SGS to explore AI to enhance mission readiness and decision optimisation
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SGS to explore AI for enhanced mission readiness and decision optimisation

08 Apr 2021

SparkCognition Government Systems (SGS) has been contracted to use artificial intelligence (AI) to enhance mission readiness and decision optimisation for the US Air Force.

SGS to explore AI for enhanced mission readiness and decision optimisation
The contract was awarded as part of AFRL’s SBIR programme. Credit: Gerd Altmann / Pixabay.

SparkCognition Government Systems (SGS) has been contracted to use artificial intelligence (AI) to enhance mission readiness and decision optimisation for the US Air Force.

Under the contract, SGS will use AI technologies to study the application of machine learning (ML) capabilities to create a tool that improves manpower planning effectiveness and scalability.

Currently, the manpower planning process methodology requires a large amount of labour to meet expectations.

With the availability of a large amount of data for the US Department of Defense (DoD) decision-makers, the data-driven approach of ML decreases manual recalibration to deliver improved results.

The contract is the first phase of US Air Force Research Laboratory’s (AFRL) Small Business Innovation Research (SBIR) programme.

The SBIR programme encourages small businesses to focus on federal research/research and development (R&D) with the ‘potential for commercialisation’.

SparkCognition Government Systems president and general manager Logan Jones said: “At SGS, we are committed to ensuring warfighter readiness, and we know the future lies in artificial intelligence.

“For the DoD, effective and efficient mission readiness and decision optimisation is at the top of the list of priorities. With that in mind, we’re excited to work with the AFRL and AFWERX to advance the applications of AI in these areas.”

According to SGS, AFRL and AFWERX teamed up to simplify the SBIR process. This streamlining will help ramp up the experience, widen the potential applicant pool, and reduce bureaucracy and overhead.