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As achievements go, learning how to pick up objects doesn’t sound quite as impressive as twice beating the world Go champion – it is, after all, something the average toddler can do. But it’s the fact that the robots themselves figured out the best way to do it using neural networks that makes this notable.

A recent Google report spotted by TNW explains how the company let robot arms pick up a variety of different objects, using neural networks to learn by trial-and-error the best way to handle each. Some 800,000 goes later, the robots seemed to have it figured out pretty well …

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Government’s other big NextGen Program “Advanced Research Projects Agency-EnergyAdvanced Research Projects Agency-Energy” (ARPA) is funding a personal climate change solution with robots, foot coolers, etc. There is one fact; US Government does love their acronyms.


Why heat or cool a whole building when you could heat or cool individual people instead?

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Allen Institute working with Baylor on reconstructing neuronal connections.


The Intelligence Advanced Research Projects Activity (IARPA) has awarded an $18.7 million contract to the Allen Institute for Brain Science, as part of a larger project with Baylor College of Medicine and Princeton University, to create the largest ever roadmap to understand how the function of networks in the brain’s cortex relates to the underlying connections of its individual neurons.

The project is part of the Machine Intelligence from Cortical Networks (MICrONS) program, which seeks to revolutionize machine learning by reverse-engineering the algorithms of the brain.

“This effort will be the first time that we can physically look at more than a thousand connections between neurons in a single cortical network and understand how those connections might allow the network to perform functions, like process visual information or store memories,” says R. Clay Reid, Ph.D., Senior Investigator at the Allen Institute for Brain Science, Principal Investigator on the project.

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?

I like this article; why? Because if I plan to make any investment into a robot that is my personal assistant, or housekeeper, or caregiver, etc. I want to ensure that they fit my own needs as a person. Many of us have taken some sort of a personality profile for work; interview for jobs where you were reviewed to be a “fit” culturaly, etc. as well as met people 1st before you hired them. So, why should be any different from the so called “humnoid robots?” And, this should be intriguing for some of us where only 6% of your gender thinks and processes information like you do.


Emotional behaviors can make your drone seem like it’s an adventurer, anti-social, or maybe just exhausted.

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Now, we’re saying 50 yrs instead of 30 yrs. And, 3 months ago it was 10 yrs. I guess 6 months from now it will be 100 yrs from now. Folks need to get a little more pragmatic instead of hyping too much or you will lose creditability with consumers and the markets.


Pew Report: Majority think AI will replace humans, though most still believe their job is secure by Steven Loeb on March 10, 2016.

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Not sure that I buy into this one. Hand gestures like anything else is often influenced by someone’s background, culture, etc. It is a known fact that in the US we have terrorists of all backgrounds not just from a particular origin, etc.; so not sure that it would have picked someone like Timothy McVeigh as a terrorist. https://lnkd.in/b4kws3t show.


Gruesome videos of terror-driven killings have grown increasingly common over the years, and, cloaked by a scarf or a hood, the perpetrators can be difficult to identify. Researchers in Jordan have now developed a way to recognize terrorists when they make the commonly displayed ¿V¿ sign

Gruesome videos of terror-driven killings have grown increasingly common over the years, and, cloaked by a scarf or a hood, the perpetrators can be difficult to identify. Researchers in Jordan have now developed a way to recognize terrorists when they make the commonly displayed ‘V’ sign.

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I believe there are good advances in AI due to the processing performance; however, as I highlighted earlier many of the principles like complex algorithms along with the pattern & predictive analysis of large volumes of information hasn’t changed much from my own work in the early days with AI. Where I have concerns and is the foundational infrastructure that “connected” AI resides on. Ongoing hacking and attacks of today could actually make AI adoption fall really short; and in the long run cause AI to look pretty bad.


A debate in New York tries to settle the question.

By Larry Greenmeier on March 10, 2016.

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