Algorithmia, a provider of enterprise machine learning operations (MLOps) software, has been selected by Raytheon Intelligence & Space, a Raytheon Technologies (NYSE: RTX) business to support the team’s development of the U.S. Army’s Tactical Intelligence Targeting Access Node (TITAN) program. TITAN is a tactical ground station that finds and tracks threats to support long-range precision targeting.

Algorithmia, along with other leaders in artificial intelligence and machine learning, will enable Raytheon Technologies TITAN team to deliver easily digestible data to Army operators. TITAN will ingest data from space and high-altitude, aerial and terrestrial sensors to provide targetable data to defense systems. It also provides multi-source intelligence support to targeting, and situational awareness and understanding for commanders.

Algorithmia’s MLOps platform has been used by over 130,000 data scientists in a wide range of organizations. Its customers include large and midsize enterprises, Fortune 500 companies, the United Nations and multiple government intelligence agencies. The company’s momentum is a product of growing interest in AI-based applications and the need organizations have to efficiently manage cost and security for machine learning models.

“Machine learning significantly accelerates the process by which organizations can uncover important data points and respond to critical issues,” said Diego Oppenheimer, CEO of Algorithmia. “Our platform streamlines the deployment of machine learning models into production while providing important oversight, including review for ethical standards, to ensure models operate when and how they should, which makes Algorithmia a natural fit for sensitive applications. We are excited to join Raytheon in supporting its work with the U.S. Army.”

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ARLINGTON, Va. – Sensors experts at Raytheon Technologies Corp. will develop a new kind of camera and digital signal processing to enable electro-optical smart sensors for tactical military applications.

Officials of the U.S. Defense Advanced Research Projects Agency (DARPA) in Arlington, Va., announced an $8.8 million contract Wednesday to the Raytheon Intelligence & Space segment in El Segundo, Calif., for the Fast Event-based Neuromorphic Camera and Electronics (FENCE) project.

FENCE seeks to develop and demonstrate a low-latency, low-power, event-based camera and a new class of digital signal processing and machine learning algorithms that use combined spatial and temporal information to enable intelligent sensors for tactical military applications.

Neuromorphic describes silicon circuits that mimic brain operation; it exhibits low latency, sparse output, and extreme energy efficiency. Neuromorphic cameras offer sparse output, and respond only to changes in the scene, with accompanying low latency and low power for small-format cameras in sparse scenes.

Event-based imaging sensors operate asynchronously, and only transmit data from pixels that have changed, so they produce 100 times less data in sparse scenes than traditional focal plane arrays (FPAs). This leads to 100x lower latency at 100x lower power.

Despite their inherent advantages, existing event-based cameras are not compatible with military applications because military images are cluttered and dynamic. The FENCE program seeks to develop an integrated event-based infrared focal plan array with embedded digital signal processing to overcome these challenges.

The FENCE program’s primary focus is on developing an asynchronous read-out integrated circuit (ROIC) capable of very low latency and power operation, and a new, low-latency event-based infrared sensor with in-pixel processing.

The project also will develop a low-power processing layer that integrates with the ROIC to identify relevant spatial and temporal signals. The ROIC and the processing layer together will enable an integrated FENCE sensor that can operate on less power than 1.5 Watts.

The FENCE program will last for four years, and DARPA researchers issued their broad agency announcement for the project last October. Raytheon may not be the only FENCE contractor, as DARPA officials say they plan to award contracts to several companies.

On this contract Raytheon will do the work in Goleta and El Segundo, Calif.; Cambridge and Tewksbury, Mass.; McKinney, Texas; Tempe, Ariz.; and New York City, and should be finished by May 2025.

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Raytheon Technologies has infused emerging technology into the company’s modeling and simulation process as part of efforts to help defense customers visualize the performance of weapons systems before they make procurement decisions.

The company said Wednesday an engineering team within its missiles and defense business used artificial intelligence and machine learning to put a Standard Missile-3 Block IIA missile through digital testing ahead of a flight test demonstration conducted by the U.S. Navy and the Missile Defense Agency in November last year.

Engineers collected and integrated data from previous SM-3 interceptor tests into a model as part of the process.

“AI and machine learning are critical to the company’s modeling and simulation framework,” Bob Fitzpatrick, vice president of requirements and capabilities at Raytheon Missiles & Defense.

“Every new flight test and every new experiment looks a little different than the last one and that means there’s a lot of rapid learning happening for the company and its customers,” Fitzpatrick added.

Wes Kremer, president of Raytheon Missiles & Defense, noted that modeling and simulation could help the warfighter understand the potential of current and future platforms to gain an edge in battlefield missions.

The company received a potential $722.4 million contract from the MDA in late October to provide SM-3 engineering and technical support to U.S. and international defense customers.

Potomac Officers Club will host its 2020 Industrial Space Defense Summit on March 23 and its 3rd Annual Artificial Intelligence Summit on March 30. To register for these virtual summits and view other upcoming events, visit the Potomac Officers Club Events page.FacebookTwitterLinkedInEmailShare

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