3 Top Blog Entries Over the Last 7 Days

A Peek into Einstein's Zurich Notebook

A Peek into Einstein's Zurich Notebook

Kudos to Professor John D. Norton at the Department of History and Philosophy of Science at the University of Pittsburgh for sharing and codifying Einstein's Zurich notebook. Here we see Einstein recounting the elements of the four-dimensional approach to relativity and electrodynamics of Minkowski, starting with the four spacetime coordinates (x, y, z, ict) = (x1, x2, x3, x4) and proceeding through scalars, four-vectors and six-vectors and the operations allowed with them. See more here.

John Morgan's beautiful brain on Riemannian Covariance Matrices

John W. Morgan | Lecture 1 | Introduction to Riemannian geometry, curvature and Ricci flow. Absolutely fantastic lecture by the great John Morgan. John Morgan is a professor of mathematics and founding director of the Simons Center for Geometry and Physics at Stony Brook University. His work is in the areas of geometry and topology. He has concentrated study of manifolds and smooth algebraic varieties. His most recent works include books, jointly with Gang Tian, explaining in detail the proof of the Poincaré conjecture and the geometrization conjecture, both of which concern the nature of three-dimensional spaces. See here.

Oren Etzioni and Peter Clark

Breakthrough for A.I. Technology: Passing an 8th-Grade Science Test

Kudos to Drs. Oren Etzioni, left, & Peter Clark, managers of the Aristo project at the the Allen Institute for Artificial Intelligence. After many previous competitions by colleagues in the field of artificial intelligence, to create an AI system that could pass an 8th Grade Science Examination, the team have succeeded in creating an AI system that does indeed pass an 8th-Grade Science Test, and get 80% on a 12th grade Science examination. Read here.





Blog Entries Over Time

Fractional order neural networks for system identification

Fractional order neural networks for system identification

Kudos to Dhiraj Kalamka and his fellow researchers at Intel where they efficacy of the Brain Floating Point (BFLOAT16) half-precision format for Deep Learning training across image classification, speech recognition, language modeling, generative networks and industrial recommendation systems. Kalamkar, D., Mudigere, D., Mellempudi, N., Das, D., Banerjee, K., Avancha, S., Vooturi, D.T., Jammalamadaka, N., Huang, J., Yuen, H. and Yang, J., 2019. A Study of BFLOAT16 for Deep Learning Training. arXiv preprint arXiv:1905.12322.

Fractional order neural networks for system identification

Fractional Order Neural Networks for System Identification

Kudos to Aguilar et. al., fantastic paper on fractional order neural networks (FONN) for system identification where their learning algorithm was generalized considering the Grünwald-Letnikov fractional derivative. They validated their new black box modeling approach by the identification of three different systems (two benchmark systems and a real system). Comparisons vs others approaches showed that the proposed FONN model reached better accuracy with less number of parameters. Aguilar, C.Z., Gómez-Aguilar, J.F., Alvarado-Martínez, V.M. and Romero-Ugalde, H.M., 2020. Fractional order neural networks for system identification. Chaos, Solitons & Fractals, 130, p.109444.

Kip_Thorne & Paul Murdin

Black Hole Apocalypse

  • By Nova
  • |
  • August 12, 2019

See Fantastic documentary of black holes and how Kip Thorne wagered with Paul Murdin as to whether black holes existed and how they proved it did. This is a fantastic documnetary. Start it at 4:15. Take a mind-blowing voyage to the most powerful and mysterious objects in the universe. Black holes are the most enigmatic and exotic objects in the universe. They’re also the most powerful, with gravity so strong it can trap light.

Taulbee Survey 2018

2018 Taulbee Survey: Data of US & Canada Computer Sciences 2018 Released

Undergrad Enrollment Continues Upward; Doctoral Degree Production Declines but Doctoral Enrollment Rises. The survey, conducted annually by the Computing Research Association, documents trends in student enrollment, degree production, employment of graduates, and faculty salaries in academic units in the United States and Canada that grant the Ph.D. in computer science (CS), computer engineering (CE), or information (I). Download here. .

Murray Gell-Mannk

Murray Gell-Mann, Who Peered at Particles and Saw the Universe, Dies at 89

Dr. Murray Gell-Mann in 1953 or 1954. He collaborated with the renowned physicist Richard Feynman at Caltech. Much as atoms can be slotted into the rows and columns of the periodic table of the elements, Dr. Gell-Mann found a way, in 1961, to classify their smaller pieces — subatomic particles like protons, neutrons, and mesons, which were being discovered by the dozen in cosmic rays and particle accelerator blasts. Arranged according to their properties, the particles clustered in groups of eight and 10.

