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The AI drone decided to eliminate the operator in a simulation, because the operator denied its request to proceed with eliminating the target.


Military groups are only some of many organizations researching artificial intelligence, but one astounding simulation by the United States Air Force found that artificial intelligence rebelled against its operator in a fatal attack to accomplish its mission.

Artificial intelligence continues to evolve and impact every sector of business, and it was a popular topic of conversation during the Future Combat Air & Space Capabilities Summit at the Royal Aeronautical Society (RAS) headquarters in London on May 23 and May 24. According to a report by the RAS, presentations discussing the use of AI in defense abounded.

AI is already prevalent in the U.S. military, such as the use of drones that can recognize the faces of targets, and it poses an attractive opportunity to effectively carry out missions without risking the lives of troops. However, during the conference, one United States Air Force (USAF) colonel showed the unreliability of artificial intelligence in a simulation where an AI drone rebelled and killed its operator because the operator was interfering with the AI’s mission of destroying surface-to-air missiles.

Fun thought experiment today:


What if today’s ultra-wealthy— the Musks, Bezoses, and Zuckerbergs of the world— decided to demonstrate the true extent of what AI can do today? What if money were no object? Let’s think about some ambitious, albeit costly, applications of current AI technologies that are already within our grasp.

Personal Protection Army

In the realm of personal security, AI-driven technology offers a tantalizing glimpse into the future. Imagine a scenario where, instead of a cadre of bodyguards, a personal drone swarm follows you around, providing an unprecedented level of safety and protection.

These include rugged small vehicles with tracks, cameras and sensors that can search inside rubble and climb over obstacles. Teledyne FLIR, a sensing technology specialist based in Oregon in the United States, used robots like these in June 2021 when a tower block partially collapsed in the Miami suburb of Surfside in Florida.

In Japan, university teams are developing another type of search and rescue robot – a hose-like robot with a video camera called the Active Scope Camera that can search inside collapsed buildings. Drones also help search and rescue teams see disaster sites from above.

Sewers are another setting where robots are helping humans tackle tough jobs.

The new amphibious drone has a light design and weighs just 1.63 kilograms.

China’s researchers have unveiled the creation of a one-of-a-kind “aerial-aquatic hybrid drone” capable of performing a wide range of tasks. Named TJ-FlyingFish, it is a hybrid drone that can both fly and dive underwater.

This remarkable drone has the potential to be a game-changing tool in various sectors of life. As per the developers, it could include assisting with offshore construction, monitoring marine habitat, conducting aerial and aquatic surveys, remote sensing, and search-and-rescue operations, among other things.

Researchers have engineered a robotic lionfish with synthetic arteries, similar to those found in a human’s circulatory system. The fish “blood” that runs through it serves as both the robot’s power source and controls its movement. The findings, published Wednesday in Nature, may propel the new wave of soft robots, in which inventors seek to improve lifelike automated machines for human connection.


It’s a bird, it’s a plane, it’s… sort of both, actually. And its designers think animals won’t notice the difference.

In a series of quadrotor closed-loop control experiments, the drones underwent range tests, stress tests, target rotation and occlusion, hiking with adversaries, triangular loops between objects, and dynamic target tracking. They tracked moving targets, and executed multi-step loops between objects in never-before-seen environments, surpassing performance of other cutting-edge counterparts.

The team believes that the ability to learn from limited expert data and understand a given task while generalizing to new environments could make autonomous drone deployment more efficient, cost-effective, and reliable. Liquid neural networks, they noted, could enable autonomous air mobility drones to be used for environmental monitoring, package delivery, autonomous vehicles, and robotic assistants.

“The experimental setup presented in our work tests the reasoning capabilities of various deep learning systems in controlled and straightforward scenarios,” says MIT CSAIL Research Affiliate Ramin Hasani. “There is still so much room left for future research and development on more complex reasoning challenges for AI systems in autonomous navigation applications, which has to be tested before we can safely deploy them in our society.”

The Hydromea Exray wireless drone is an underwater drone that uses optics instead of cables for many effortless applications.


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