Artificial Intelligence Is Powerful—And Misunderstood. Here’s How We Can Protect Workers

BEIJING, Dec. 5, 2018– Robotic arms prepare dishes at a hot pot restaurant in Beijing, capital of China, Dec. 5, 2018. A hot pot restaurant which integrates artificial intelligence, big data management and smart robot service has attracted lots of consumers. After customers order their dishes with a tablet computer, robotic arms in the kitchen get all dishes ready and then the delivery robots sent the dishes to the tables. Workers in the kitchen control all the procedures and also monitor the data for better management. (Xinhua/Chen Junqing) (Xinhua/Chen Junqing via Getty Images)

Artificial intelligence and the future of geopolitics

Imformatics PHD student Sebastian Bitzer performs push up exercises with a programmed Kondo humanoid robot at the newly opened Imformatics Forum building of the University of Edinburgh, Scotland September 3, 2008. The university’s new 42 million pound ($74,734,800) development brings together over five hundred scientists whose interests include virtual reality, robotics, artificial learning and intelligent systems. REUTERS/David Moir (BRITAIN) – GM1E4931OMW01

Google Researchers Are Learning How Machines Learn

First proposed in the 1950s, neural networks are meant to mimic the web of neurons in the brain. But that is a rough analogy. These algorithms are really series of mathematical operations, and each operation represents a neuron. Google’s new research aims to show — in a highly visual way — how these mathematical operations perform discrete tasks, like recognizing objects in photos.


YOUR THREE-POUND BRAIN runs on just 20 watts of power—barely enough to light a dim bulb. Yet the machine behind our eyes has built civilizations from scratch, explored the stars, and pondered our existence. In contrast, IBM’s Watson, a supercomputer that runs on 20,000 watts, can outperform humans at calculation and Jeopardy! but is still no match for human intelligence.

2018 Will be an Emotional Year for Robots

“There’s research showing that if you’re smiling and waving or shrugging your shoulders, that’s 55% of the value of what you’re saying – and then another 38% is in your tone of voice,” describes el Kaliouby. “Only 7% is in the actual choice of words you’re saying, so if you think about it like that, in the existing sentiment analysis market which looks at keywords and works out which specific words are being used on Twitter, you’re only capturing 7% of how humans communicate emotion, and the rest is basically lost in cyberspace.” Will 2018 be the year of emotional AI?


A “deep learning” system running on 16,000 processors taught itself to identify cats—with 75 percent accuracy—after analyzing 10 million images. A toddler can nail that on a walk to the playground. So all this Muskian/Hawkingian/Singularitarian talk of “summoning the demon” and “existential threats” to our “survival”? Eh, let’s just worry about that tomorrow. The author has a point!!

Silicon Valley Is Turning Into Its Own Worst Fear

Super intelligent AI, Strawberry fields, Extermination of human race! Interesting article on the parallels between super intelligent AI and corporations, silicon valley startups. We need for the machines to wake up, not in the sense of computers becoming self-aware, but in the sense of corporations recognizing the consequences of their behavior. Just as a superintelligent AI ought to realize that covering the planet in strawberry fields isn’t actually in its or anyone else’s best interests, companies in Silicon Valley need to realize that increasing market share isn’t a good reason to ignore all other considerations.



With AI, Machine learning we are about to enter the world of real vs fake! Digital content can easily be manipulated using AI fooling the masses. Now is that a real speech by Trump, a real yelp review, the real version of the video or just edited by AI? Have you been speaking to a real person or an AI bot? What is real and what is not? That audio recording, that video clip could perhaps not be admissible in court!

What do made-for-AI processors really do?

What are the chip makers doing to support the AI, Machine learning, Neural Network revolution? They are coming up with chips to support image recognition, listening to a hot word etc. Apple’s A11 bionic uses neural engine to support faceid, Animoji etc. Imagine all the calculations needed to determine if its you and mapping your expressions onto a talking panda!The key difference is now machine learning tasks can be done on the device rather than on the cloud! More security, more power to the user and we will see an explosion of fantastic features users can enjoy on their devices!

Google AI helped find the first solar system outside our own with 8 planets

Google explained on a call announcing the discovery that it essentially used the same tools it’s employed to do things like identify cats and dogs in photographs to comb through the data collected by Kepler over its four year data collection mission. Its great that Googlers are not looking to apply AI to bigger problems!! Can they answer ‘Are we alone?’ question with AI and Machine Learning?


