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Design of a Superconducting Quantum Computer

John Martinis visited Google LA to give a tech talk: "Design of a Superconducting Quantum Computer." This talk took place on October 15, 2013


Via Szabolcs Kósa
Andreas Pappas's curator insight, March 28, 2014 12:42 AM

Although the video is quite long, it manages to thoroughly address the concepts and difficulties behind developing a quantum super computer. Nevertheless, the language used though-out the video is somewhat complex and without an understanding of the metalanguage used it is difficult to follow. Therefore, this a good resource for those with an advanced knowledge and understanding of quantum computers. 

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VIDEO lecture: First steps in scientific data visualisation using d3.js - by Drew Conway

Mike Dewar (Data Scientist, bit.ly), presents a talk on getting started with data driven design in Javascript to the New York Open Statistical Programming Meetup on Jan. 12, 2012. Mike Bostock's d3 javascript library has lately taken the internet by storm, being the engine underlying a very beautiful set of visualisations (mbostock.github.com/d3/). Because of this, many have investigated d3.js as a potential addition to their current visualisation stack, only to fall over one of some common hurdles. This talk will demonstrate how to clear these first few hurdles, including:
- how to create and serve nice data objects
- how to use chrome's console to inspect and play with your visualisation,
- how d3 interacts with the document object model,
- how to draw arbitrary SVG objects,
- how to use d3.layout to relieve you of a few common graph-vis tasks.

The talk will be useful to those who are curious about using d3.js and wants to get started making interactive and dynamic statistical visualisations. You can download the slides (all written with d3.js) from Mike Dewar's Github: github.com/mikedewar/d3talk

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Memristor and Memristive Systems

Memristor and Memristive Systems Symposium

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Videos of machine learning, artificial intelligence and playful machines

Videos of machine learning, artificial intelligence and playful machines | Science-Videos | Scoop.it
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Google Workshop on Quantum Biology: Classical and Quantum Information in DNA

DNA stores and replicates information. Special sequences of different nucleic acids (adenine, cytosine, guanine, thymine) encode life's blueprints. These nucleic acids can be divided into a classical part (massive core) and a quantum part (electron shell and single protons). The laws of quantum mechanics map the classical information (A,C,G,T) onto the configuration of electrons and position of single protons. Although DNA replication requires perfect copies of the classical information, the core that constitutes this information does not directly interact with the copying machine. Instead, only the quantum degrees of freedom are measured. Thus successful copying requires a correct translation of classical to quantum to classical information. It has been shown that the electronic system is well shielded from thermal noise. This leads to entanglement inside the DNA helix. It is an open question if this entanglement influences the genetic information processing. In this talk I will discuss possible consequences of entanglement for the information flow and the similarities and differences between classical computing, quantum computing and DNA information processing.

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Machine Learning Summer School (by Purdue University) - 65 Lectures

This course will provide a simple unified introduction to batch training algorithms for supervised, unsupervised and partially-supervised learning. The concepts introduced will provide a basis for the more advanced topics in other lectures.

The first part of the course will cover supervised training algorithms, establishing a general foundation through a series of extensions to linear prediction, including: nonlinear input transformations (features), L2 regularization (kernels), prediction uncertainty (Gaussian processes), L1 regularization (sparsity), nonlinear output transformations (matching losses), surrogate losses (classification), multivariate prediction, and structured prediction. Relevant optimization concepts will be acquired along the way.

The second part of the course will then demonstrate how unsupervised and semi-supervised formulations follow from a relationship between forward and reverse prediction problems. This connection allows dimensionality reduction and sparse coding to be unified with regression, and clustering and vector quantization to be unified with classification—even in the context of other extensions. Current convex relaxations of such training problems will be discussed.

The last part of the course covers partially-supervised learning—the problem of learning an input representation concurrently with a predictor. A brief overview of current research will be presented, including recent work on boosting and convex relaxations.

See other lectures at Purdue MLSS Playlist: http://www.youtube.com/playlist?list=...

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Eric Ladizinsky: Evolving Scalable Quantum Computers

Eric Ladizinsky visited the Quantum AI Lab at Google LA to give a talk "Evolving Scalable Quantum Computers." This talk took place on March 5, 2014.

