Lifeboat Foundation

Amazon’s Prime Air drone delivery plans scored a boost on Thursday. The Federal Aviation Administration approved an exemption allowing the company to move forward with operations while working towards formal certification of the MK27 UA aircraft and the airline operations. The approval comes with significant limits, but allows the company to continue development of the platform and supports progress towards the necessary certifications.

The relief provided in this 44807 exemption would enable the Amazon MK27 unmanned aircraft (MK27 UA) and associated aircraft systems (MK27 UAS) to operate in cargo delivery operations without an airworthiness certificate. The FAA concludes that Amazon’s compliance with the conditions and limitations of this exemption, along with the FAA’s safety evaluation of the MK27 UAS, will enable Amazon’s operations using the MK27 UAS without adversely affecting safety. Amazon is currently engaged in the process to receive a type certificate for the MK27 UAS utilized in its operations.

Services to include spotting racial bias, developing guidelines around AI projects.

Denis Shiryaev uses algorithms to colorize and sharpen old movies, bumping them up to a smooth 60 frames per second. The result is a stunning glimpse at the past.

This is a working proof of concept of the NeuralLace. It can detect limb motion and smell sensation via neural implants in the brain. So far it’s only been tested in pigs, but an early usecase might be a digital replacement for spinal cord injuries. But the real future goal about is getting to implant an internet enabled AI into your brain.

Elon Musk showed off Neuralink’s new implantable brain chip and demonstrated it working in real time on a pig.

Continue reading “Neuralink: Elon Musk’s entire brain chip presentation in 14 minutes (supercut)” »

The White House on Wednesday will announce that federal agencies and their private sector partners are committing more than $1 billion over the next five years to establish 12 new research institutes focused on artificial intelligence and quantum information sciences.

The effort is designed to ensure the U.S. remains globally competitive in AI and quantum technologies, administration officials said.

Why underwater robots are vacuuming up lionfish.

This tiny battery could change the game for micro robots.

Abstract: Advances in high speed imaging techniques have opened new possibilities for capturing ultrafast phenomena such as light propagation in air or through media. Capturing light-in-flight in 3-dimensional xyt-space has been reported based on various types of imaging systems, whereas reconstruction of light-in-flight information in the fourth dimension z has been a challenge. We demonstrate the first 4-dimensional light-in-flight imaging based on the observation of a superluminal motion captured by a new time-gated megapixel single-photon avalanche diode camera. A high resolution light-in-flight video is generated with no laser scanning, camera translation, interpolation, nor dark noise subtraction. A machine learning technique is applied to analyze the measured spatio-temporal data set. A theoretical formula is introduced to perform least-square regression, and extra-dimensional information is recovered without prior knowledge. The algorithm relies on the mathematical formulation equivalent to the superluminal motion in astrophysics, which is scaled by a factor of a quadrillionth. The reconstructed light-in-flight trajectory shows a good agreement with the actual geometry of the light path. Our approach could potentially provide novel functionalities to high speed imaging applications such as non-line-of-sight imaging and time-resolved optical tomography.

One of the biggest impediments to adoption of new technologies is trust in AI.

Now, a new tool developed by USC Viterbi Engineering researchers generates automatic indicators if data and predictions generated by AI algorithms are trustworthy. Their research paper, “There Is Hope After All: Quantifying Opinion and Trustworthiness in Neural Networks” by Mingxi Cheng, Shahin Nazarian and Paul Bogdan of the USC Cyber Physical Systems Group, was featured in Frontiers in Artificial Intelligence.

Neural networks are a type of artificial intelligence that are modeled after the brain and generate predictions. But can the predictions these neural networks generate be trusted? One of the key barriers to adoption of self-driving cars is that the vehicles need to act as independent decision-makers on auto-pilot and quickly decipher and recognize objects on the road—whether an object is a speed bump, an inanimate object, a pet or a child—and make decisions on how to act if another vehicle is swerving towards it.