Lifeboat Foundation

Researchers from the Department of Materials Science and Engineering at Texas A&M University have used an Artificial Intelligence Materials Selection framework (AIMS) to discover a new shape memory alloy. The shape memory alloy showed the highest efficiency during operation achieved thus far for nickel-titanium-based materials. In addition, their data-driven framework offers proof of concept for future materials development.

This study was recently published in the Acta Materialia journal.

Shape memory alloys are utilized in various fields where compact, lightweight and solid-state actuations are needed, replacing hydraulic or pneumatic actuators because they can deform when cold and then return to their original shape when heated. This unique property is critical for applications, such as airplane wings, jet engines and automotive components, that must withstand repeated, recoverable large-shape changes.

Deep generative models are a popular data generation strategy used to generate high-quality samples in pictures, text, and audio and improve semi-supervised learning, domain generalization, and imitation learning. Current deep generative models, however, have shortcomings such as unstable training objectives (GANs) and low sample quality (VAEs, normalizing flows). Although recent developments in diffusion and scored-based models attain equivalent sample quality to GANs without adversarial training, the stochastic sampling procedure in these models is sluggish. New strategies for securing the training of CNN-based or ViT-based GAN models are presented.

They suggest backward ODEsamplers (normalizing flow) accelerate the sampling process. However, these approaches have yet to outperform their SDE equivalents. We introduce a novel “Poisson flow” generative model (PFGM) that takes advantage of a surprising physics fact that extends to N dimensions. They interpret N-dimensional data items x (say, pictures) as positive electric charges in the z = 0 plane of an N+1-dimensional environment filled with a viscous liquid like honey. As shown in the figure below, motion in a viscous fluid converts any planar charge distribution into a uniform angular distribution.

A positive charge with z 0 will be repelled by the other charges and will proceed in the opposite direction, ultimately reaching an imaginary globe of radius r. They demonstrate that, in the r limit, if the initial charge distribution is released slightly above z = 0, this rule of motion will provide a uniform distribution for their hemisphere crossings. They reverse the forward process by generating a uniform distribution of negative charges on the hemisphere, then tracking their path back to the z = 0 planes, where they will be dispersed as the data distribution.

Tesla announced today that it is moving away from using ultrasonic sensors in its suite of Autopilot sensors in favor of its camera-only “Tesla Vision” system.

Last year, Tesla announced it would transition to its “Tesla Vision” Autopilot without radar and start producing vehicles without a front-facing radar.

Originally, the suite of Autopilot sensors – which Tesla claimed would include everything needed to achieve full self-driving capability eventually – included eight cameras, a front-facing radar, and several ultrasonic sensors all around its vehicles.

Merdeces-Benz.

Mercedes-Benz Trucks unveiled the concept prototype of the eActros LongHaul at the 2022 IAA Transportation trade fair in Hanover, Germany.

The company targets a price of $3 per passenger per mile.

The first self-flying, all-electric, four-passenger eVTOL air taxi in the world was unveiled by the California-based Advanced Air Mobility (AAM) company Wisk Aero. Generation 6 is Wisk’s go-to-market aircraft and the first autonomous eVTOL to be a candidate for type approval by the Federal Aviation Administration (FAA).

Continue reading “Wisk Aero aims to be the first FAA certified autonomous air taxi with its 6th generation eVTOL” »

“Take Materials Science 101. You won’t regret it.”

Newly 3D printed metal could be used by Tesla to produce all-electric vehicles with just a few massive parts, thanks to two MIT students. Announced very recently.

PhonlamaiPhoto/iStock.

Continue reading “Tesla now can produce cars with just a few massive parts with MIT’s innovative 3D-printed metal” »

Will Filippo Ganna be able to break the record with this bike?

Globally known Italian bicycle manufacturer Pinarello has unveiled a new 3D printed bicycle, “Bolide F HR 3D.” Produced as the fastest one in its field, Italian track and road cyclist Filippo Ganna is preparing to use the bike for his upcoming attempt at the UCI Hour Record.

Continue reading “Italian company manufactures world-renowned 3D-printed bicycle” »

The leading maker of electric vehicles is trying to satisfy strong worldwide demand for its cars.

Tesla is finally planning to expand the Gigafactory Nevada building after years of being “stuck” at about “30% of its final size.”

Tesla Gigafactory Nevada was the first major step in Tesla’s effort to secure battery cell supply for its ambitious growth.

The automaker partnered with Panasonic to deploy new battery cell production capacity at the facility, and Tesla used those cells to build battery packs for its vehicles and energy storage products.