The U.S. Air Force showcases its first AI fighter jet with high profile! The minister personally conducted the test drive without interfering during the whole process, and 100,000 lines of code were tested for 21 times.

Estimated read time 10 min read

Recently, the military circle has been overwhelmed by the news: US military fighter jets can now complete fully automatic air combat using AI.

Yes, just recently, the US military’s AI fighter jet was made public for the first time, unveiling its mystery.

The full name of this fighter is the Variable Stability Flight Simulator Test Aircraft (VISTA). It was personally flown by the Secretary of the U.S. Air Force to simulate a one-on-one air battle.

On May 2, U.S. Air Force Secretary Frank Kendall took off in an X-62A VISTA at Edwards Air Force Base.

Note that during the one-hour flight, all flying actions are completed autonomously by AI!

Kendall said——

For decades, we have imagined the unlimited potential of autonomous air-to-air combat, but it has always remained out of reach. But now, we have reached a moment of transformation, and it is the breakthrough achievements of the ACE team that make this possible.

The Secretary of the Air Force personally conducted a test flight

It can be seen that under the blazing sunshine at noon, an orange and white F-16 fighter jet takes off with a roar – it is controlled by AI, not a human pilot.

During the test flight, U.S. Air Force Secretary Frank Kendall sat in the front seat of the aircraft. Accompanied by a safety pilot in the back seat, he completed a set of test tasks without touching the X-62A controls.

AI controls the F-16 to fly at speeds of more than 550 miles per hour, which directly puts Kendall’s body under the pressure of five times the force of gravity.

It approached an F-16 piloted by a human pilot. The two aircraft were racing within a distance of only 304 meters, twisting and circling in an attempt to force the other into a weak position.

After the one-hour flight, Kendall walked out of the cockpit with a smile.

He said he had seen enough evidence during his flight that he was willing to trust the AI ​​to decide whether to launch weapons in a war.

The AI ​​software on the aircraft will first learn from millions of data points in the simulator, and then verify the conclusions during actual flights. These real-world performance data are then re-entered into the simulator, where the AI ​​processes the data for in-depth learning.

VISTA’s military operators claimed that the United States is the only country in the world to possess similar AI aircraft.

The first AI vs. human dog fight

As early as April 2024, the U.S. Air Force Test Pilot School and DARPA announced that they had completed the first dog fight between AI and humans.

The dogfight was completed by an F-16D (Block 30) two-seat aircraft code-named X-62A VISTA and a human pilot flying an F-16 fighter jet.

In the dog fight, the X-62A demonstrated defensive maneuvers, attack twitching and other skills, while the human pilot sitting in it could take over the AI ​​system without activating the safety switch.

The two aircraft demonstrated a “high-angle nose-to-nose battle”, with their relative speed reaching 1,200 miles per hour, and the closest distance reaching about 610 meters.

The X-62A’s safe and autonomous dogfighting on another manned aircraft is an important milestone not only for ACE, but for autonomous flight as a whole.

Moreover, DARPA and the Air Force emphasized that although dog fighting is the core of this test, the goal of ACE is far from being as simple as dog fighting.

Bill Gray, chief test pilot of the U.S. Air Force USAF TPS, explained: Dog fighting is a problem that needs to be solved, so they began to test autonomous AI systems in the air.

Every lesson we learned applies to any task you can give an autonomous system.

X-62A and F-16 during simulated dog fight

21 test flights, 100,000 lines of code

VISTA, also known as X-62A, is a modified version of the General Dynamics F-16D.

The U.S. Air Force has been using it to test advanced technologies since the 1990s.

Today, VISTA has been integrated into DARPA’s Air Combat Evolution Program ACE, equipped with machine learning and specialized software.

VISTA was developed by Lockheed Martin, a defense technology company.

VISTA can be seen as an AI pathfinder, which uses a new driverless design.

This work is crucial to realizing distributed teams.

The efficiency of the team is also amazing. In less than a year, the initial real-time AIAgent was installed in the X-62A system, demonstrating the first AI-human dog fight, and in 21 test flights , completed changes to more than 100,000 lines of critical code for flight software.

X-62A cockpit during last year’s simulated dog fight

The vice president of Lockheed Martin said that X-62A VISTA is an important platform for them to develop, test, integrate AI, and establish AI certification standards.

Moreover, X-62A VISTA will completely change the future of aerospace.

The hardware and software architecture in the platform are proven and provide a safe and controllable environment for AIAgent and advanced algorithms, allowing them to quickly prototype and develop.

This open architecture enables highly complex testing by leveraging Skunk Works’ Model Tracking Algorithm (MFA) and Simulated Autonomous Control System (SACS).

