Lifeboat Foundation

• Relightable Gaussian Codec Avatars ➡️ https://go.fb.me/gdtkjm • URHand: Universal Relightable Hands ➡️ https://go.fb.me/1lmv7o • RoHM: Robust Human Motion Reconstruction via Diffusion ➡️ https://www.youtube.com/embed/hX7yO2c1hEE

RoHM is a novel diffusion-based motion model that, conditioned on noisy and occluded input data, reconstructs complete, plausible motions in consistent global coordinates. Given the complexity of the problem — requiring one to address different tasks (denoising and infilling) in different solution spaces (local and global motion) — we decompose it into two sub-tasks and learn two models, one for global trajectory and one for local motion. To capture the correlations between the two, we then introduce a novel conditioning module, combining it with an iterative inference scheme. We apply RoHM to a variety of tasks — from motion reconstruction and denoising to spatial and temporal infilling. Extensive experiments on three popular datasets show that our method outperforms state-of-the-art approaches qualitatively and quantitatively, while being faster at test time.

A series of advances in materials and design have enabled manufacturers to work at scales smaller than a billionth of a size to create devices and objects of nanoscopic dimensions. This is nanotechnology, which, although relatively new, produces materials and technologies already used in mass production.

The European Commission defines nano as any material that is at least 50% composed of particles between one and one hundred nanometers in size (i.e. one billionth of a meter, or one-millionth of a millimeter). Nanomaterials differ from conventional materials because of their unique properties such as higher electrical conductivity and mechanical strength, sensor technologies, and biomedical applications, and because they can create coatings that make surfaces more hydrophobic or self-cleaning.

The widespread use of nanotechnology is relatively new. Since 2000, nanomaterials have been used industrially as new research and experimental designs have made their effectiveness in different sectors clear. For example, in the health field, nanotechnology helps to reduce diagnostic errors and to develop nanobots (microscale robots) to repair and replace intercellular structures, or repair DNA molecules; in the chemical sector, it facilitates coating devices with nanoparticles to improve their smoothness and heat resistance; in manufacturing, materials developed with nanotechnology enhance the performance of the final product by improving heat resistance, strength, durability, and electrical conductivity.

As one of the Department of Defense’s 14 critical technology areas, artificial intelligence has taken center stage in the organization’s research and development endeavors.

According to Matt Turek, deputy director of the Defense Advanced Research Projects Agency’s Information Innovation Office, approximately 70 percent of the agency’s programs now use AI and machine learning. Its priorities are not just to develop systems for U.S. warfighters, but to prevent “strategic surprise” from adversary AI systems.

As information technology is moving toward the era of big data, the traditional Von-Neumann architecture shows limitations in performance. The field of computing has already struggled with the latency and bandwidth required to access memory (“the memory wall”) and energy dissipation (“the power wall”). These challenging issues, such as “the memory bottleneck,” call for significant research investments to develop a new architecture for the next generation of computing systems. Brain-inspired computing is a new computing architecture providing a method of high energy efficiency and high real-time performance for artificial intelligence computing. Brain-inspired neural network system is based on neuron and synapse. The memristive device has been proposed as an artificial synapse for creating neuromorphic computer applications. In this study, post-silicon nano-electronic device and its application in brain-inspired chips are surveyed. First, we introduce the development of neural networks and review the current typical brain-inspired chips, including brain-inspired chips dominated by analog circuit and brain-inspired chips of the full-digital circuit, leading to the design of brain-inspired chips based on post-silicon nano-electronic device. Then, through the analysis of N kinds of post-silicon nano-electronic devices, the research progress of constructing brain-inspired chips using post-silicon nano-electronic device is expounded. Lastly, the future of building brain-inspired chips based on post-silicon nano-electronic device has been prospected.

Keywords: brain-inspired chips; neuron; phase change memory; post-silicon nano-electronic device; resistive memory; synapse.

Copyright © 2022 Lv, Chen, Wang, Li, Xie and Song.

Technological singularity: a hypothetical event where artificial intelligence (AI) surpasses human capabilities and leads to a transformative cascade of change.

Technological singularity: a hypothetical event where artificial intelligence (AI), pushed by exponential growth in computational power and intelligence, surpasses human capabilities and leads to a transformative cascade of change.

Coined by mathematician John von Neumann and popularized by futurist Ray Kurzweil, the singularity signifies a critical moment in human history—one where the trajectory of civilization takes an unpredictable turn and the boundaries between humans and machines blur. Kurzweil argued that technological progress follows an exponential trajectory and predicted that the singularity would occur around the year 2045, leading to a merging of human and machine intelligence and unprecedented levels of innovation.

What can a picture from space tell you? “You’re likely to have a drought here that might lead to civil unrest.”

It reads. It talks. It collates mountains of data and recommends business decisions. Today’s artificial intelligence might seem more human than ever. However, AI still has several critical shortcomings.

A new Citi report says finance will be “at the forefront” of changes due to artificial intelligence.

In a much-anticipated debate, prominent aging researchers Aubrey de Grey and Peter Fedichev presented their competing, but also overlapping, theories.

When the non-profits Foresight Institute, Open Longevity, and Say Forever had the idea to hold debates on the best strategy to defeat aging, there was little question about whom they should invite first. Aubrey de Grey, head of LEV Foundation and one of the faces of the longevity field, and Peter Fedichev, CEO of Gero and a rising star in the same field, already had an impromptu debate last year in Zuzalu, the longevity/crypto/AI-themed pop-up city in Montenegro. I had the honor to witness that clash of titans, which kept a small but dedicated crowd on its toes for more than two hours.

The impromptu debate in Zuzalu. Photo: Arkadi Mazin.