University of Massachusetts Awarded DITTO Contract to Improve AI

UMass teams with Lockheed Martin Advanced Technology Laboratories to design machine learning framework
Hava Siegelmann
Hava Siegelmann

AMHERST, Mass. – The Defense Advanced Research Projects Agency (DARPA) has awarded the University of Massachusetts Amherst Biologically Inspired Neural & Dynamical Systems (BINDS) Laboratory, the DARPA DITTO – Intelligent Auto-Generation and Composition of Surrogate Models project. This is one of the agency’s AI Explorations. UMass’s co-PI on this award is Lockheed Martin Advanced Technology Laboratories. DITTO aims at developing an AI machine learning framework that can speedily simulate a complex system by automatically generating surrogate models for system’s component and integrating them into one design. The UMass-LM team seeks to design a machine learning framework with their Modular Knowledgeable AI (MOKA) system.

MOKA provides a large leap in AI by incorporating the meta-cognition of all available knowledge at a level of accuracy not previously possible, and the design of an original neural compiler that aggregates models effectively into a modular system working accurately locally and as a single super-intelligent system globally.

Hava Siegelmann, director of the UMass Amherst BINDS lab, said, “Meta-cognition is the ability of the human mind to leverage knowledge about the self in relation to a given task. Our proposed MOKA system will incorporate knowledge about self, its inputs, and other components it may interface with, already starting at the neural architecture. This will lead to computing that is informed of itself and its environment. This capability will vastly reduce the reliance and time of training and also greatly improve capabilities and accuracy.”

“This is an exciting opportunity for Lockheed Martin Advanced Technology Laboratories to work with the BINDS lab”, said Janet Wedgwood, Lockheed Martin lead engineer on the DITTO project, “We are combining our vast experience in Integrated Circuits design and testing with the top level of the University’s machine learning neural networks to propose an automated proof-of-concept software framework for fast and accurate testing of new and updated designs.”

The complexity and time-consuming nature of state-of-the-art hardware simulations have a significant impact on the cost and schedule of system development. Design flaws can translate into a loss of millions to billions of dollars in funding to fix and prevent dangerous outcomes. The MOKA system reduces those costs by incorporating knowledge at the neural architecture, keeping a robust awareness about itself and its environment, a capability that reduces the need for training while greatly improves accuracy.

Lockheed Martin is a global security and aerospace company that employs approximately 110,000 people worldwide and is principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products and services.

The Biologically Inspired Neural & Dynamical Systems (BINDS) Laboratory at the Computer Science Department, was created to advance research in the interface between biological (and neuroscience) computing and artificial intelligence, improving knowledge, building superior AI and using the results to contribute to humanity.