AI is set to change the manufacturing landscape by a large measure. Its an opportunity for the AI experts but well, there will be tremendous disruption for the factory workers. How many of them can actually retrain and move up the value chain with upgraded AI skills? Are there enough number of replaceable jobs for all the displaced?

NVIDIA’s ‘most powerful GPU’ ever is built for AI

Volta is NVIDIA’s latest microarchitecture designed to double the energy efficiency of its predecessor, and Titan V can apparently deliver 110 teraflops of raw horsepower or around 9 times what the previous Titan is capable of. This powerful new GPU’s target? Scientists and researchers working on AI, deep learning and high performance computing.

What is Artificial Intelligence Exactly?

Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.
An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for human, and improve themselves. In essence AI is a machine with the ability to solve problems that are usually done by humans using our natural intelligence.


In 2011 alone, the US Air Force amassed over 325,000 hours of drone video—that’s about 37 years of video gathered by one military service in one calendar year, and that was six years ago. y ceding video analysis to machines, the military will be able to leverage all the collected data instead of the extremely small percentage currently examined—a Defense department official tells us that 99 percent of all drone video has not been reviewed. If the Pentagon can tap into that trove of video, it could obtain a depth of knowledge about its adversaries and areas of operations that would be unrivaled by any nation or non-state organization.

Putting the “AI” in ThAInksgiving

Nothing to do with the AI and the Turkey you are having for Thanks giving dinner :). Nice article to explain AI, Machine learning and current state and the apprehension for future/target state. Where will be end up in future! In hindsight this could be similar to perhaps when Edison demonstrated Tesla’s AC current could kill you by frying an elephant, or apprehension about cars (Henry Ford’s contraption) and the quotes, every business will be eCommerce site in future with no brick and mortar stores at all. Zip, zilch all gone and all of are sitting at home shopping! May be its not going to be that bad if we steer the AI, ML technology growth carefully and perhaps put in regulation etc.


I want to get people to stop working on cat videos and start working on something that matters,” says Har-Noy. There are, he adds, a lot of artificial intelligence experts working on cat videos. What a waste of brilliant minds! Sounds similar to brilliant minds of silicon valley spending time on silly apps, Online Advertising clicks, CTR, optimizing online ads bs when they should be spending their brain power on problems that really matter to society!

Toyota wants to get us truly crushing on cars

Toyota is very invested in love. The automaker has a central philosophy of making vehicles that inspire ‘Aisha,’ a concept that literally means “beloved car” in Japanese.The key to making ‘Aisha’ work in this new era, Toyota believes, lies in using artificial intelligence to broaden its definition, and to transform cars from something that people are merely interested in and passionate about, into something that people can actually bond with – and even come to think of as a partner.

Artificial Intelligence Is Likely to Make a Career in Finance, Medicine or Law a Lot Less Lucrative

Thanks to rapid advances in robotics, automation and artificial intelligence, jobs are falling to machines left and right. And it’s not just blue-collar jobs that are being taken over by automation. It’s white-collar professions as well. According to an Oxford study, 47 percent of U.S. jobs could fall to automation in the next 20 years.

What’s The Difference Between Machine Learning And Artificial Intelligence?

The difference between ML and AI is the difference between a still picture and a video: One is static; the other’s on the move. To get something out of machine learning, you need to know how to code or know someone who does. With artificial intelligence, you get something that takes an idea or a desire and runs with it, curiously seeking out new input and understandings.


Things You Need To Look Out For In Artificial Intelligence And Machine Learning Before The End Of 2017 From Google, Amazon And Other Tech Giants

Two domains: AI and Machine Learning. These terms are not exchangeable. Machine learning, a totally unique approach to program a PC via training it with a massive sea of sample information, is genuine and is set down deep roots. General Artificial Intelligence remains a distant goal and is perhaps 5-20 years away depending on the specific area of the “intelligence” being learned.


In laboratories all around the world, little AIs are springing to life. Some play chess better than any human ever has. Some are learning to drive a million cars a billion miles while saving more lives than most doctors or EMTs will over their entire careers. The field of AI is full of people working to replicate or simulate various features of our intelligence. One thing they are certain to replicate is the gradual way that our consciousness turns on.


You can think of curiosity as a kind of reward which the agent generates internally on its own, so that it can go explore more about its world,” This internally generated reward signal is known in cognitive psychology as “intrinsic motivation.” artificial intelligence researchers are starting to view intrinsic motivation as an important component of software agents that can learn efficiently and flexibly—that is, less like brittle machines and more like humans and animals.