Lifeboat Foundation

Superconducting materials are characterized by the fact that they lose their electrical resistance below a certain temperature, the so-called transition temperature. In principle, they would be ideal for transporting electrical energy over very long distances from the electricity producer to the consumer.

Numerous energy challenges would be solved in one fell swoop: For example, the electricity generated by wind turbines on the coast could be channeled inland without losses. However, this would only be possible if materials were available that have superconducting properties at normal room and ambient temperatures.

In 2019, an unusually high transition temperature of minus 23 degrees Celsius was measured in experiments coordinated by the Max Planck Institute in Mainz. The measurement took place at a compression pressure of 170 gigapascals—1.7 million times higher than the pressure of the Earth’s atmosphere. The material was a lanthanum hydride (LaH_10+δ), a compound of atoms of the metal lanthanum with hydrogen atoms. The report on these experiments and other similar reports remain highly controversial. They have internationally aroused great interest in research on lanthanum hydrides with different compositions and structures.

A new study has revealed how the glass-like shells of diatoms help these microscopic organisms perform photosynthesis in dim conditions. A better understanding of how these phytoplankton harvest and interact with light could lead to improved solar cells, sensing devices and optical components.

“The computational model and toolkit we developed could pave the way toward mass-manufacturable, sustainable optical devices and more efficient light harvesting tools that are based on diatom shells,” said research team member Santiago Bernal from McGill University in Canada. “This could be used for biomimetic devices for sensing, new telecommunications technologies or affordable ways to make clean energy.”

Continue reading “Glass-like shells of diatoms help turn light into energy in dim conditions” »

The fine structure constant is one of the most important natural constants of all. At TU Wien, a remarkable way of measuring it has been found—it shows up as a rotation angle.

One over 137: This is one of the most important numbers in physics. It is the approximate value of the so-called fine structure constant—a physical quantity that is of outstanding importance in atomic and particle physics.

There are many ways to measure the fine structure constant—usually it is measured indirectly, by measuring other physical quantities and using them to calculate the fine structure constant. At TU Wien, however, an experiment has now been performed, in which the fine structure constant itself can be directly measured—as an angle.

‘Friendly consultation’

Marcos wants note verbale sent.

A multi-institution research team has developed an optical chip that can train machine learning hardware. Their research is published today in Optica.

Machine learning applications have skyrocketed to $165 billion annually, according to a recent report from McKinsey. But before a machine can perform intelligence tasks such as recognizing the details of an image, it must be trained. Training of modern-day artificial intelligence (AI) systems like Tesla’s autopilot costs several million dollars in electric power consumption and requires supercomputer-like infrastructure.

This surging AI “appetite” leaves an ever-widening gap between computer hardware and demand for AI. Photonic integrated circuits, or simply optical chips, have emerged as a possible solution to deliver higher computing performance, as measured by the number of operations performed per second per watt used, or TOPS/W. However, though they’ve demonstrated improved core operations in machine intelligence used for data classification, photonic chips have yet to improve the actual front-end learning and machine training process.

Anguera, J.A., Volponi, J.J., Simon, A.J. et al. Integrated cognitive and physical fitness training enhances attention abilities in older adults. npj Aging 8, 12 (2022). https://doi.org/10.1038/s41514-022-00093-y.

Download citation.

Alphabet’s X unit spun up a tool that teaches code to write itself. It has been moved into Google Labs, signaling its growing importance.

https://www.youtube.com/watch?v=QrXnYHubFPc

Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED
AI News Timestamps:
0:00 New AI Robot Dog Beats Human Soccer Skills.
2:34 Breakthrough Humanoid Robotics & AI Tech.
5:21 Google AI Makes HD Video From Text.
8:41 New OpenAI DALL-E Robotics.
11:31 Elon Musk Reveals Tesla Optimus AI Robot.
16:49 Machine Learning Driven Exoskeleton.
19:33 Google AI Makes Video Game Objects From Text.
22:12 Breakthrough Tesla AI Supercomputer.
25:32 Underwater Drone Humanoid Robot.
29:19 Breakthrough Google AI Edits Images With Text.
31:43 New Deep Learning Tech With Light waves.
34:50 Nvidia General Robot Manipulation AI
36:31 Quantum Computer Breakthrough.
38:00 In-Vitro Neural Network Plays Video Games.
39:56 Google DeepMind AI Discovers New Matrices Algorithms.
45:07 New Meta Text To Video AI
48:00 Bionic Tech Feels In Virtual Reality.
53:06 Quantum Physics AI
56:40 Soft Robotics Gripper Learns.
58:13 New Google NLP Powered Robotics.
59:48 Ionic Chips For AI Neural Networks.
1:02:43 Machine Learning Interprets Brain Waves & Reads Mind.

WASP-39b could be key to finding much calmer, more habitable worlds.