Toggle light / dark theme

How A.I. is searching for Aliens | The Age of A.I.

We have always wondered whether other intelligent life exists in this galaxy, but for the first time we have the technology to help answer that question. With artificial intelligence, researchers have renewed the hunt for alien life in space and also begun to wonder if an entirely new life form has been born on earth.

The Age of A.I. is a 8 part documentary series hosted by Robert Downey Jr. covering the ways Artificial Intelligence, Machine Learning and Neural Networks will change the world.

0:00 Looking For Alien Life.
4:23 SETI
10:52 Time Traveling.
15:25 Inner Life.
21:21 A-I-A-I-O
25:13 Ethical Challenges.
27:52 Alien Pulses.
32:12 What’s Next

The Age of A.I. | Official Trailer

We are at the dawn of a new age and the implications of AI technology for humans are almost unimaginable. Welcome to The Age of AI.

Robert Downey Jr. hosts a brand new YouTube Originals series — The Age of AI. Discover the most innovative and leading technologies that will change the world forever.

Technology is moving faster than ever, and it’s taking less time to be widely adopted. Join host Rober Downey Jr. to explore the depths of this fascinating, gripping technology.

Smart microrobots learn how to swim and navigate with artificial intelligence

Researchers from Santa Clara University, New Jersey Institute of Technology and the University of Hong Kong have been able to successfully teach microrobots how to swim via deep reinforcement learning, marking a substantial leap in the progression of microswimming capability.

There has been tremendous interest in developing artificial microswimmers that can navigate the world similarly to naturally-occuring swimming microorganisms, like bacteria. Such microswimmers provide promise for a vast array of future biomedical applications, such as targeted drug delivery and microsurgery. Yet, most artificial microswimmers to date can only perform relatively simple maneuvers with fixed locomotory gaits.

The artificial intelligence-powered swimmer switches between different modes of locomotory gaits (color-coded) autonomously in tracing a complex trajectory ‘SWIM’. (Image: Commun. Phys., 5,158 (2022))

Artificial intelligence discovers new physics variables!

Analysing pendulum videos, the artificial intelligence tool identified variables not present in current mathematics.


An artificial intelligence tool has examined physical systems and not surprisingly, found new ways of describing what it found.

How do we make sense of the universe? There’s no manual. There’s no prescription.

At its most basic, physics helps us understand the relationships between “observable” variables – these are things we can measure. Velocity, energy, mass, position, angles, temperature, charge. Some variables like acceleration can be reduced to more fundamental variables. These are all variables in physics which shape our understanding of the world.

Tesla teases Optimus humanoid robot prototype with new image

Tesla has teased its Optimus humanoid robot prototype with a new image ahead of a full unveiling planned for September 30th.

Earlier this year, CEO Elon Musk announced “Tesla AI Day #2” with “many cool updates” on August 19.

The original “Tesla AI Day” held last year was an event focused on the company’s self-driving program. The automaker also unveiled its Dojo supercomputer and announced plans for the “Tesla Bot” humanoid robot – now known as Tesla Optimus.

Futureseek Daily Link Review; 05 August 2022

* At Long Last, Mathematical Proof That Black Holes Are Stable * Who Gets to Work in the Digital Economy? * Mice produce rat sperm with technique that could help conservation.

* Quantum computer can simulate infinitely many chaotic particles * Radar / AI & ML: Scaling False Peaks * Cyber security for the human world | George Loukas | TEDx.

* Can Airbnb Outperform a Potential Recession? | WSJ * San Diego joins other cities in restricting cops’ use of surveillance technology * Blue Origin launches crew of 6 to suborbital space, nails landings.

A highly efficient colloidal quantum dot imager that operates at near-infrared wavelengths

Advances in the fields of robotics, autonomous driving and computer vision have increased the need for highly performing sensors that can reliably collect data in different environmental conditions. This includes imagers that can operate at near-infrared wavelengths (i.e., 0.7–1.4 µm), thus potentially collecting high resolution images in complex or unfavorable atmospheric conditions, such as in the presence of rain, fog and smoke.

Researchers at Huazhong University of Science and Technology (HUST), HiSilicon Optoelectronics Co. Limited, and Optical Valley Laboratory have recently developed a near-infrared colloidal quantum dot (CQD) imager. This highly efficient imager was presented in a paper published in Nature Electronics.

“Our group was founded at Wuhan National Laboratory for Optoelectronics, HUST in 2012 and continuously conducts research on CQD materials and devices with Associate Prof. Jianbing Zhang,” Liang Gao, one of the researchers involved in the study, told TechXplore.

Google is here to Counter Code Complexities through ML-enhanced Completion

Google has described how the researchers have combined machine learning and semantic engines to develop a novel Transformer-based hybrid semantic ML code completion. The increasing complexity of code poses a key challenge to productivity in software engineering. Code completion has been an essential tool that has helped mitigate this complexity in integrated development environments. Intelligent code completion is a context-aware code completion feature in some programming environments that speeds up the process of coding applications by reducing typos and other common mistakes.

Google AI’s latest research explains how they combined machine learning and semantic engine SE to develop a novel transformer-based hybrid semantic ML code completion. A revolutionary Transformer-based hybrid semantic code completion model that is now available to internal Google engineers was created by Google AI researchers by combining ML with SE. The researchers’ method for integrating ML with SEs is defined as re-ranking SE single token proposals with ML, applying single and multi-line completions with ML, and then validating the results with the SE.

A common approach to code completion is to train transformer models, which use a self-attention mechanism for language understanding, to enable code understanding and completion predictions. Additionally, google suggested employing ML of single token semantic suggestions for single and multi-line continuation. Over three months, more than 10,000 Google employees tested the model in eight programming languages.

Alzheimer’s-Diagnosing AI Better Than Medical Experts? New Study Shows It Can Solve Physician Shortage

They claimed that artificial intelligence can actually solve some of the hardest challenges that affect the delivery of dementia treatment to old people, especially those with Alzheimer’s disease.

In 2021, the National Library of Medicine revealed that more than 6.2 million U.S. residents are suffering from Alzheimer’s.