These important updates not only enhance VISTA’s capabilities, but also maintain its advantage for rapid prototyping.

As a result, the team was able to make rapid software changes and conduct frequent flight tests.

Test after test has proven that this architecture is powerful enough to reliably transition to third-party distributed hardware and replicate the safe and controllable flight test goals demonstrated by VISTA.

AI has achieved breakthrough impact on autonomous air combat

The first battle between the X-62A and the manned F-16 in April was a milestone event.

It was this incident that made machine learning in 2023 a reality in the sky.

The future U.S. drone program and the U.S. Air Force’s collaborative fighter program will be directly affected.

Shield AI, a participant in the ACE program, acquired Heron in 2021.

The AI ​​pilot developed by Heron had won DARPA’s dog fighting test the previous year.

As early as 2022, DARPA worked with the Air Force and Lockheed Martin to integrate AIAgent into the X-62A system, and in December of that year, it used these algorithms to conduct the first autonomous test flight of the jet.

The X-62A/VISTA’s flight system can be configured to imitate any other aircraft model, which allows it to complete a variety of testing purposes, making it an ideal platform to support work such as ACE.

Que Harris, Lockheed Martin’s chief flight control engineer, said the team has an integration space in VISTA’s flight control that allows the AIAgent to send commands to VISTA as if they were sending commands to VISTA’s simulation model.

This can be thought of as an “autonomous sandbox” inside the jet.

Dr. Chris Cotting, director of the USAF TPS, described it this way: It’s like you have a simulator laboratory in a research institution.

“We’ve packed the entire simulator lab into the F-16.”

As we mentioned above, during the subsequent 21 test flights of the X-62A, the Agent needed to be reprogrammed almost every day, and the final modified code reached 100,000 lines.

By rapidly training and retraining algorithms in a fully digital environment, the X-62A can support a variety of flight tests.

No pilot, no communication, fully realize the swarm concept

Brandon Tseng, co-founder and president of Shield AI, said that the ideal autonomous aircraft would look like this –

There is no remote pilot, no communications, and no GPS. These aircraft implement the concept of a formation or swarm that can carry out the commander’s intent.

They can execute missions, working together dynamically, reacting to each other, as well as to the battlefield, hostile threats and civilians on the ground.

Another value embodied by this technology is to make the entire system and the entire fleet better.

At any time, the best AI pilot can be on board the aircraft. When learning on a fleet, there are them on every aircraft.

“You will always have the best quadcopter pilots, the best V-BAT pilots, the best CCA pilots. They will dominate. Then you will be able to win the engagement with an incredibly high win rate.” .

Big challenge: You need to trust the algorithm to implement it in reality

However, this process also presents difficult challenges.

First, there is rule-based autonomy.

Dr. Daniela Rus of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) explains that if you write rules in an “if-then” way, they must be robust. Therefore, in order for the system to work properly, a team of experts is needed to generate the code.

Dr. Rus explained that because machine learning relies heavily on analyzing historical data when making decisions, they often find insights that humans cannot detect, or non-traditional language expressions that are not rule-based.

Machine learning is very powerful in environments and situations where conditions fluctuate dynamically, making it difficult to establish clear and strong rules.

The so-called “environment and situation” are the unknowable independent decisions made by the human opponent in a dog fight.

Given this unpredictability, conducting such simulated engagements is extremely dangerous even for well-trained pilots.

Accident and fatality data during dogfighting training with F-16 and F/A-18 fighter jets from 2000 to 2016

Air Force Col. James Valpiani, commander of U.S. Air Force TPS, said many elements involved in using machine learning are not fully understood.

“Understandability and verification hinder us from exploring this area.” Currently, there is no civilian or military way to certify machine learning agents for flight-critical systems.

And this is indeed where ACE and the real-world X-62A test flights come into play.

The most important thing about the machine learning agent on the VISTA jet is that it learns to prevent the aircraft from performing dangerous and unethical actions, including defining codes for allowed flight ranges, avoiding collisions in the air or on the ground, and preventing the unauthorized use of weapons.

The U.S. military insists that humans will always be somewhere in the loop in the operation of future autonomous weapons systems, but their exact place in that cycle will evolve over time. This has been the subject of much debate.

“We have to be able to trust these algorithms in order to use them in the real world.”

On April 1, 2024, the first batch of F-16 fighter jets will be converted into autonomous test beds in accordance with the VENOM plan and arrive at Eglin Air Force Base

In addition to the ACE program, the X-62A is not the only aircraft used by the US Air Force for advanced autonomous technology in recent years.

Currently, the Air Force is modifying six additional F-16 aircraft and converting them into experimental aircraft to support a program called Project VENOM for large-scale collaborative autonomous testing.

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