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The University of Innsbruck, Austria, realized a quantum computer that breaks out of this paradigm and unlocks additional computational resources, hidden in almost all of today’s quantum devices. Computers are well-known for operating with binary information, or zeros and ones, which has led to computers powering so much. This new approach results in more computational power with fewer quantum particles.

Quantum computers work with more than zero and one and digital computers work with zeros and ones, also called binary information. Quantum computers are also designed with binary information processing in mind. In fact, it was so successful that computers now power everything from coffee makers to self-driving cars, and it’s hard to imagine life without them. Restricting researchers to binary systems prevent these devices from living up to their true potential.

Continue reading “Quantum Computers can Look Beyond Zeros and Ones! Research Reveals” »

Constructing a tiny robot from DNA and using it to study cell processes invisible to the naked eye… You would be forgiven for thinking it is science fiction, but it is in fact the subject of serious research by scientists from Inserm, CNRS and Université de Montpellier at the Structural Biology Center in Montpellier. This highly innovative “nano-robot” should enable closer study of the mechanical forces applied at microscopic levels, which are crucial for many biological and pathological processes. It is described in a new study published in Nature Communications.

Our cells are subject to mechanical forces exerted on a microscopic scale, triggering biological signals essential to many cell processes involved in the normal functioning of our body or in the development of diseases.

For example, the feeling of touch is partly conditional on the application of mechanical forces on specific cell receptors (the discovery of which was this year rewarded by the Nobel Prize in Physiology or Medicine). In addition to touch, these receptors that are sensitive to mechanical forces (known as mechanoreceptors) enable the regulation of other key biological processes such as blood vessel constriction, pain perception, breathing or even the detection of sound waves in the ear, etc.

Physicists are (temporarily) augmenting reality to crack the code of quantum systems.

Predicting the properties of a molecule or material requires calculating the collective behavior of its electrons. Such predictions could one day help researchers develop new pharmaceuticals or design materials with sought-after properties such as superconductivity. The problem is that electrons can become “quantum mechanically” entangled with one another, meaning they can no longer be treated individually. The entangled web of connections becomes absurdly tricky for even the most powerful computers to unravel directly for any system with more than a handful of particles.

Now, quantum physicists at the Flatiron Institute’s Center for Computational Quantum Physics (CCQ) in New York City and the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland have sidestepped the problem. They created a way to simulate entanglement by adding to their computations extra “ghost” electrons that interact with the system’s actual electrons.

Recently, Blake Lemoine a computer scientist and machine learning bias researcher for Google released an interview with Google’s LaMDA a conversation technology and AI. Blake proposes, based on his time testing LaMDA, that it is a super intelligence and sentient. Blake details just what made him come to this conclusion and why he believes we have passed the singularity, last year.

Blake’s links:
https://twitter.com/cajundiscordian.
https://cajundiscordian.medium.com/is-lamda-sentient-an-interview-ea64d916d917

Continue reading “Is Artificial Sentience Here? with Blake Lemoine” »

Social robots, robots that can interact with humans and assist them in their daily lives, are gradually being introduced in numerous real-world settings. These robots could be particularly valuable for helping older adults to complete everyday tasks more autonomously, thus potentially enhancing their independence and well-being.

Researchers at University of Bari have been investigating the potential using social robots for ambient assisted living applications for numerous years. Their most recent paper, published in UMAP’22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, specifically explores the value of allowing social robots who are assisting seniors to learn the relationships between a user’s routines and his/her mood.

“Social robots should support older adults with daily activity and, at the same time, they should contribute to emotional wellness by considering affective factors in everyday situations,” Berardina De Carolis, Stefano Ferilli and Nicola Macciarulo wrote in their paper. “The main goal of this research is to investigate whether it is possible to learn relations between the user’s affective state state and daily routines, made by activities, with the aid of a social robot, Pepper in this case.”

To efficiently navigate real-world environments, robots typically analyze images collected by imaging devices that are integrated within their body. To enhance the performance of robots, engineers have thus been trying to develop different types of highly performing cameras, sensors and artificial vision systems.

Many artificial vision systems developed so far draw inspiration from the eyes of humans, animals, insects and fish. These systems have different features and characteristics, depending on the environment in which they are designed to operate in.

Most existing sensors and cameras are designed to work either in on the ground (i.e., in terrestrial environments) or in water (i.e., in aquatic environments). Bio-inspired artificial vision systems that can operate in both terrestrial and aquatic environments, on the other hand, remain scarce.

Its process is faster than the human brain, and it is ready for deep learning.

Researchers at Oxford University’s Department of Materials, working in collaboration with colleagues from Exeter and Munster, have developed an on-chip optical processor capable of detecting similarities in datasets up to 1,000 times faster than conventional machine learning algorithms running on electronic processors.

The new research published in Optica took its inspiration from Nobel Prize laureate Ivan Pavlov’s discovery of classical conditioning. In his experiments, Pavlov found that by providing another stimulus during feeding, such as the sound of a bell or metronome, his dogs began to link the two experiences and would salivate at the sound alone. The repeated associations of two unrelated events paired together could produce a learned response—a conditional reflex.

Co-first author Dr. James Tan You Sian, who did this work as part of his DPhil in the Department of Materials, University of Oxford, said, “Pavlovian associative learning is regarded as a basic form of learning that shapes the behavior of humans and animals—but adoption in AI systems is largely unheard of. Our research on Pavlovian learning in tandem with optical parallel processing demonstrates the exciting potential for a variety of AI tasks.”

India is a developing country where Robotics is still lagging because of the lack of availability of Robotics components, 3D printed parts and suitable quality motors. The science of Robotics requires a high-end technology to be implemented by researchers or Robotics scientists.

Despite all these, if a teacher (not a Robotics Scientist) can do something in the field and able to develop a prototype that is comparable with the Robots developed by big facilitated and resourceful companies with the help of their best engineers on a huge budget, then the person deserves the appreciation.

A computer science teacher in Kendriya Vidyalaya, IIT Bombay, Dinesh Kunwar Patel has developed the world’s first social and educational humanoid Robot ‘Shalu’ that can speak 47 languages, including 9 Indian and 38 foreign languages. The homemade Robot ‘Shalu’ is made of waste materials, including cardboard, wood, and aluminium.