Weekly Top 10 Automation Articles

1. There’s No Such Thing As A “Tech Person” In The Age Of AI

When I was an undergrad at MIT, and later an engineer in Silicon Valley, I always felt like a bit of a black sheep because of my perpetual desire to straddle technology and the humanities. That went against the culture of both worlds, indicative of a broader impulse globally to separate the two. 

In hindsight, this separation hasn’t served us so well. As Henry Kissinger wrote in the June 2018 issue of the Atlantic: “The Enlightenment started with essentially philosophical insights spread by a new technology. Our period is moving in the opposite direction. It has generated a potentially dominating technology in search of a guiding philosophy.”

That so-called dominating technology is artificial intelligence. Its sudden rise has already permeated every aspect of our lives, transforming our social, political, and economic systems. We no longer live in a society that reflects our old, manufactured separations. To catch up, we need to restructure the way we learn and work.

Author: Karen Hao

Read More On: MIT TECHNOLOGY REVIEW

2. SpaceX's Crew Dragon Capsule Successfully Docks With ISS, Without Use Of Robotic Arm

A day after its launch atop a Falcon 9 rocket, SpaceX’s uncrewed Crew Dragon spacecraft has successfully docked with the International Space Station, CNN reported on Sunday.

That the docking procedure went without error is not only a sigh of relief for NASA’s Commercial Crew Program—the project to replace the retired Space Shuttle that is years behind schedule—but excellent news for the three astronauts currently residing on the station. There was a chance that the Crew Dragon, which Russian space operators warned did not have a backup docking system, would fail to successfully attach to the station. As CNN noted, there was also a risk that it could damage the ISS.

Author: Tom McKay

Read More On: GIZMODO

3. Don’t Look Now: Why You Should Be Worried About Machines Reading Your Emotions

Could a program detect potential terrorists by reading their facial expressions and behavior? This was the hypothesis put to the test by the US Transportation Security Administration (TSA) in 2003, as it began testing a new surveillance program called the Screening of Passengers by Observation Techniques program, or Spot for short.

While developing the program, they consulted Paul Ekman, emeritus professor of psychology at the University of California, San Francisco. Decades earlier, Ekman had developed a method to identify minute facial expressions and map them on to corresponding emotions. This method was used to train “behavior detection officers” to scan faces for signs of deception.

But when the program was rolled out in 2007, it was beset with problems. Officers were referring passengers for interrogation more or less at random, and the small number of arrests that came about were on charges unrelated to terrorism. Even more concerning was the fact that the program was allegedly used to justify racial profiling.

Author: Oscar Schwartz

Read More On: THE GUARDIAN

4. Shark Or Baseball ? Inside The ‘Black back’ Of A Neural Network

SHAN CARTER, A researcher at Google Brain, recently visited his daughter’s second-grade class with an unusual payload: an array of psychedelic pictures filled with indistinct shapes and warped pinwheels of color. He passed them around the class and was delighted when the students quickly deemed one of the blobs a dog ear. A group of 7-year-olds had just deciphered the inner visions of a neural network.

Carter is among the researchers trying to pierce the “black box” of deep learning. Neural networks have proven tremendously successful at tasks like identifying objects in images, but how they do so remains largely a mystery. Their inner workings are shielded from human eyes, buried in layers of computations, making it hard to diagnose errors or biases. On Wednesday, Carter’s team released a paper that offers a peek inside, showing how a neural network builds and arranges visual concepts.

Author: Gregory Barber

Read More On: WIRED

5. China’s Huawei Has Big Ambitions To Weaken The US Grip On AI Leadership

Ren Zhengfei, the reclusive founder and CEO of China’s embattled tech giant, Huawei, is defiant about American efforts to impede his company with lawsuits and restrictions.

“There is no way the US can crush us,” Ren said in a rare recent interview with international media. “The world cannot leave us because we are more advanced.”

It might sound like bluff and bluster, but these words carry a measure of truth. Huawei’s technology road map, especially in the field of artificial intelligence, points to a company that is progressing more rapidly—and on more technology fronts—than any other business in the world. Apart from its AI aspirations, Huawei is an ascendant player in the next-generation 5G wireless networking market, as well as the world’s second-largest smartphone maker behind Samsung (and ahead of Apple).

