- Facebook has become the latest technology company to dig into Montreal’s burgeoning artificial intelligence sector, announcing the opening of a research lab in the city Friday.
- “For many years, I’ve seen a steady stream of talented AI researchers … leaving my lab but also leaving our country,” Pineau told dignitaries, including Prime Minister Justin Trudeau.
- That would put it on par with three other Facebook hubs currently based in New York City, Paris and Menlo Park, Calif., and serve as recognition that Montreal has quickly developed a concentration of expertise in the area of artificial intelligence.
- Apart from the lab, Facebook said it intends to invest $7 million in the city’s AI community to fund research and students.
- Yoshua Bengio, a computer science professor at Université de Montréal and an AI researcher, says Facebook is not just applying artificial intelligence, but is also creating new science.
Facebook has become the latest technology company to dig into Montreal’s burgeoning artificial intelligence sector, announcing the opening of a research lab in the city Friday.
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Artificial Intelligence (AI) is a science and a set of computational technologies that are inspired by—but typically operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action. While the rate of progress in AI has been patchy and unpredictable, there have been significant advances since the field’s inception sixty years ago…
Toby Walsh, Professor Artificial Intelligence, University of NSW Sydney “There’s lots of AI already in our lives. You can already see it on your smartphone every time you use Siri, every time you ask a lexer a question, every time you actually use your satellite navigation. You are using one of these algorithms. You are using some AI that’s recognizing your speech, answering questions, giving you search results recommending books for you to buy on Amazon. They’re the beginnings of AI everywhere in our lives.”
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- Meet Canada, the Queen of AIIt’s not often big business, government, non-profits and universities agree on anything, but when it comes to Canada being THE place for AI research and development, everyone is on board, including ROSS Intelligence.The news seemed to arrive all at once, even though Canada has long been at the forefront of technology, from Vancouver’s film studios to Montreal’s world-class animation talent.
- Everyone seemed to come together (a rarity) and as a group, all parties were thinking ahead (another rarity): academia, government, non-profit organizations and businesses all came out in strong support of artificial intelligence research and development.The announcements were made in relatively quick succession: A new federal budget would provide $125 million to improve Canada’s competitive and strategic advantage in AI.
- “Deep learning is the cause of the AI renaissance and Canada was one of the only places that would fund deep learning research,” says Jimoh Ovbiagele, Co-founder and CTO at ROSS Intelligence.
- Image: Kenny LouieAnd although Ovbiagele says American companies hired many of Canada’s deep learning pioneers, offering them large salaries and resources like data (the key ingredient for machine learning) to support their research, Canada is still a leader in the field.
- We will be working with Canadian research institutions, like the University of Toronto, to advance deep learning research and application,” says Ovbiagele.As for companies like Google and Microsoft, their role in advancing AI and technology is absolutely critical.
The news seemed to arrive all at once, even though Canada has long been at the forefront of technology, from Vancouver’s film studios to Montreal’s world-class animation talent. But in the past few…
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- Google’s neural network, software which uses statistics to approximate how the brain learns, taught itself to detect the shapes of cats and humans with more than 70% accuracy.
- “Over the last five years it’s been pretty incredible, the progress of deep [neural] nets,” says Grant Van Horn, lead competition organizer and graduate student at California Institute of Technology.
- Van Horn says this latest Google competition differs from ImageNet, which forces algorithms to identify a wide variety of objects like cars and houses and boats, because iNat requires AI to examine the “nitty-gritty details” that separate one species from another.
- On a scale from general image recognition (ImageNet) to specific (facial recognition,where most faces generally look the same and only slight variations matter), iNat lies somewhere in the middle, Van Horn says.
- Van Horn, who has specialized in building AI that distinguishes differences between birds, said that the iNat competition illustrates how AI is beginning to help people learn about the world around them, rather than just help them organize their photos, for instance.
In 2012, Google made a breakthrough: It trained its AI to recognize cats in YouTube videos. Google’s neural network, software which uses statistics to approximate how the brain learns, taught itself to detect the shapes of cats and humans with more than 70% accuracy. It was a 70% improvement over any other machine learning at the time. Five years later,…
Continue reading “Five years ago, artificial intelligence was struggling to identify cats. Now it’s trying to tackle 5000 species — Quartz”
- In this article, we have listed some of the best free machine learning books that you should consider going through (no order in particular).
- This book holds the prologue to statistical learning methods along with a number of R labs included.
- The online version of the book is available now for free.
- For the mathematics- savvy people, this is one of the most recommended books for understanding the magic behind Machine Learning.
- This book has a lot to offer to the Engineering and Computer Science students studying Machine Learning and Artificial Intelligence.
In this article, we have listed some of the best free machine learning books that you should consider going through (no order in particular).
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- The online version of the book is now complete and will remain available online for free.
- For more information about this 700+ pages free book and its authors, click here.
- The picture below represents a selection of (non-free) deep learning books: you can check them here.
- For other free data science books, click here.
- To access the free deep learning textbook, scroll down to the contents section, below the picture.
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in partic…
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- Though many fear what could happen when AI is fully incorporated (mainly due to sci-fi movies that portray the AI as somehow malicious) the rise of artificial intelligence will ultimately improve many aspects of our everyday lives.
- With the use of artificial intelligence, retailers can now focus on the manufacturing and quality of the product while the AI sorts through the data and makes it clear and concise.
- With the increased efficiency and integration of strong artificial intelligence some jobs will inevitably be taken over by machines.
- As quickly as artificial intelligence is advancing, there are still challenges that need to be overcome before there is a full shift towards strong AI use.
- This data is the basis for the central concept of artificial intelligence: machine learning.
This year, 2017, has been dubbed the year artificial intelligence (AI). With developers already beginning to innovate and improve the technologies that already exist, the potential growth in the field is undeniable. The question of strong artificial intelligence is not one of “if” but one of “when” and it is only a matter of time before artificial intelligence is fully integrated into our lives. There are two main types of artificial intelligence to keep an eye out for: strong and weak.
Continue reading “Artificial Intelligence: The Future Of Everything”