U.S. Air Force testing artificial intelligence on fighter jets

Can artificial intelligence effectively fly combat aircraft? The U.S. Air Force is currently testing an experimental XQ-58 aircraft code-named "Valkyrie" to verify this theory. The XQ-58 was developed in partnership with the Air Force Research Laboratory (AFRL) and defense contractor Kratos to demonstrate the potential of artificially intelligent drones known as "collaborative combat aircraft" in combat.

While the XQ-58 does not have a pilot, it will be equipped with missiles and bombs, as well as data-gathering sensors. The aircraft can be used for certain high-risk missions, such as destroying anti-aircraft positions deep in enemy territory. The idea is to surround a manned aircraft, such as an F-35 or F-22, with a swarm of coordinated combat aircraft. The drone does not fire its weapons on its own but is controlled by a nearby pilot.

The core problem is the rising cost of fighter jets. The Air Force's main fighter, the F-35 Lightning II, sells for $80 million each, while the air superiority fighter, the F-22 Raptor, sells for $143 million each. This has led the U.S. Air Force to reduce the size of its fighter fleet to its lowest level ever.

Drones are much cheaper to build, with costs ranging from $3 million each to $25 million for more complex aircraft like the XQ-58. According to a New York Times article this week, this will make it "affordable" for the Air Force.

It remains to be seen whether artificial intelligence can replicate the movements of an experienced pilot. Known as Tactical Autonomy, the Air Force Research Laboratory has invested millions of dollars in testing airframes and algorithms for unmanned flights, including the Valkyrie, MQ-20 Avenger, UTAP-22 MAKO and VISTA X-62 .

The latest collaborative combat aircraft tested is called "Valkyrie". Last month, the U.S. Air Force Research Laboratory (AFRL) announced that the Valkyrie and its artificial intelligence and machine learning-driven systems successfully conducted a three-hour training flight

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