Lifeboat Foundation

In 1965, American engineer Gordon Moore made the prediction that the number of transistors integrated on a silicon chip doubles every two years or so. This has proven to be true to this day, allowing software developers to double the performance of their applications. However, the performance of artificial intelligence (AI) algorithms seems to have outpaced Moore’s Law.

According to a new report produced by Stanford University, AI computational power is accelerating at a much higher rate than the development of processor chips.

“Prior to 2012, AI results closely tracked Moore’s Law, with compute doubling every two years,” the authors of the report wrote. “Post-2012, compute has been doubling every 3.4 months.”

About AI bias.

Yet AI bias is by itself a biased term, as if the machine/algorithm were to blame for human bias and/or an incorrect data set.

Decision-making algorithms transform how automated systems evaluate and synthesize novel compounds.

On Dec. 11, 2019, a general framework for incorporating and correcting for nonclassical electromagnetic phenomena in nanoscale systems will be presented in the journal Nature.

More than 150 years have passed since the publication of James Clerk Maxwell’s “A Dynamical Theory of the Electromagnetic Field” (1865). His treatise revolutionized the fundamental understanding of electric fields, magnetic fields and light. The 20 original equations (elegantly reduced to four today), their boundary conditions at interfaces, and the bulk electronic response functions (dielectric permitivity and magnetic permeability) are at the root of the ability to manipulate electromagnetic fields and light.

Life without Maxwell’s equations would lack most current science, communications and technology.

Treating prostate cancer through traditional means such as surgery or radiotherapy carries certain risks, with some patients experiencing impotence, urinary problems and bowel trouble, among other unwanted side effects. Safer and less invasive treatment options could soon be on the table, however, including a novel MRI-guided ultrasound technique that eliminated significant cancers in 80 percent of subjects in a year-long study.

The new technique is called MRI-guided transurethral ultrasound ablation (TULSA) and has been under development for a number of years. The minimally invasive technology involves a rod that enters the prostate gland via the urethra and emits highly controlled sound waves in order to heat and destroy diseased tissue, while leaving healthy tissue unharmed.

Continue reading “Ultrasound destroys 80 percent of prostate cancers in one-year study” »

Quadratic equations are polynomials, meaning strings of math terms. An expression like “x + 4” is a polynomial. They can have one or many variables in any combination, and the magnitude of them is decided by what power the variables are taken to. So x + 4 is an expression describing a straight line, but (x + 4)² is a curve. Since a line crosses just once through any particular latitude or longitude, its solution is just one value. If you have x², that means two root values, in a shape like a circle or arc that makes two crossings.

Larry Page and Sergey Brin founded Google in 1996 on the back of an algorithm, turned it into one of the most valuable companies in the world, and have now given up their leadership roles three times — even though they’ve always retained a controlling interest in the company behind the scenes. Here’s a timeline of their most important moments in Google and Alphabet history.

Physicists find hints that entanglement explains Einstein’s equations for gravity.

Determining the quantum mechanical behavior of many interacting particles is essential to solving important problems in a variety of scientific fields, including physics, chemistry and mathematics. For instance, in order to describe the electronic structure of materials and molecules, researchers first need to find the ground, excited and thermal states of the Born-Oppenheimer Hamiltonian approximation. In quantum chemistry, the Born-Oppenheimer approximation is the assumption that electronic and nuclear motions in molecules can be separated.

A variety of other scientific problems also require the accurate computation of Hamiltonian ground, excited and thermal states on a quantum computer. An important example are combinatorial optimization problems, which can be reduced to finding the ground state of suitable spin systems.

So far, techniques for computing Hamiltonian eigenstates on quantum computers have been primarily based on phase estimation or variational algorithms, which are designed to approximate the lowest energy eigenstate (i.e., ground state) and a number of excited states. Unfortunately, these techniques can have significant disadvantages, which make them impracticable for solving many scientific problems.