Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: mathematics – Page 153

The goal of roboticists has long been to make A.I. as efficient as the human brain, and researchers at the Massachusetts Institute of Technology just brought them one step closer.

In a recent paper, published in the journal Biology, scientists were able to successfully train a neural network to recognize faces at different angles by feeding it a set of different orientations for several face templates. Although this only initially gave the neural network the ability to roughly reach invariance — the ability to process data regardless of form — over time, the network taught itself to achieve full “mirror symmetry. Through mathematical algorithms, the neural network was able to mimic the human brain’s ability to understand objects are the same despite orientation or rotation.

The brain requires three different layers to process image orientation.

Read more

What if a simple algorithm were all it took to program tomorrow’s artificial intelligence to think like humans?

According to a paper published in the journal Frontiers in Systems Neuroscience, it may be that easy — or difficult. Are you a glass-half-full or half-empty kind of person?

Researchers behind the theory presented experimental evidence for the Theory of Connectivity — the theory that all of the brains processes are interconnected (massive oversimplification alert) — “that a simple mathematical logic underlies brain computation.” Simply put, an algorithm could map how the brain processes information. The painfully-long research paper describes groups of similar neurons forming multiple attachments meant to handle basic ideas or information. These groupings form what researchers call “functional connectivity motifs” (FCM), which are responsible for every possible combination of ideas.

Read more


Image copyright of Augusta University

Our brains have a basic algorithm that enables us to not just recognize a traditional Thanksgiving meal, but the intelligence to ponder the broader implications of a bountiful harvest as well as good family and friends.

“A relatively simple mathematical logic underlies our complex brain computations,” said Dr. Joe Z. Tsien, neuroscientist at the Medical College of Georgia at Augusta University, co-director of the Augusta University Brain and Behavior Discovery Institute and Georgia Research Alliance Eminent Scholar in Cognitive and Systems Neurobiology.

Read more

Once synbio computing is fully matured then our tech dev work maybe done.

By Frances Van Scoy, West Virginia University.

The first computers cost millions of dollars and were locked inside rooms equipped with special electrical circuits and air conditioning. The only people who could use them had been trained to write programs in that specific computer’s language. Today, gesture-based interactions, using multitouch pads and touchscreens, and exploration of virtual 3D spaces allow us to interact with digital devices in ways very similar to how we interact with physical objects.

Continue reading “Moving toward computing at the speed of thought” | >

Sapp Center for Science Teaching and Learning, Old Chemistry Building

““The School of Humanities and Sciences is systematically re-thinking how we teach entry-level courses in the sciences,” said Richard P. Saller, dean of the School of Humanities and Sciences, during opening remarks for the event. “Half of all freshman enrollments in Stanford are in beginning-level sciences and math. We have tremendous impact by raising the level of teaching in these areas.””

Read more

Optalysys’s technology performs a mathematical function called the Fourier transform by encoding data, say a genome sequence, into a laser beam. The data can be manipulated by making light waves in the beam interfere with one another, performing the calculation by exploiting the physics of light, and generating a pattern that encodes the result. The pattern is read by a camera sensor and fed back into a conventional computer’s electronic circuits. The optical approach is faster because it achieves in a single step what would take many operations of an electronic computer.

The technology was enabled by the consumer electronics industry driving down the cost of components called spatial light modulators, which are used to control light inside projectors. The company plans to release its first product next year, aimed at high-performance computers used for processing genomic data. It will take the form of a PCI express card, a standard component used to upgrade PCs or servers usually used for graphics processors. Optalysys is also working on a Pentagon research project investigating technologies that might shrink supercomputers to desktop size, and a European project on improving weather simulations.

In 2015, Optalysis built a prototype that achieves a processing speed equivalent to 320 Gflops and it is incredibly energy efficient as it uses low-powered, cost effective components.

Read more

Quantum theory is strange and counterintuitive, but it’s very precise. Lots of analogies and broad concepts are presented in popular science trying to give an accurate description of quantum behavior, but if you really want to understand how quantum theory (or any other theory) works, you need to look at the mathematical details. It’s only the mathematics that shows us what’s truly going on.

Mathematically, a quantum object is described by a function of complex numbers governed by the Schrödinger equation. This function is known as the wavefunction, and it allows you to determine quantum behavior. The wavefunction represents the state of the system, which tells you the probability of various outcomes to a particular experiment (observation). To find the probability, you simply multiply the wavefunction by its complex conjugate. This is how quantum objects can have wavelike properties (the wavefunction) and particle properties (the probable outcome).

No, wait. Actually a quantum object is described by a mathematical quantity known as a matrix. As Werner Heisenberg showed, each type of quantity you could observe (position, momentum, energy) is represented by a matrix as well (known as an operator). By multiplying the operator and the quantum state matrix in a particular way, you get the probability of a particular outcome. The wavelike behavior is a result of the multiple connections between states within the matrix.

Read more

SciWorks Radio is a production of 88.5 WFDD and SciWorks, the Science Center and Environmental Park of Forsyth County, located in Winston-Salem.

We’ve come a long way from stone tools. With great complexity, we manufacture things like jet airplanes, interplanetary probes, medical tools, and microprocessors. We build with a top-down approach, starting with a big picture concept which we then design and assemble in pieces.

Duke University professor of computer sciences, Dr. John Reif, notes that nature works from the bottom up to assemble complex structures in three dimensions.

Read more

According to our best understanding of the Universe, if you travel back in time as far as you can, around 13.8 billion years or so, you’ll eventually reach a singularity — a super-dense, hot, and energetic point, where the laws that govern space-time breakdown.

Despite our best attempts, we can’t peer past that singularity to see what triggered the birth of our Universe — but we do know of only one other instance in the history of our Universe where a singularity exists, and that’s inside a black hole. And the two events might have more in common than you’ve ever considered, as physicist Ethan Siegel explains over at Forbes.

It might sound a little crazy, but, as Siegel reports, from a mathematical perspective, at least, there’s no reason that our own Big Bang couldn’t have been the result of a star collapsing into a black hole in an alternate, four-dimensional universe.

Read more