Professor of Physics, Hans Roslings' 200 Countries 200 Years

This clip from 2010 plots the health and wealth of 200 countries over 200 years. Animating data in real space, Hans Rosling explains how global health and wealth trends have changed since 1810. Hans Rosling was a Swedish physician, academic, statistician, and public speaker. He was the Professor of International Health at Karolinska Institute and was the co-founder and chairman of the Gapminder Foundation, which developed the Trendalyzer software system

US Plug in Sales

Interesting perspective of electric plug-in vehicle sales since 2012.It is interesting how despite the continual bad news about fellow SOuth African Elon Musk, Tesla rises to the top and dominates in the last few years.

18 years of tech disruption in 60 seconds

18 years of #ech #isruption in 60 seconds. This is how the ranking of the 15 top global brands has changed over the last 19 years. Notice how quickly Google and APple rise. Questions baout Amazon will yet to be seen. By 2025 will there be any non-tech #Brands in the top 20?

Rory Lewis Mathematics for Artificial Intelligence

Mathematics for Artificial Intelligence – Calculus & Optimization

This is a very well laid out article, well written, that does a great job identifying and focusing on the essential elements in machine learning that are extrinsically linked to mathematical principles. Nikola Živković answers a questioni I often hear from students, "How much math should I know in order to get into the field?” -- In particular, "How much calculus do I need for artificial intelligence and machine learning?". Živković answers these questions by eloquently stating "Machine learning and deep learning applications usually deal with something that is called the cost function, objective function or loss function. "

See moore at his blog here.

Mathematics of Karen Uhlenbeck

Congrats to Karen Uhlenbeck; first woman to win Abel Prize for mathematics

Dr. Uhlenbeck was awarded the Abel prize for her discovery of a phenomenon called “bubbling,” among other effervescent results. Even Robert MacPherson, a topologist and faculty member in mathematics at the institute, made a rare social appearance. A decade ago, Dr. MacPherson and a collaborator formulated an equation describing how, in three and higher dimensions, individual bubbles evolve in live foams — the fleeting foam at the meniscus in his champagne flute, for instance, or the more enduring head on a pint of beer. Dr. Uhlenbeck’s contribution is her pioneering achievements in geometric partial differential equations, gauge theory and integrable systems. Here dA/dt is the rate of change of the area of a domain, αi is the exterior (turning) angle at a triple junction on that domain (where three domain walls meet - looking at a.>.See journal paper here.

Rory Lewis artificial intelligence and neuroscience

How the brain distinguishes between objects

Now available on GitHub. This is the version released with the original paper. It contains 2 million (question, answer) pairs per module, with questions limited to 160 characters in length, and answers to 30 characters in length. Note the training data for each question type is split into "train-easy", "train-medium", and "train-hard". This allows training models via a curriculum.

See the original paper here

Download the data set and code from GitHub here

Rory Lewis artificial intelligence

Good introductory video

Start watching Bill Shander's class on Skillshare

Rory Lewis artificial intelligence and d3.js

Mike Bostock, master "observer

Excerpt from Mike Bostock · Jun 15, 2018. See here. For example, say I’m happily biking along 🚲😅 at when I get passed by a car 🚗💨 going . I might think: Yikes! That car was going three times my speed! Or: That car was going faster than me! (Cars are scary!) Or maybe I’m a cryptocurrency speculator, and I bought one Dinglecoin at the start of the year for and then sold it yesterday for . I’d say: *Oops, my return was *. Maybe I should invest elsewhere. There are many ways to compare values. Depending on what you seek to understand, one method may be better than another. In this post, we’ll walk through some common methods and consider their uses. Side-by-Side Let’s start by looking separately at 1980 and 2014. Hover over any of the counties to see the underlying values.

Rory Lewis artificial intelligence and neuroscience

How the brain distinguishes between objects

Kudos to Professor James J. DiCarlo and Rishi Rajalingham1 for incredible work deciphering how the inferior temporal (IT) population supports visual object recognition behavior. In the image, for Experiment 1 (n = 10 in monkey M, n = 7 in monkey P) are shown; 8 other sites measured under Experiment 2 they observed spatial clustering of colors.They quantified the non-uniformity of the behavioral deficits using a sparsity index

Rajalingham, Rishi, and James J. DiCarlo. "Reversible inactivation of different millimeter-scale regions of primate IT results in different patterns of core object recognition deficits." Neuron (2019).

