I'm a biomedical and electrical engineer with interests in information theory, complexity, evolution, genetics, signal processing, theoretical mathematics, and big history.
I'm also a talent manager-producer-publisher in the entertainment industry with expertise in representation, distribution, finance, production, content delivery, and new media.
I’ve been paying a lot more attention to the IndieWeb space this year, with the intention of revamping my lifelogging site to both include more services that I still use (and remove the fitness tracking that I decided to stop), as well as become a repository for webmentions.
David, Welcome! Come on in, the water’s fine…
I remember lurking for over a year and a half before dipping a toe in for the first time myself. Everyone I’ve met has been so kind, thoughtful, supportive, and helpful that I now regret having let so much time pass before jumping in with both feet.
Since it looks like you’re playing in the WordPress world, feel free to drop into the #WordPress channel (or any of the others for that matter) anytime to ask questions, help others solve problems (we can always use help with UX/UI, and themes especially), talk about what itches you’re working on, or even just to say “hi”. If you haven’t yet, I’m sure you’ll enjoy meeting some of the WP regulars including pfefferle (Germany), GWG (New York), miklb (Florida), snarfed (San Francisco), jgmac1106 (Connecticut), jeremycherfas (Rome), and me: chrisaldrich (Los Angeles).
I hope that the most overwhelming part isn’t getting to know the community, but the sheer number of things that are becoming possible to do with one’s website that weren’t as easily possible just a few years ago. My biggest problem reading the chat logs usually comes in the form of saying, “That sounds/looks cool, I want that too!” about 8 times a day. My best advice for “eating the whole whale” is to do it one bite at a time.
I’ll also personally extend an invitation to the upcoming IndieWeb Summit in Portland at the end of the month. If you can’t make it in person, there should be enough support to allow a lot of direct participation via chat and live streaming video–it’s not quite as much fun as attending in person, but you can participate to a level higher than most conferences typically allow.
Directed by Alex Chapple. With Keri Russell, Matthew Rhys, Maximiliano Hernández, Holly Taylor. Philip and Elizabeth's troubled marriage is further tested when a mission to discredit a Polish pro-democracy leader reunites Philip with his old flame.
Directed by Daniel Sackheim. With Keri Russell, Matthew Rhys, Maximiliano Hernández, Holly Taylor. A mole hunt within the KGB causes suspicion amongst allies and shatters trust within the Jennings' marriage. Meanwhile, Stan's plan to keep his mole safe puts her at even greater risk of discovery.
Directed by Holly Dale. With Keri Russell, Matthew Rhys, Maximiliano Hernández, Holly Taylor. A crucial agent crumbles under emotional distress and threatens to topple a valuable network of KGB informants.
Probability and statistics have long helped scientists make sense of data about the natural world — to find meaningful signals in the noise. But classical statistics prove a little threadbare in today’s landscape of large datasets, which are driving new insights in disciplines ranging from biology to ecology to economics. It's as true in biology, with the advent of genome sequencing, as it is in astronomy, with telescope surveys charting the entire sky.
The data have changed. Maybe it's time our data analysis tools did, too.
During this three-month online course, starting June 11th, instructors Hector Zenil and Narsis Kiani will introduce students to concepts from the exciting new field of Algorithm Information Dynamics to search for solutions to fundamental questions about causality — that is, why a particular set of circumstances lead to a particular outcome.
Algorithmic Information Dynamics (or Algorithmic Dynamics in short) is a new type of discrete calculus based on computer programming to study causation by generating mechanistic models to help find first principles of physical phenomena building up the next generation of machine learning.
The course covers key aspects from graph theory and network science, information theory, dynamical systems and algorithmic complexity. It will venture into ongoing research in fundamental science and its applications to behavioral, evolutionary and molecular biology.
Students should have basic knowledge of college-level math or physics, though optional sessions will help students with more technical concepts. Basic computer programming skills are also desirable, though not required. The course does not require students to adopt any particular programming language for the Wolfram Language will be mostly used and the instructors will share a lot of code written in this language that student will be able to use, study and exploit for their own purposes.
The course will begin with a conceptual overview of the field.
Then it will review foundational theories like basic concepts of statistics and probability, notions of computability and algorithmic complexity, and brief introductions to graph theory and dynamical systems.
Finally, the course explores new measures and tools related to reprogramming artificial and biological systems. It will showcase the tools and framework in applications to systems biology, genetic networks and cognition by way of behavioral sequences.
Students will be able apply the tools to their own data and problems. The instructors will explain in detail how to do this, and will provide all the tools and code to do so.
The course runs 11 June through 03 September 2018.
Tuition is $50 required to get to the course material during the course and a certificate at the end but is is free to watch and if no fee is paid materials will not be available until the course closes. Donations are highly encouraged and appreciated in support for SFI's ComplexityExplorer to continue offering new courses.
In addition to all course materials tuition includes:
Six-month access to the Wolfram|One platform (potentially renewable by other six) worth 150 to 300 USD.