Author: Will Knight

Read More ON: MIT TECHNOLOGY REVIEW

6. Google Is Making It Easier For AI Developers To Keep Users’ Data Private

Google has announced a new module for its machine learning framework, TensorFlow, that lets developers improve the privacy of their AI models with just a few lines of extra code.

TensorFlow is one of the most popular tools for building machine learning applications, and it’s used by developers around the world to create programs like text, audio, and image recognition algorithms. With the introduction of TensorFlow Privacy, these developers will be able to safeguard users’ data with a statistical technique known as “differential privacy.”

PRIVACY IS IMPORTANT WHEN AI TOOLS VACUUM UP DATA

Introducing this tool is in keeping with Google’s principles for responsible AI development, Google product manager Carey Radebaugh tells The Verge. “If we don’t get something like differential privacy into TensorFlow, then we just know it won’t be as easy for teams inside and outside of Google to make use of it,” says Radebaugh. “So for us it’s important to get it into TensorFlow, to open source it, and to start to create this community around it.

Author: James Vincent

Read More On: THE VERGE

7. Whoever Predicts the Future Will Win the AI Arms Race

The race for advanced artificial intelligence has already started. A few weeks ago, U.S. President Donald Trump signed an executive order creating the “American AI Initiative,” with which the United States joined other major countries pursuing national strategies for developing AI. China released its “New Generation Plan” in 2017, outlining its strategy to lead the world in AI by 2030. Months after that announcement, Russian President Vladimir Putin declared, “Whoever becomes the leader in this sphere will become the ruler of the world.”

But it’s less clear how much AI will advance, exactly. It may only be able to perform fairly menial tasks like classifying photographs, driving, or bookkeeping. There’s also a distinct possibility that AI will become as smart as humans or more so, able to make complex decisions independently. A race toward a technology with such a range of possible final states, stretching from banal to terrifying, is inherently unstable. A research program directed toward one understanding of AI may prove to have been misdirected after years of work. Alternatively, a plan to focus on small and achievable advances could be leapfrogged by a more ambitious effort.

Author: Adrian Pecotic

Read More On: FOREIGN POLICY

8. Artificial Intelligence Regulation May Be Impossible

Artificial intelligence is a tool humanity is wielding with increasing recklessness. We say it’s for our common good with machine learning hype equal to business profits. But what happens when we don’t have the code of ethics, laws, government accountability, corporate transparency and capability of monitoring the space to be able to achieve AI regulation?

Artificial intelligence regulation isn’t just complex terrain, it’s uncharted territory for an age that is passing the baton from human leadership to machine learning emergence, automation, robotic manufacturing and deep learning reliance.

Author: Michael Spencer

Read More On: FORBES

9. This AI Lets You Deepfake Your Voice To Speak Like Barack Obama

The accent, emotion, and intonation are all mine. But somehow I now sound like a youngish woman with a high-pitched voice.

My feminine “voice skin” was created by Modulate.ai, a company based in Cambridge, Massachusetts. The firm uses machine learning to copy, model, and manipulate the properties of voice in a powerful new way.

The technology goes far beyond the simple voice filters that can let you sound like Kylo Ren. Using this approach, it is possible to assume any age, gender, or tone you’d like, all in real time. Or to take on the voice of a celebrity. I can hold a lengthy phone conversation in the guise of Katie if I wish.

Author: Will knight

Read More On: MIT TECHNOLOGY REVIEW

10. What Is The Best Book On Artificial Intelligence (AI)?

AI is rapidly changing the way we live and do business, which leaves many business leaders feeling like they’re struggling to keep pace with developments. As such, business leaders often ask me for tips on recommend reading – they want to know which books will help them understand the AI revolution, grasp its impact on our world and plan for an AI-driven future.
I read a lot about AI, for my consulting work, and more recently as research for my latest book ‘Artificial Intelligence in Practice’ and, of course, because I find the subject absolutely fascinating. In fact, I’d say I’ve devoured pretty much every key AI book that’s been published in the last decade.

Author: Bernard Marr

Read More On: FORBES

Yusra Hamid