How robotics and automation could create new jobs in the new normal

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Depending on who you ask, AI and automation will either destroy jobs or create new ones. In reality, a greater push toward automation will probably both kill and create jobs — human workers will become redundant in certain spheres, sure, but many new roles will likely crop up. A report last year from PA Consulting, titled “People and machines: From hype to reality,” supports this assertion, predicting that AI and automation will lead to a net gain in job numbers. This is pretty much in line with findings from the Organization for Economic Co-operation and Development (OECD), a pan-governmental economic body spanning 36 member countries, which noted that “employment in total may continue to rise” even if automation disrupts specific industries.

Automation has gained increased attention amid the great social distancing experiment sparked by COVID-19. But it’s too early to say whether the pandemic will expedite automation across all industries. Recent LinkedIn data suggests AI hiring slowed during the crisis, but there are plenty of cases where automation could help people adhere to social distancing protocols — from robot baristas and cleaners to commercial drones.

Of course, any discussion about automation invariably raises the question of what it means for jobs.

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Helm.ai pioneers breakthrough…. “Deep Teaching” of neural networks

 

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Helm.ai today announced a breakthrough in unsupervised learning technology. This new methodology, called Deep Teaching, enables Helm.ai to train neural networks without human annotation or simulation for the purpose of advancing AI systems. Deep Teaching offers far-reaching implications for the future of computer vision and autonomous driving, as well as industries including aviation, robotics, manufacturing and even retail.

Artificial intelligence, or AI, is commonly understood as the science of simulating human intelligence processed by machines. Supervised learning refers to the process of training neural networks to perform certain tasks using training examples, typically provided by a human annotator or synthetic simulator to machines to perform certain tasks, while unsupervised learning is the process of enabling AI systems to learn from unlabelled information, infer inputs and produce solutions without the assistance of pre-established input and output patterns.

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Exploring the three elephants in the autonomous vehicle room

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The expression “elephant in the room” refers to an important question that everyone knows about but no one wants to discuss because it makes them uncomfortable.

Today, in the area of Autonomous Vehicles (AVs), there are three elephants in the room which are worth exploring.

Let’s get started.

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The 6 unholy AI systems thou shalt not develop

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TLDR; don’t pretend a Magic 8 Ball is a useful tool for grownups and don’t build hate machines

Artificial intelligence may be the most powerful tool humans have. When applied properly to a problem suited for it, AI allows humans to do amazing things. We can diagnose cancer at a glance or give a voice to those who cannot speak by simply applying the right algorithm in the correct way.

But AI isn’t a panacea or cure-all. In fact, when improperly applied, it’s a dangerous snake oil that should be avoided at all costs. To that end, I present six types of AI that I believe ethical developers should avoid.

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Elon Musk claims AI will overtake humans in ‘less than five years’

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Chatbots powered by artificial intelligence are already capable of passing some Turing tests. ( AFP via Getty Images )

Existential threat posed by artificial intelligence is much closer than previously predicted, billionaire warns.

Elon Musk has warned that humans risk being overtaken by artificial intelligence within the next five years.

The prediction marks a significant revision of previous estimations of the so-called technological singularity, when machine intelligence surpasses human intelligence and accelerates at an incomprehensible rate.

Noted futurist Ray Kurzweil previously pegged this superintelligence tipping point at around 2045, citing exponential advances in technologies like robotics, computers and AI.

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Bank of Korea launches a department devoted to blockchain and AI

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Bank of Korea is launching a digital innovation department that will leverage blockchain and AI to improve business efficiency.

The Bank of Korea has reportedly chosen to establish a “Digital Innovation department” through organizational reform in the second half of this year, according to the local news on July 22.

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The ‘android of self-driving cars’ built a 100,000x cheaper way to train AI for multiple trillion-dollar markets

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Level 5 self-driving means autonomous cars can drive themselves anywhere, at any time, in any conditions.

How do you beat Tesla, Google, Uber and the entire multi-trillion dollar automotive industry with massive brands like Toyota, General Motors, and Volkswagen to a full self-driving car? Just maybe, by finding a way to train your AI systems that is 100,000 times cheaper.