Free digital copy of the course textbook to be published by Cambridge University Press.
Several gifts will be given away to the top students finishing the course, check the FAQ page for more details.
Best final projects will be invited to expand their results and submit them to the journal Complex Systems, the first journal in the field founded by Stephen Wolfram in 1987.
About the Instructor(s):
Hector Zenil has a PhD in Computer Science from the University of Lille 1 and a PhD in Philosophy and Epistemology from the Pantheon-Sorbonne University of Paris. He co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. He is also the head of the Algorithmic Nature Group at LABoRES, the Paris-based lab that started the Online Algorithmic Complexity Calculator and the Human Randomness Perception and Generation Project. Previously, he was a Research Associate at the Behavioural and Evolutionary Theory Lab at the Department of Computer Science at the University of Sheffield in the UK before joining the Department of Computer Science, University of Oxford as a faculty member and senior researcher.
Narsis Kiani has a PhD in Mathematics and has been a postdoctoral researcher at Dresden University of Technology and at the University of Heidelberg in Germany. She has been a VINNOVA Marie Curie Fellow and Assistant Professor in Sweden. She co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. Narsis is also a member of the Algorithmic Nature Group, LABoRES.
TA: Alyssa Adams has a PhD in Physics from Arizona State University and studies what makes living systems different from non-living ones. She currently works at Veda Data Solutions as a data scientist and researcher in social complex systems that are represented by large datasets. She completed an internship at Microsoft Research, Cambridge, UK studying machine learning agents in Minecraft, which is an excellent arena for simple and advanced tasks related to living and social activity. Alyssa is also a member of the Algorithmic Nature Group, LABoRES.
The development of the course and material offered has been supported by:
The Foundational Questions Institute (FQXi)
John Templeton Foundation
Santa Fe Institute
Swedish Research Council (Vetenskapsrådet)
Algorithmic Nature Group, LABoRES for the Natural and Digital Sciences
Living Systems Lab, King Abdullah University of Science and Technology.
Department of Computer Science, Oxford University
Cambridge University Press
London Mathematical Society
ItBit for the Natural and Computational Sciences and, of course,
the Algorithmic Dynamics lab, Unit of Computational Medicine, SciLifeLab, Center for Molecular Medicine, The Karolinska Institute
Here Goldberg goes into the complexity of potential causes of capitalism. His discussion of The Miracle and what it represents gains a lot more flavor and nuance than the one word construct it’s had up until now in the text.
He discusses Common law as an emergent property of a society. Again here I note some vocabulary stemming from the “Complexity” science movement of the past several decades as well as that of David Christian et al in the Big History conversation. (Speaking of which, I’ve noted he’s got a new book out on the topic.)
I will take some issue with what looks like a logical problem toward the end of the chapter here:
Therefore the demise of our civilization is only inevitable if the people saying and arguing the right things stop talking.
I do take his broader point, but what, praytell, are the right things, particularly when you’ve just made the argument that you’re not exactly sure what complex system caused it all? We really need to know exactly what caused it to be able to fight to maintain the correct parts of the Goldilocks conditions.
In general, I find myself agreeing with the broadest points here and find the arguments and ideas quite intriguing.
A wonderful mentor recently advised me to write for the job that I wanted. I liked this advice a bit more than the classic “dress for the position you want”, but wasn’t quite sure where to start. Writing anything began to feel like an intense endeavor that would map out the path my life would follow singularly, no wandering adventures. A tad dramatic, right? My previous writing had touched on a number of things: graffiti and street art, women’s history, 3D modeling, and workshops. But lately I have felt stuck and I have made all of the excuses: I’m too busy. There’s other tasks that need to be completed first. I’m tired of staring at a computer screen. I’m not a very good writer. When I finally logged into my blog, I found a hacked mess. Another excuse not to write as I focused on rebuilding.
I too spend an inordinate amount of time monkeying around with my website/writing platform, but I also find that by using it as a regular commonplace book, I’m rarely at a loss for something to write about…
In ed tech, schools are the customers, but students are the users.
This also reminds me of the market disconnect between students and their textbooks. Professors are the ones targeted for the “sale” or adoption when the actual purchasers are the students. This causes all kinds of problems in the way the textbook market works and tends to drive prices up–compared to a market in which the student directly chooses their textbook. (And the set up is not too dissimilar to how the healthcare industry works in which the patient (customer) is making a purchase of health care coverage and not actually the health care itself.
I am about to criticize and show examples from a copyright poster (or, for you new-fangled kids, an infographic) I received in the mail today from Turnitin, the anti-plagiarism company. Fair dealin…
Clint you’re dead on in your analysis here. Some of these things are definitely not plagiarism. Worse, they seem to be resorting to fearmongering.
I’m hoping that the marketing department of the company was just trying to round out a list of 10 things for their handy, but improper, infographic. Shame on them for spreading bad information in hopes that increased fear will help to sell their product.
To help fight poor information and to promote the raw power of remixing and extending, I’ll reference this excellent video from Matt Ridley: