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Apple's personal assistant Siri is more of a glorified voice recognition feature of your iPhone than a deep conversation partner. A personal assistant that could truly understand human conversations and written texts might actually represent an artificial intelligence capable of matching or exceeding human intelligence. The Canadian startup Maluuba hopes to help the tech industry achieve such a breakthrough by training AI to become better at understanding languages. The key, according Maluuba's leaders, is building a better way to train AIs. Like humans, AI can only get better at understanding languages by practicing.

When Robert Schapire started studying theoretical machine learning in graduate school three decades ago, the field was so obscure that what is today a major international conference was just a tiny workshop, so small that even graduate students were routinely excluded. But it has become one of the hottest fields in computer science, turning once-obscure academic gatherings like the upcoming Annual Conference on Neural Information Processing Systems in Barcelona, Spain, into a sold-out affair attended by thousands of computer scientists from top corporations and academic institutions. "It's been really something to see this field develop, and to see things that seemed impossible become possible in my lifetime," said Schapire, a principal researcher in Microsoft's New York City research lab whose machine learning research is widely used in the field. The NIPS conference, which starts Monday, is so popular because machine learning has quickly become an indispensable tool for developing technology that consumers and businesses want, need and love. Machine learning is the basis for technology that can translate speech in real time, help doctors read radiology scans and even recognize emotions on people's faces.

It's 8:00 am on a Tuesday morning. You've awoken, scanned the headlines on your phone, responded to an online post, ordered a holiday sweater for your mom, locked up the house, and are driving to work, listening to some great new music on the radio. You've also used artificial intelligence (AI) more than a dozen times -- to be roused, to call up local weather report, to purchase a gift, to secure your house, to be alerted to an upcoming traffic jam, and even to identify an unfamiliar song. AI is already pervasive in our world, and it's making a huge difference in our everyday lives. But this is not the AI you've seen in sci-fi movies, with nervous scientists clacking on keyboards and attempting to halt machines from destroying the world. Sometimes it's obvious, like when you ask Siri to get you directions to the nearest gas station, or Facebook suggests a friend for you to tag in an image you posted online. Sometimes less so, like when you use your Amazon Echo to make an unusual purchase on your credit card (like that goofy holiday sweater) and don't get a fraud alert from your bank.

This is how humans operate. We try something, we judge the result and modify our behavior. What some considered to be science fiction only a few years ago, AI is edging closer to reality as decades of research -- combined with advances in compute power, memory, storage, network connectivity, sensors and the software that unites them all -- is poised to enable new classes of intelligent predictive analytics. These innovations will bring benefits to multiple industries, and to society as a whole in the way we lead our everyday lives. Al is going to change our lives for the better as machines learn, reason, act and adapt -- transforming industries by amplifying human capabilities, automating tedious or dangerous tasks, and solving some of our most challenging societal problems.

Meet the Innovators of Washington DC in a brand new episode of What's Next at https://youtu.be/Wacx_Nu7kX8 Artificial intelligence is poised to disrupt industries, social norms, and ways of life across the planet. Here are our top 10 sources for artificial intelligence news, events, job postings, and more across the web: #10 Get Started with these TED Talks One way to get your mind blown about where AI is and where it's heading check out TED's artificial intelligence playlist at http://bit.ly/2gENYd9 #9 Follow the Allen Institute for Artificial Intelligence Microsoft co-founder and billionaire Paul Allen has funded the non-profit Allen Institute for Artificial Intelligence and they have a very active Twitter handle profile with job openings, events, and news. Follow them at http://bit.ly/2gRqXmy #8 Let XPRIZE Challenge You on Facebook and Instagram XPrize is an organization that runs design competitions that challenge technologists to use advanced technologies like AI to benefit mankind and it's run by people like James Cameron, Larry Page, Arianna Huffington, and Ratan Tata. Like them on Facebook at http://bit.ly/2fLkFbG and follow them on Instagram at http://bit.ly/2grBV5f #7 Subscribe to Eazl's Weekly Brain Boosts on YouTube Here at Eazl, we're often reporting on advances in AI that the mainstream media ignores. You can get weekly tech updates that often feature what's happening in AI by subscribing to the Eazl YouTube channel at http://bit.ly/eazlyoutube #6 Learn with MIT's AI Open Courseware Playlist If you're interested in learning about the tech behind AI, MIT has an amazing playlist with tons of free lectures on beginner, intermediate, and advanced AI development topics at http://bit.ly/2grGr3k #5 Bring DeepLearn007 into Your Twitter Feed @deeplearn007 is one of the best people to follow on Twitter for everything AI and futurist technology.

Comment Remember that kid in middle school who was deeply into Dungeons & Dragons, and hadn't seen his growth spurt yet? Machine learning is sort of like that kid – deep, wide, and short – and not so tall. Big data – an increased availability of large data sets for training and deployment has also driven the need for deeper nets. Deeper nets – deep neural nets have multiple layers, and often possess higher-order architecture (width) within a given layer. Clever training – it was discovered that a large dose of unsupervised learning in the earlier stages of training allowed for the net to do its own automated, lower-level feature recognition and extraction, and pass those features on to the next stage for higher-level feature recognition.

Silicon Valley is training computers to see, hear and speak and cars and trucks to drive themselves. Some people aren't so sure how they feel about this new wave of artificial intelligence that summons fears of Terminator-like sentient machines. So Facebook is trying to dispel some of the pop-culture myths with a series of six instructional videos that attempt to explain this complex field of computer science. Whether searching on your smartphone for a good place to eat or trying to avoid traffic on the commute home, Facebook says you are already using artificial intelligence all the time. "I think the more open we can be about it and the more we can demystify and explain how it actually works, the more quickly we can address concerns," said Joaquin Quiñonero Candela, director of applied machine learning at Facebook.

A lot of state of the art machine learning algorithms are available via open source software. Many open source software are designed to be used via a command line interface. I much prefer to use Python as I can mix many packages together, and I can use a combination of Numpy, Pandas, and Scikit-Learn to orchestrate my machine learning pipelines. I am not alone, and as a result, many open source machine learning software provide a Python api. For instance Vowpal Wabbit does not support a Python API that works with Anaconda.

Thanks to the relentless work of dedicated engineers, artificial intelligence, or AI, becomes smarter by the day. But while computers become better at replicating human tasks, reading comprehension, an area where machines have yet to catch up, is declining among young people, suggesting a chilling future in which AI may put people out of work. That is why Noriko Arai, a mathematician at the National Institute of Informatics, decided in November to change the direction of her project from teaching an AI to pass the entrance exam for Japan's most prestigious school -- the University of Tokyo, better known as Todai -- to focusing on improving the reading comprehension of future generations using AI technology. "AI engineers have always said that humans don't have to worry because only menial jobs will be taken over by machines. But what about the people who do such jobs?"