Lifeboat Foundation

Computer vision is one of the most popular applications of artificial intelligence. Image classification, object detection and object segmentation are some of the use cases of computer vision-based AI. These techniques are used in a variety of consumer and industrial scenarios. From face recognition-based user authentication to inventory tracking in warehouses to vehicle detection on roads, computer vision is becoming an integral part of next-generation applications.

Computer vision uses advanced neural networks and deep learning algorithms such as Convolutional Neural Networks (CNN), Single Shot Multibox Detector (SSD) and Generative Adversarial Networks (GAN). Applying these algorithms requires a thorough understanding of neural network architecture, advanced mathematics and image processing techniques. For an average ML developer, CNN remains to be a complex branch of AI.

Apart from the knowledge and understanding of algorithms, CNNs demand high end, expensive infrastructure for training the models, which is out of reach for most of the developers.

Researchers have designed a machine learning algorithm that predicts the outcome of chemical reactions with much higher accuracy than trained chemists and suggests ways to make complex molecules, removing a significant hurdle in drug discovery.

University of Cambridge researchers have shown that an algorithm can predict the outcomes of complex chemical reactions with over 90% accuracy, outperforming trained chemists. The algorithm also shows chemists how to make target compounds, providing the chemical “map” to the desired destination. The results are reported in two studies in the journals ACS Central Science and Chemical Communications.

A central challenge in drug discovery and materials science is finding ways to make complicated organic molecules by chemically joining together simpler building blocks. The problem is that those building blocks often react in unexpected ways.

Researchers from SLAC and around the world increasingly use machine learning to handle Big Data produced in modern experiments and to study some of the most fundamental properties of the universe (Symmetry magazine).

O.o.

Hot on the heels of the ground-breaking ‘Sum-Of-Three-Cubes’ solution for the number 33, a team led by the University of Bristol and Massachusetts Institute of Technology (MIT) has solved the final piece of the famous 65-year-old maths puzzle with an answer for the most elusive number of all—42.

Continue reading “Sum of three cubes for 42 finally solved—using real life planetary computer” »

When practical quantum computing finally arrives, it will have the power to crack the standard digital codes that safeguard online privacy and security for governments, corporations, and virtually everyone who uses the Internet. That’s why a U.S. government agency has challenged researchers to develop a new generation of quantum-resistant cryptographic algorithms.

Many experts don ’t expect a quantum computer capable of performing the complex calculations required to crack modern cryptography standards to become a reality within the next 10 years. But the U.S. National Institute of Standards and Technology (NIST) wants to stay ahead by getting new cryptographic standards ready by 2022. The agency is overseeing the second phase of its Post-Quantum Cryptography Standardization Process to narrow down the best candidates for quantum-resistant algorithms that can replace modern cryptography.

“Currently intractable computational problems that protect widely-deployed cryptosystems, such as RSA and Elliptic Curve-based schemes, are expected to become solvable,” says Rafael Misoczki, a cryptographer at the Intel Corporation and a member of two teams (named Bike and Classic McEliece) involved in the NIST process. “This means that quantum computers have the potential to eventually break most secure communications on the planet.”

❤👍👍👍

Greetings with some good news for the women’s world. Just recently, one of the most prestigious mathematics prizes in the world – The Abel Prize was awarded to a woman for the first time ever. Yes! Karen Uhlenbeck is a mathematician and a professor at the University of Texas and is now the first woman to win this prize in mathematics. You go Karen!

The award, which is modeled by the Nobel Prize, is awarded by the king of Norway to honor mathematicians who have made an influence in their field including a cash prize of around $700,000. The award to Karen cites for “the fundamental impact of her work on analysis, geometry and mathematical physics.” This award exists since 2003 but has only been won by men since.

Continue reading “The ‘Nobel Prize of Math’ Has Been Won By A Woman For The First Time Ever” »

Rumour has it that Albert Einstein spent his last few hours on Earth scribbling something on a piece of paper in a last attempt to formulate a theory of everything. Some 60 years later, another legendary figure in theoretical physics, Stephen Hawking, may have passed away with similar thoughts. We know Hawking thought something called “M-theory” is our best bet for a complete theory of the universe. But what is it?

Since the formulation of Einstein’s theory of general relativity in 1915, every theoretical physicist has been dreaming of reconciling our understanding of the infinitely small world of atoms and particles with that of the infinitely large scale of the cosmos. While the latter is effectively described by Einstein’s equations, the former is predicted with extraordinary accuracy by the so-called Standard Model of fundamental interactions.

Our current understanding is that the interaction between physical objects is described by four fundamental forces. Two of them – gravity and electromagnetism – are relevant for us on a macroscopic level, we deal with them in our everyday life. The other two, dubbed strong and weak interactions, act on a very small scale and become relevant only when dealing with subatomic processes.

20th century physics has seen two major paradigm shifts in the way we understand Mother Nature. One is quantum mechanics, and the other is relativity. The marriage between the two, called quantum field theory, conceived an enfant terrible, namely anti-matter. As a result, the number of elementary particles doubled. We believe that 21st century physics is aimed at yet another level of marriage, this time between quantum mechanics and general relativity, Einstein’s theory of gravity. The couple has not been getting along very well, resulting in mathematical inconsistencies, meaningless infinities, and negative probabilities. The key to success may be in supersymmetry, which doubles the number of particles once more.

Why was anti-matter needed? One reason was to solve a crisis in the 19th century physics of classical electromagnetism. An electron is, to the best of our knowledge, a point particle. Namely, it has no size, yet an electric charge. A charged particle inevitably produces an electric potential around it, and it also feels the potential created by itself. This leads to an infinite “self-energy” of the electron. In other words, it takes substantial energy to “pack” all the charge of an electron into small size.

On the other hand, Einstein’s famous equation says that mass of a particle determines the energy of the particle at rest. For an electron, its rest energy is known to be 0.511 MeV. For this given amount of energy, it cannot afford to “pack” itself into a size smaller than the size of a nucleus. Classical theory of electromagnetism is not a consistent theory below this distance. However, it is known that the electron is at least ten thousand times smaller than that.

This week a collaborative effort among computer scientists and academics to safeguard data is winning attention and it has quantum computing written all over it.

The Netherlands’ Centrum Wiskunde & Informatica (CWI), national research institute for mathematics and computer science, had the story: IBM Research developed “quantum-safe algorithms” for securing data. They have done so by working with international partners including CWI and Radboud University in the Netherlands.

IBM and partners share concerns that data protected by current encryption methods may become insecure within the next 10 to 30 years.