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Which Technologies Will Dominate in 2022?

@machinelearnbot

Predicting the future is hard and risky. But predicting the future in the computer industry is even harder and riskier due to dramatic changes in technology and limitless challenges to innovation. At the beginning of my term as 2014 president of IEEE Computer Society, with help from more than a dozen technology leaders, we set out to survey 23 potential technologies that could change the landscape of computer science and industry by the year 2022. With the IEEE CS 2022 Report, we created a comprehensive document that outlines future disruptive technologies, helps scientists and researchers understand the impact of technologies in the future, and provides the general public with an idea of how technology is evolving, along with its implications for society. At the foundation of the report is our understanding that by 2022, we will be well into a phase where intelligence becomes seamless and ubiquitous to those who can afford and use state-of-the-art information technology.


Developers are using artificial intelligence to spot fake news

#artificialintelligence

The animated face of prototype robot GRACE, Graduate Robot Attending Conference, is tested by Carnegie Mellon University computer scientist Reid Simmons, right, in the lab at the school in Pittsburgh Tuesday, July 9, 2002. It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us.


Sophia the robot is crowdfunding her brain ZDNet

#artificialintelligence

Sophia, the eerily realistic humanoid robot by Hanson Robotics, is asking the public to help fund her Artificial Intelligence (AI). In a video released today, Sophia announced the details of an upcoming token sale for SingularityNET, an open source platform for AI and machine learning that powers her "brain" and endless other robots. Blockchain technology will manage transactions on this open AI ecosystem. You can this executive guide as a PDF (free registration required). The token sale will begin on Dec. 8, 2017, and there is no minimum contribution amount, so anyone can participate.


Eighth planet found in faraway solar system

#artificialintelligence

A record-tying eighth planet has been found in a faraway solar system, matching our own in numbers. Even more amazing, machines and not humans made the discovery. NASA joined with Google on Thursday to announce the finding. This eighth planet orbits the star known as Kepler-90, some 2,545 light-years away. Like Earth, this new planet, Kepler-90i, is the third rock from its sun.


Five Visionary CEOs Share How AI And Digital Will Shape Our Future

#artificialintelligence

Reid Hoffman, the founding CEO of LinkedIn, once told me, "Your ideal timing for innovation is two years because you want to get the runway going." As digital and artificial intelligence transform most industries, I thought it would be interesting to explore how some of today's transformative CEOs envision the future. Below are insights from five CEOs – who are transforming healthcare, smart phones, entertainment, corporate culture and the internet – about their technology breakthrough, and how they see technology changing the world over the next five years. Lixin Cheng: The foldable ZTE Axon M is the first real innovation to hit the smartphone market in the last 10 years. Its two identical 5.2-inch screens enable consumers to take advantage of true multitasking capabilities and much more through four different modes.


Engineers program tiny robots to move, think like insects

#artificialintelligence

While engineers have had success building tiny, insect-like robots, programming them to behave autonomously like real insects continues to present technical challenges. A group of Cornell University engineers has been experimenting with a new type of programming that mimics the way an insect's brain works, which could soon have people wondering if that fly on the wall is actually a fly. The amount of computer processing power needed for a robot to sense a gust of wind, using tiny hair-like metal probes imbedded on its wings, adjust its flight accordingly, and plan its path as it attempts to land on a swaying flower would require it to carry a desktop-size computer on its back. Silvia Ferrari, professor of mechanical and aerospace engineering and director of the Laboratory for Intelligent Systems and Controls, sees the emergence of neuromorphic computer chips as a way to shrink a robot's payload. Unlike traditional chips that process combinations of 0s and 1s as binary code, neuromorphic chips process spikes of electrical current that fire in complex combinations, similar to how neurons fire inside a brain.


Google's Artificial Intelligence Builds Its Own AI 'Child'

#artificialintelligence

It seems that the beginning of an era in which artificial intelligence (AI) systems can build other systems of artificial intelligence has arrived. As recently, the tech giant Google's Artificial Intelligence (AI) has built its own AI (Artificial Intelligence) child. The day has come when machines make other machines. To be more concrete, it is the beginning of an era in which artificial intelligence systems can build other systems of artificial intelligence. An advance that has made the tech giant Google's AutoML project a reality by designing a computer vision system that far exceeds the most cutting-edge models.


NASA uses Google machine learning for exoplanet detection ZDNet

#artificialintelligence

An eighth planet orbiting a Sun-like star over 2,500 light years away called Kepler-90 has been detected by running the data from NASA's Kepler Space Telescope through a Google neural network. The network was trained using 15,000 previously vetted signals from the Kepler exoplanet catalogue, NASA explained, before it moved on to learning how to detect weaker signals. "We got lots of false positives of planets, but also potentially more real planets," said NASA Sagan postdoctoral fellow Andrew Vanderburg. "It's like sifting through rocks to find jewels. If you have a finer sieve, then you will catch more rocks but you might catch more jewels, as well."


Building an Audio Classifier using Deep Neural Networks

@machinelearnbot

Understanding sound is one of the basic tasks that our brain performs. This can be broadly classified into Speech and Non-Speech sounds. We have noise robust speech recognition systems in place but there is still no general purpose acoustic scene classifier which can enable a computer to listen and interpret everyday sounds and take actions based on those like humans do, like moving out of the way when we listen to a horn or hear a dog barking behind us etc. Our model is only as complex as our data, thus getting labelled'data is very important in machine learning'. The complexity of the Machine Learning systems arise from the data itself and not from the algorithms.


IT leaders turn to AI to defend against AI-powered cyberattacks

#artificialintelligence

"Critical component" Some 91 percent of cybersecurity professionals are worried that next-generation cyberattacks will be based around AI, a study from Webroot found. As TechRepublic reports, most of the experts surveyed said they will defend against AI-based attacks using more AI. Almost all the businesses (99%) intending to use AI are optimistic it will improve their cybersecurity responses. The technology is being used in three key ways to augment existing anti-malware solutions. These percentages aren't the same across the globe.