"The nineteenth century was known as the machine age, the twentieth century will go down in history as the information age. I believe the twenty-first century will be the quantum age". Paul Davies

Quantum computation represents a fundamental paradigm shift in information processing. By harnessing strange, counterintuitive quantum phenomenon, quantum computers promise computational capabilities far exceeding any conceivable classical computing systems for certain applications. These applications may include the core hard problems in machine learning and artificial intelligence, complex optimization, and simulation of molecular dynamics .. the solutions of which could provide huge benefits to humanity. 

Realizing this potential requires a concerted scientific and technological effort combining multiple disciplines and institutions ... and rapidly evolving quantum processor designs and algorithms as learning evolves. D-Wave Systems has built such a mini-Manhattan project like effort and in just a under a decade, created the first, special purpose, quantum computers in a scalable architecture that can begin to address real world problems. D-Wave's first generation quantum processors (now being explored in conjunction with Google/NASA as well as Lockheed and USC) are showing encouraging signs of being at a "tipping point" .. matching state of the art solvers for some benchmark problems (and sometimes exceeding them) ... portending the exciting possibility that in a few years D-Wave processors could exceed the capabilities of any existing classical computing systems for certain classes of important problems in the areas of machine learning and optimization. 

In this lecture, Eric Ladizinsky, Co-Founder and Chief Scientist at D-Wave will describe the basic ideas behind quantum computation , Dwave's unique approach, and the current status and future development of D-Wave's processors. Included will be answers to some frequently asked questions about the D-Wave processors, clarifying some common misconceptions about quantum mechanics, quantum computing, and D-Wave quantum computers.

Speaker Info: Eric Ladizinsky is a physicist, Co-founder, and Chief Scientist of D-Wave Systems. Prior to his involvement with D-Wave, Mr. Ladizinsky was a senior member of the technical staff at TRW's Superconducting Electronics Organization (SCEO) in which he contributed to building the world's most advanced Superconducting Integrated Circuit capability intended to enable superconducting supercomputers to extend Moore's Law beyond CMOS. In 2000, with the idea of creating a quantum computing mini -Manhattan-project like effort, he conceived, proposed, won and ran a multi-million dollar, multi-institutional DARPA program to develop a prototype quantum computer using (macroscopic quantum) superconducting circuits. Frustrated with the pace of that effort Mr. Ladizinsky, in 2004, teamed with D-Wave's original founder (Geordie Rose) to transform the then primarily IP based company to a technology development company modeled on his mini-Manhattan-project vision. He is also responsible for designing the superconducting (SC) IC process that underlies the D-Wave quantum processors ... and transferring that process to state of art semiconductor production facilities to create the most advanced SC IC process in the world.

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Crockford on JavaScript - 12 hours of Javascript Language Videos

Douglas Crockford puts the JavaScript programming language in its proper historical context, tracing the language's structure and conventions (and some of its quirks) back to their roots in the early decades of computer science.

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Turing Machine Web Class - Automata Theory

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Arthur C. Clarke - "Fractals of Science" or "The Colors Of Infinity"

Arthur C. Clarke presents this unusual documentary on the mathematical discovery of the Mandelbrot Set (M-Set) in the visually spectacular world of fractal geometry. This show relates the science of the M-Set to nature in a way that seems to identify the hand of God in the design of the universe itself. Dr. Mandelbrot in 1980 discovered the infinitely complex geometrical shape called the Mandelbrot Set using a very simple equation with computers and graphics.

 

Arthur C. Clarke's soft-spoken style sets the "common man" at ease, and his pinpoint commentary makes the concept of fractals easy to understand. One need not be a stellar mathematician to grasp the concepts and why they are profound. The experts are trotted out, and they, too, explain fractal geometry in ways that are accessible to everyman.

 

Fractals are part of our lives, and maths informs everything that exists, whether natural or man-made. In the novel, a software engineer tries to create a program that sets the flapping of a bird's wings to music using mathematical equations. That is exactly what fractals seem to do; they describe events in nature in mathematical ways, and the section of "Colors" which discusses this is eye-opening.

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Speeding up the web and finding the right shade of blue - 83 lectures from Imperial College London

Imperial College London is a science-based institution with a reputation for excellence in teaching and research that attracts 12,000 students and 6,000 staff of the highest international quality.

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Google Python Class [7 VIDEO lectures]

By Nick Parlante

 

Support materials and exercises:
http://code.google.com/edu/languages/google-python-class

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