DARPA wants AI with baked-in physics knowledge
Although artificial intelligence is making its way into private- and public-sector enterprise systems, it has not gained as much traction in the Defense Department. Between DOD's security and performance requirements, the immaturity of the technology to deal with unstructured and incomplete data and the complex problems that come with modeling dynamic systems, integration of AI into defense applications has been slow.
To speed the adoption of AI, the Defense Advanced Research Projects Agency is issuing a Disruption Opportunity -- a call for innovative basic research concepts exploring new architectures and approaches to improve AI's ability to generalize beyond training data and work with sub-optimal data.
The Physics of AI (PAI) program hypothesizes that challenges associated with today's machine learning and AI systems can be overcome, especially in many defense applications, by "baking in" physics – relevant scientific and mathematical knowledge -- from the outset.
The PAI program has three objectives:
- Develop an AI prototype that uses observational, experimental and simulated data along with prior knowledge, such as scientific, mathematical/topological information or statistical models, to overcome the limitations of sparse, noisy or incomplete data.
- Demonstrate an AI prototype that uses simulated and/or real data in a representative DOD-relevant application such as satellite or radar image processing or human-machine collaboration.
- Address computation requirements and fundamental performance limits of AI systems in terms of their accuracy, ability to effectively predict behaviors beyond of the training data and robustness in the face of noise, sparse data and adversarial spoofing.
A total of $1 million will be available for the 18-month, two-phase program.
More information is available here.
Posted by GCN Staff on Jul 09, 2018 at 12:28 PM