Archive for the ‘Mathematics’ Category

Seth Llyod is a Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology MIT. His talk, “Programming the Universe”, is about the computational power of atoms, electrons, and elementary particles.

A highly recommended watch.

A musical investigation into the nature of atoms and subatomic particles, the jiggly things that make up everything we see. Featuring Morgan Freeman, Stephen Hawking, Michio Kaku, Brian Cox, Richard Feynman, and Frank Close.

“The Quantum World” is the eleventh installment in the ongoing Symphony of Science music video series. Materials used in the creation of this video are from: for downloads & more videos!

Richard Feynman – Fun to Imagine

BBC Visions of the Future – the Quantum Revolution

Through the Wormhole with Morgan Freeman

Into the Universe with Stephen Hawking

Brian Cox TED Talk

BBC What Time is it

BBC Wonders of the Universe

BBC Horizon – What Is Reality

via Symphony of Science – the Quantum World! – YouTube.

Hannah Fry trained as a mathematician, and completed her PhD in fluid dynamics in early 2011. After a brief period working as an aerodynamicist in the motorsport industry, she came back to UCL to work on a major interdisciplinary project in complexity science. The project spans several departments, including Mathematics and the Centre for Advanced Spatial Analysis, and focuses on understanding global social systems — such as Trade, Migration and Security. Hannah’s research interests revolve around creating new mathematical techniques to study these systems, with recent work including studies of the London Riots and Consumer Behaviour.

Talk: Is life really that complex?
Recently scientists have begun to appreciate that many of the mechanisms inherent in our social systems have analogies in seemingly unrelated problems. The movement of a crowd, for instance, can be understood using techniques traditionally applied to the flow of a fluid, and the uptake of a new technology can be predicted using knowledge of how disease spreads.
By exploiting these analogies, a new field is emerging at the interface between social sciences and mathematics, the potential of which I hope to illustrate using a mathematical model of the London Riots. Our approach can demonstrate why certain areas of the city were at higher risk than others and help determine which policing strategies may have resulted in a swifter resolution to the unrest.
We will discuss how social modelling can provide a greater understanding of our society, and help design better systems for all: from healthcare to policing and policy.

An intriguing combination of programmers, artists, and philosophers, these creators embrace a process that delegates essential decisions to computers, data sets, or even random variables. This allows important metaphors to arise in their work, calling attention to the relationship between humans and the computers that surround us, the mountains of information we generate, and the powerful impact that technology has on our relationships with each other.


Luke Dubois, Generative Composer
Scott Draves, Generative Artist
Will Wright, Game Designer

Music by:

Codex Machine,
Luke Dubois,
Revolution Void,
Reno Project,

Marvin Minsky is worried that after making great strides in its infancy, AI has lost its way, getting bogged down in different theories of machine learning. Researchers “have tried to invent single techniques that could deal with all problems, but each method works only in certain domains.” Minsky believes we’re facing an AI emergency, since soon there won’t be enough human workers to perform the necessary tasks for our rapidly aging population.

So while we have a computer program that can beat a world chess champion, we don’t have one that can reach for an umbrella on a rainy day, or put a pillow in a pillow case. For “a machine to have common sense, it must know 50 million such things,” and like a human, activate different kinds of expertise in different realms of thought, says Minsky.

Minsky suggests that such a machine should, like humans, have a very high-level, rule-based system for recognizing certain kinds of problems. He labels these parts of the brain “critics.” When one critic gets selected in a particular situation, the others get turned off. In the “cloud of resources” that comprises our mind, mental states, from emotions to reasoning, result from activating or suppressing the right resource. Minsky further refines his machine’s reasoning architecture with six levels of thinking that attempt to emulate the different kinds of reasoning humans may engage in, often simultaneously: These include learned reactions, deliberative thinking, and reflective thinking, among others. A smart machine must have at least these levels, he says, because psychology, unlike physics, doesn’t lend itself to a minimal number of laws. With at least 400 different areas of the brain operating, “if a theory tries to explain everything by just 20 principles, it’s doing something wrong.”

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read all at MIT world

A must watch: Kevin Slavin argues that we’re living in a world designed for — and increasingly controlled by — algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can’t understand, with implications we can’t control.

This is an extremely interesting video talk by Geoffrey West, a physicist former president of SantaFe Institute. It is by all means a must watch piece on the frontiers of the science of complexity.

Regretfully will not allow to embed their videos so here is the link:

An excerpt from the conversation:

The great thing about cities, the thing that is amazing about cities is as they grow, so to speak, their dimensionality increases. That is, the space of opportunity, the space of functions, the space of jobs just continually increases. And the data shows that. If you look at job categories, it continually increases. I’ll use the word “dimensionality.”  It opens up. And in fact, one of the great things about cities is that it supports crazy people. You walk down Fifth Avenue, you see crazy people. There are always crazy people. Well, that’s good. Cities are tolerant of extraordinary diversity. …

This is in complete contrast to companies. The Google boys in the back garage so to speak with ideas of the search engine, were no doubt promoting all kinds of crazy ideas and maybe having even crazy people around them.

Well, Google is a bit of an exception, because it still tolerates some of that. But most companies start out probably with some of that buzz. But the data indicates that at about 50 employees to a hundred that buzz starts to stop. A company that was more multi dimensional, more evolved, becomes uni dimensional. It closes down.

Indeed, if you go to General Motors or you go to American Airlines or you go to Goldman Sachs, you don’t see crazy people. Crazy people are fired. Well, to speak of crazy people, is taking the extreme. But maverick people are often fired.

It’s not surprising to learn that when manufacturing companies are on a down turn, they decrease research and development, and in fact in some cases, do actually get rid of it, thinking this is “oh, we can get that back in two years we’ll be back on track.”

Well, this kind of thinking kills them. This is part of the killing, and this is part of the change from superlinear to sublinear, namely companies allow themselves to be dominated by bureaucracy and administration over creativity and innovation, and unfortunately, it’s necessary. You cannot run a company without administrative. Someone has got to take care of the taxes and the bills and the cleaning the floors and the maintenance of the building and all the rest of that stuff. You need it. And the question is, “can you do it without it dominating the company?” The data suggests that you can’t.