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The Deep Learning Gold Rush of 2015

Terrific and to the point overview of the major technological innovations we have witnessed in Silicon Valley in the last few decades by : an Entrepreneur, Scientist, and Co-Founder of vision.ai, previously a Postdoctoral Scholar at MIT’s Computer Science and Artificial Intelligence Laboratory, and obtained a PhD in Robotics from Carnegie Mellon University, and studied Physics/CS as an undergrad.

“In the last few decades, we have witnessed major technological innovations such as personal computers and the internet finally reach the mainstream. And with mobile devices and social networks on the rise, we’re now more connected than ever. So what’s next? When is it coming? And how will it change our lives? Today I’ll tell you that the next big advance is well underway and it’s being fueled by a recent technique in the field of Artificial Intelligence known as Deep Learning.”

Tomasz’s overview starts from the 1970s with Semiconductors towards 2015-2020 with Deep Learning Revitalising Robotics (see image below).

“To understand why it took so long for Deep Learning to take-off, let’s take a brief look at the key technologies which defined Silicon Valley over the last 50 years.  The following timeline gives an overview of where Silicon Valley has been and where it’s going.”

Teh Futures Agency - Silicon Valley Innovatons Timeline

He then gives a historical overview of all the important technologies invented in Silicon Valley:

1970s: Semiconductors
1980s: Personal Computers
1990s: Internet
2000s: Mobile and Social
2010-2015: Deep Learning comes to the party
2015-2020: Deep Learning Revitalises Robotics

As reported previously on The Futures Agency blog as well – check our archive on Artifical Intelligence btw, Tomasz continues: “Google and Facebook announced that their operations are now being powered by Deep Learning. And with most Deep Learning Titans representing the tech giants (Yann LeCun at Facebook Research, Geoffrey Hinton at Google, Andrew Ng at Baidu), Deep Learning is likely to become one of the most sought after tech skills. With Toyota to invest in $1 Billion in Robotics and Artificial Intelligence Research (November 6, 2015), the announcement of YC Research (October 7, 2015), and the new Google Brain Residency Program “Pre-doc” AI jobs (October 26, 2015), Silicon Valley just got a whole lot more interesting.”

The hierarchical award-winning "AlexNet" Deep Learning architecture  Visualized using MIT's Toolbox for Deep Learning Neuron Visualization

The hierarchical award-winning “AlexNet” Deep Learning architecture
Visualized using MIT’s Toolbox for Deep Learning Neuron Visualization

And…

“Massive hiring of deep learning experts by the leading tech companies has only begun, but we also should be on the lookout for new ventures built on top of Deep Learning, not just a revitalization of last decade’s successes. On this front, keep a close look at the following Deep Learning Cloud Service upstarts: Richard Socher from MetaMindMatthew Zeiler from Clarifai, and Carlos Guestrinfrom Dato.

(…)

With their 2013 acquisition of Boston Dynamics (a hardware play), 2014 acquisition of DeepMind (a software play), and a serious autonomous car play, Google is definitely early to the Robotics party. But the noteworthy bits are happening at the intersection of deep learning and robotics.  I suggest taking a closer look at the Robotics research of Pieter Abbeel of Berkeley, Abhinav Gupta of Carnegie Mellon, and Ashutosh Saxena of Stanford — all likely stars in the next Deep Learning for Robotics race. As long as Rodney Brooks keeps creating innovative Robotics platforms like Baxter, my expectations for Robotics are off the charts.”

In other words, head over and find out all about why it’s pretty clear that everybody is rushing to get some of the Deep Learning Silicon Valley Gold.

Related:

Check out ‘Redefining the relationship of man and machine’ – an audio-visual meditation by Gerd Leonhard.

In this unique film, Futurist Gerd Leonhard reads his chapter in the 2015 book ‘The Future of Business’, entitled ‘Redefining the relationship of man and machine’. In his piece, Gerd addresses the key issues and opportunities that will arise from an increasing convergence of humanity and technology, touching on related topics such as AI, Digital Ethics, reductionism, technological unemployment and machine-thinking.

And some more related media, created by Gerd Leonhard.

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Posted by Rudy de Waele aka @mtrends / shift2020.com

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