimizing neural networks with digital twin models to provide a number of advantages, including lower maintenance costs, better explainability, and increased capacity to handle unforeseen circumstances.
The technique addresses difficult control problems and creates new avenues for the industries of petrochemicals, manufacturing, chemicals, metals and mining, and aviation to use machine control.
About Luffy AI
Luffy AI has developed ultra-efficient, adaptive neural networks that enable true learning and adaption at the edge. At over 800 times more computationally efficient, we can target applications completely inaccessible to current AI approaches.
Luffy is leveraging this advantage to build AI control systems that learn the nuances of the equipment and adapt to changes over time to obtain maximum performance and robustness.