Rory Lewis artificial intelligence

Integer to Rational Derivate

This image shows Here pushing the property to the limit (example in case n=3): Kudos to Stefano Maruelli on a very cool way make a Sum work its way into a Rational under certain conditions. The idea is to make a Sum capable to rise, for example, the Square of a Rational a=A/K. Of course n-th power representation of a Rational will follow by the same Telescoping Sum Property. Here is his example of a Step Sum capable to rise an Integer (A) and/or a Rational (A/K) Upper Limit, at the condition that Both the Upper and lower Limits are divisible by the Step (K) we choose.

Rory Lewis Political Engineering Artificial Intelligence

For a Black Mathematician, What It’s Like to Be the ‘Only One’

Fascinating article in NYT. Edray Goins frequently asked himself whether he was right to factor race into the challenges he faced: “Did it really happen that way, or am I blowing it out of proportion?” Photo. Jared Soares. Fewer than 1 percent of doctorates in math are awarded to African-Americans. Edray Goins, who earned one of them, found the upper reaches of the math world a challenging place. See full article in the New York Times here.

The Unexpected Creates Reward When Listening to Music

If you love it when a musician strikes that unexpected but perfect chord, you are not alone. New research shows the musically unexpected activates the reward centre of our brains, and makes us learn about the music as we listen. Researchers at McGill University put 20 volunteers through a musical reward learning task. Each participant chose a colour, then a direction. Continue @ Neuroscience News here or read the original paper here. Gold, Benjamin P., et al. Musical reward prediction errors engage the nucleus accumbens and motivate learning. Proceedings of the National Academy of Sciences Feb 2019.

Rory Lewis UCCS Bachelor of Innovation

Riemannian Covariance Matrices

Not that I am trying to draw in more than 3-Dimenions. But our hypothesis is that a manifold with n-dimenions with clustering could procure a machine learning system to learn different dimenions differently and thus become smart. Photo taken by Eli Brainard UCCS, Feb 6th, 2019. In general, one will find that Riemann distance is better for defining positive semidefinite matrices such as covariance matrices where one wants manifold to be able to retain n-dimenions, than Euclidian distance. To view equations, see larger version of photo here.

Rory Lewis Political Engineering Artificial Intelligence

Political Engineering; How Trump's Artificial Intelligence Reshaped the Election Map

Bostok's amazing bigdata and very cool D3 award winning visualization. Specifically made to interact with artificial intelligence and graphics. This image shows the county shifts from 2012. See full article in the New York Times here.

Model Theory and Proof Theory of Coalgebraic Predicate Logic

Congrats to Tadeusz Litak et al. Generalization of first-order logic originating in a neglected work and show that an entirely general completeness result is NOT possible!

Abstract: We propose a generalization of first-order logic originating in a neglected work by C.C. Chang: a natural and generic correspondence language for any types of structures which can be recast as Set-coalgebras. We discuss axiomatization and completeness results for several natural classes of such logics. Continue reading here.

>Litak, Tadeusz, et al. "Model Theory and Proof Theory of Coalgebraic Predicate Logic." arXiv preprint arXiv:1701.03773 (2017).

Rory Lewis Political Engineering Artificial Intelligence

Political Engineering; How Trump's Artificial Intelligence Reshaped the Election Map

Bostok's amazing bigdata and very cool D3 award winning visualization. Specifically made to interact with artificial intelligence and graphics. This image shows the shift ijn counties Obama won in 2012.See full article in the New York Times here.

Rory Lewis Political Engineering Artificial Intelligence

Political Engineering; How Trump's Artificial Intelligence Reshaped the Election Map

Bostok's amazing bigdata and very cool D3 award winning visualization. Specifically made to interact with artificial intelligence and graphics. This image shows shifts in counties with populations of 150,000 or more. See full article in the New York Times here.

Rory Lewis Political Engineering Artificial Intelligence

Political Engineering; How Trump's Artificial Intelligence Reshaped the Election Map

Bostok's amazing bigdata and very cool D3 award winning visualization. Specifically made to interact with artificial intelligence and graphics. This image shows where more than 75% are whites with no college degree. See full article in the New York Times here.