Profile cover photo
Profile photo
Stephen Paul King
280 followers -
Insanely curious about my world.
Insanely curious about my world.

280 followers
About
Posts

Post has shared content
So, lock 'em up, zap their brains, take away their freedoms and dignity. Because "they don't fit in, they don't belong, they aren't like us, we don't get them."

Despite the fact, there's scant evidence any of that accomplishes a damn thing in the long run.

But then there's the almost apologetic admission that lithium is magick. (80% reduction long term.)

"Suicide rates average approximately 1% annually, or perhaps 60 times higher than the international population rate of 0.015% annually. Suicidal acts typically occur early in bipolar disorders and in association with severe depressive or mixed states. The high lethality of suicidal acts in bipolar disorders is suggested by a much lower ratio of attempts:suicide (approximately 3:1) than in the general population (approximately 30:1). Risk factors can help to identify patients at increased suicidal risk, but ongoing clinical assessment is essential to limit risk. Empirical short-term interventions to manage acute suicidal risk include close clinical supervision, rapid hospitalization, and electroconvulsive therapy. Remarkably, however, evidence of the long-term effectiveness of most treatments against suicidal behavior is rare. A notable exception is lithium prophylaxis, which is associated with consistent evidence of major (approximately 80%),"
Add a comment...

Post has shared content
Well said!
Garry Kasparov on the future and impact of Machine Learning...

"Romanticizing the loss of jobs to technology is little better than complaining that antibiotics put too many grave diggers out of work. The transfer of labor from humans to our inventions is nothing less than the history of civilization. It is inseparable from centuries of rising living standards and improvements in human rights."

"What a luxury to sit in a climate-controlled room with accesses to the sum of human knowledge on a device in your pocket and lament how we don't work with our hands anymore! There are still plenty of places in the world where people with with their hands all day, and also live without clean water and modern medicine. They are literally drying from a lack of technology."

"Machines that replace physical labor have allowed us to focus more on what makes us human: our minds. Intelligent machines will continue that process, taking over the more menial aspects of cognition and elevating our mental lives toward creativity, curiosity, beauty, and joy."

"These are what truly make us human, not any particular activity or skill like swinging a hammer - or even playing chess."

Some Context

Garry Kasparov held the title of Chess World Champion longer than anyone in history. He is among a handful of players often considered to be the greatest human chess player who ever lived.

However, Garry has one other distinction that sets him apart: He was the first World Champion to be defeated by a computer. Thus he has a special relationship with intelligent machines : )

The quote is from Garry's book: Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins.



(Artwork by: Vioxtar)
Photo
Add a comment...

Post has shared content
Complex math can be made so simple with the right point of view. Figure made for explanations of needs [1]. Wait and see, meanwhile enjoy the elegance of symmetry.

[1] https://github.com/chorasimilarity/needs
Photo
Add a comment...

Post has shared content
Tensor Networks in a Nutshell -- https://arxiv.org/abs/1708.00006

Together with +Ville Bergholm, we have produced what I hope will provide a good introduction to tensor networks. We had the idea years ago to present the topic largely through examples and to explain the details we had to sort of figure out on our own in our early exploration studying the topic. The paper will appear in Contemporary Physics and should be readable by graduate students. Feedback is encouraged.

abstract. Tensor network methods are taking a central role in modern quantum physics and beyond. They can provide an efficient approximation to certain classes of quantum states, and the associated graphical language makes it easy to describe and pictorially reason about quantum circuits, channels, protocols, open systems and more. Our goal is to explain tensor networks and some associated methods as quickly and as painlessly as possible. Beginning with the key definitions, the graphical tensor network language is presented through examples. We then provide an introduction to matrix product states. We conclude the tutorial with tensor contractions evaluating combinatorial counting problems. The first one counts the number of solutions for Boolean formulae, whereas the second is Penrose's tensor contraction algorithm, returning the number of 3-edge-colorings of 3-regular planar graphs.

#physics #quantumComputing #tensorNetworks

https://arxiv.org/abs/1708.00006
Photo
Add a comment...

Post has shared content
Category theory in chemistry

My working hypothesis is that living systems seem ‘messy’ to physicists because they operate at a higher level of abstraction than physicists are used to. That’s what I’m trying to explore these days.

Back in 1963, Bill Lawvere had the idea that the process of assigning ‘meaning’ to expressions could be seen as a functor from one category to another. This idea has caught on in theoretical computer science: it’s called functorial semantics.

The basic idea is that a program is a morphism in a category, and what it computes is a morphism in another category, and there's a functor from the first category to the second. Some programming languages like Haskell, Scheme and Scala have been designed to explicitly take advantage of this point of view.

What I want to to do is apply functorial semantics to biology. I expect that in biology there are many ways to view the 'meaning' of what's going on - there's no one best answer; instead, there are many different levels of abstraction at which we can usefully view things. Life somehow manages to exploit this.

This is hard to think about: biology is much more tricky than computer programming! So I've been starting with simpler things, like chemistry.

+Blake Pollard and I have been working on open reaction networks: that is, networks of chemical reactions where some chemicals can flow in from an outside source, or flow out. The picture to keep in mind is shown below.

The yellow circles are different kinds of chemicals. The aqua boxes are different reactions. The purple dots in the sets X and Y are ‘inputs’ and ‘outputs’, where certain kinds of chemicals can flow in or out.

There's no serious difference between 'inputs' and 'outputs': chemical can flow in or out at any of these points. The only reason for segregating inputs and outputs is to make it easy to stick together two open reaction networks: we attach the outputs of the first to the inputs of the second.

This makes open reaction networks into the morphisms of a category. The main thing you do with morphisms is compose them, and here that means attaching the outputs of one open reaction network to the inputs of another.

Blake and I figured out how to first ‘gray-box’ an open reaction network, converting it into an open dynamical system, and then ‘black-box’ it, obtaining the relation between input and output flows and concentrations that holds in steady state. The first step extracts the dynamical behavior of an open reaction network; the second extracts its static behavior. And both these steps are functors between categories!

For a more detailed story about this, go here:

https://johncarlosbaez.wordpress.com/2017/07/30/a-compositional-framework-for-reaction-networks/

#chemistry
Photo
Add a comment...

Post has shared content
Add a comment...

Post has attachment
Add a comment...

Post has shared content
Add a comment...

Post has attachment
Add a comment...

Post has attachment
Add a comment...
Wait while more posts are being loaded