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Category: computing – Page 865

“A common challenge to the ideas presented in this book is that these exponential trends must reach a limit, as exponential trends commonly do.” –Ray Kurzweil, The Singularity Is Near

Much of the future we envision today depends on the exponential progress of information technology, most popularly illustrated by Moore’s Law. Thanks to shrinking processors, computers have gone from plodding, room-sized monoliths to the quick devices in our pockets or on our wrists. Looking back, this accelerating progress is hard to miss—it’s been amazingly consistent for over five decades.

But how long will it continue?

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More urgency placed on making Microfluidics/ embedded H2O droplets for cooling microchips so that the emergence of high performing microchips coming in the future.

DARPA and Lockheed Martin have a plan to build microfluidic cooling into modern microprocessors. This could dramatically improve CPU cooling and break the bottleneck on clock speed scaling — at least, for a little while.

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More large steps forward in Quantum technology with the latest chip with optical qubits.

The optical chip overcomes a number of obstacles in the development of quantum computers. A research team has demonstrated that on-chip quantum frequency combs can be used to simultaneously generate multiphoton entangled quantum bit states. It is the first chip capable of simultaneously generating multi-photon qubit states and two-photon entangled states on hundreds of frequency modes. The chip is scalable, compact, and compatible with existing technologies.

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Another data scientist with pragmatic thinking which is badly needed today. Keeping it real with Una-May O’Reilly.

Mumbai: Una-May O’Reilly, principal research scientist at Anyscale Learning For All (ALFA) group at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory, has expertise in scalable machine learning, evolutionary algorithms, and frameworks for large-scale, automated knowledge mining, prediction and analytics. O’Reilly is one of the keynote speakers at the two-day EmTech India 2016 event, to be held in New Delhi on 18 March.

In an email interview, she spoke, among other things, about how machine learning underpins data-driven artificial intelligence (AI), giving the ability to predict complex events from predictive cues within streams of data. Edited excerpts:

When you say that the ALFA group aims at solving the most challenging Big Data problems—questions that go beyond the scope of typical analytics—what do you exactly mean?

Typical analytics visualize and retrieve direct information in the data. This can be very helpful. Visualizations allow one to discern relationships and correlations, for example. Graphs and charts plotting trends and comparing segments are informative. Beyond its value for typical analytics, one should also be aware that the data has latent (that is, hidden) predictive power. By using historical examples, machine learning makes it possible to build predictive models from data. What segments are likely to spend next month? Which students are likely to drop out? Which patient may suffer an acute health episode? Predictive models of this sort rely upon historical data and are vital. Predictive analytics is new, exciting and what my group aims to enable technologically.

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“A metaphorical chip holding all the programming for our universe stores information like a quantum computer.” This is the radical insight to the foundation of our Universe developed by Mark Van Raamsdonk, a professor of theoretical physics at the University of British Columbia, that says that the world we see around us is a projection from a set of rules written in simpler, lower-dimensional physics—just as the 2D code in a computer’s memory chip creates an entire virtual 3D world. “What Mark has done is put his finger on a key ingredient of how space-time is emerging: entanglement,” says Gary Horowitz, who studies quantum gravity at the University of California Santa Barbara. Horowitz says this idea has changed how people think about quantum gravity, though it hasn’t yet been universally accepted. “You don’t come across this idea by following other ideas. It requires a strange insight,” Horowitz adds. “He is one of the stars of the younger generation.”

“We’re trying to construct a dictionary,” says Van Raamsdonk, that allows physicists to translate descriptions of our complex universe into simpler terms. If they succeed, they will have found the biggest jigsaw piece in the puzzle of a Grand Unified Theory—something that can describe all of the forces of our universe, at all scales from the atomic to the galactic. That puzzle piece is, specifically, something that can describe gravity within the framework of quantum mechanics, which governs physics on small scales. Such a unified theory is needed to explain the extreme scenarios of a black hole or the first moments of the universe.”

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Thousands of electrical components make up today’s most sophisticated systems – and without innovative cooling techniques, those systems get hot. Lockheed Martin is working with the Defense Advanced Research Projects Agency (DARPA) Microsystems Technology Office (MTO) on its ICECool-Applications research program that could ultimately lead to a lighter, faster and cheaper way to cool high-powered microchips – by cooling the chips with microscopic drops of water.

This technology has applications in electronic warfare, radars, high-performance computers and data servers.

A core team of Lockheed Martin engineers is working on a solution to meet the goal of DARPA’s Inter/Intra Chip Enhanced Cooling (ICECool) program: to enhance the performance of RF MMIC power amplifiers and embedded high performance computing systems through chip-level heat removal techniques. Lockheed Martin experimentally demonstrated the effectiveness of its microfluidic cooling approach which resulted in a four-times reduction in thermal resistance and a corresponding six-times increase in RF output power when compared to conventional cooling techniques.

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A group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have found a way to speed up the Web without actually increasing the connection throughput or making fundamental code changes.

It created Polaris, a framework that determines how to overlap the objects being downloaded by a page and minimize the amounts of time a site fetches individual resources. The framework creates a dependency graph of the page, then uses that to determine when each object should be loaded.

Don’t miss our biggest TNW Conference yet! Join us May 26 & 27 in Amsterdam.

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A huge milestone has just been reached in the field of artificial intelligence: AlphaGo, a program developed by Google’s DeepMind unit, has defeated legendary Go player Lee Se-dol in the first of five historic matches being held in Seoul, South Korea. Lee resigned after about three and a half hours, with 28 minutes and 28 seconds remaining on his clock. The series is the first time a professional 9-dan Go player has taken on a computer, and Lee is competing for a $1 million prize.

“I was very surprised,” said Lee after the match. “I didn’t expect to lose. [But] I didn’t think AlphaGo would play the game in such a perfect manner.” DeepMind founder Demis Hassabis expressed “huge respect for Lee Se-dol and his amazing skills,” calling the game “hugely exciting” and “very tense.” Team lead David Silver said it was an “amazing game of Go that really pushed AlphaGo to its limits.”

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