It’s called Deep Teaching.

Perhaps not surprisingly, it works by taking human effort out of the equation.

And Helm.ai says it’s the key to unlocking autonomous driving. Including cars driving themselves on roads they’ve never seen … using just one camera.

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How Intuit is moving from mobile-first to AI-first

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“AI fundamentally changes how we develop apps and what apps can do, and I would say we’re at the beginning of that revolution,” Intuit CTO Marianna Tessel said.

In a conversation with Nara Logics CEO Jana Eggers at Transform 2020 today, Tessel outlined some of the key ways that AI is changing the mindset at Intuit, with a focus on the app development process. Notably, Intuit is trying to adapt much in a similar way to how it adapted to the emergence of smartphones.

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Artificial intelligence makes blurry faces look more than 60 times sharper

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This AI turns blurry pixelated photos into hyperrealistic portraits that look like real people. The system automatically increases any image’s resolution up to 64x, ‘imagining’ features such as pores and eyelashes that weren’t there in the first place.

Duke University researchers have developed an AI tool that can turn blurry, unrecognizable pictures of people’s faces into eerily convincing computer-generated portraits, in finer detail than ever before.

Previous methods can scale an image of a face up to eight times its original resolution. But the Duke team has come up with a way to take a handful of pixels and create realistic-looking faces with up to 64 times the resolution, ‘imagining’ features such as fine lines, eyelashes and stubble that weren’t there in the first place.

“Never have super-resolution images been created at this resolution before with this much detail,” said Duke computer scientist Cynthia Rudin, who led the team.

The system cannot be used to identify people, the researchers say: It won’t turn an out-of-focus, unrecognizable photo from a security camera into a crystal clear image of a real person. Rather, it is capable of generating new faces that don’t exist, but look plausibly real.

While the researchers focused on faces as a proof of concept, the same technique could in theory take low-res shots of almost anything and create sharp, realistic-looking pictures, with applications ranging from medicine and microscopy to astronomy and satellite imagery, said co-author Sachit Menon ’20, who just graduated from Duke with a double-major in mathematics and computer science.

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Eye, robot: Artificial intelligence dramatically improves accuracy of classic eye exam

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The classic eye exam may be about to get an upgrade. Researchers have developed an online vision test—fueled by artificial intelligence (AI)—that produces much more accurate diagnoses than the sheet of capital letters we’ve been staring at since the 19th century. If perfected, the test could also help patients with eye diseases track their vision at home.

“It’s an intriguing idea” that reveals just how antiquated the classic eye test is, says Laura Green, an ophthalmologist at the Krieger Eye Institute. Green was not involved with the work, but she studies ways to use technology to improve access to health care.

The classic eye exam, known as the Snellen chart, has been around since 1862. The farther down the sheet a person can read, the better their vision. The test is quick and easy to administer, but it has problems, says Chris Piech, a computer scientist at Stanford University. Patients start to guess at letters when they become blurry, he says, which means they can get different scores each time they take the test.

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Microsoft sacks journalists to replace them with robots

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Users of the homepages of the MSN website and Edge browser will now see news stories generated by AI

Dozens of journalists have been sacked after Microsoft decided to replace them with artificial intelligence software.

Staff who maintain the news homepages on Microsoft’s MSN website and its Edge browser – used by millions of Britons every day – have been told that they will be no longer be required because robots can now do their jobs.

Around 27 individuals employed by PA Media – formerly the Press Association – were told on Thursday that they would lose their jobs in a month’s time after Microsoft decided to stop employing humans to select, edit and curate news articles on its homepages.

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Artificial intelligence can make personality judgments based on photographs

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Russian researchers from HSE University and Open University for the Humanities and Economics have demonstrated that artificial intelligence is able to infer people’s personality from ‘selfie’ photographs better than human raters do. Conscientiousness emerged to be more easily recognizable than the other four traits. Personality predictions based on female faces appeared to be more reliable than those for male faces. The technology can be used to find the ‘best matches’ in customer service, dating or online tutoring.

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