There’s no shortage of dire warnings about the dangers of artificial intelligence these days. Modern prophets, such as late physicist Stephen Hawking and investor Elon Musk, foretell the imminent decline of humanity. With the advent of artificial general intelligence and self-designed intelligent programs, new and more intelligent AI will appear, rapidly creating ever smarter machines that will, eventually, surpass us.
The tech giants Amazon, Google and Facebook have all begun to use machine learning to give you tips on what to wear. Is fashion styling the next field to be disrupted by artificial intelligence (AI), or will the human eye remain supreme?
Data drives our global digital ecosystem, and AI technologies reveal patterns in data. Smartphones, smart homes, and smart cities influence how we live and interact, and AI systems are increasingly involved in recruitment decisions, medical diagnoses, and judicial verdicts. Whether this scenario is utopian or dystopian depends on your perspective.
Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don’t have much to do with real brain science. I’m a professor of bioengineering and neurosciences interested in understanding how the brain works as a system – and how we can use that knowledge to design and engineer new machine learning models.
As a cryptocurrency, there is no physical form that gives Bitcoin value, so it is impossible to perform traditional fundamental analysis of the currency. Consequently, many investors track the so-called technical trading indicators (geometric patterns constructed from historical prices and trading volumes) in order to understand and predict Bitcoin’s future movement.
During the course of a day, robots might be expected to do everything from making a cup of tea to changing the bedding while holding a conversation. These are all challenging tasks that are more challenging when attempted together. No two homes will be the same, which will mean robots will have to learn fast and adapt to their environment. As anyone sharing a home will appreciate, the objects you need won’t always be found in the same place – robots will need to think on their feet to find them.
A common question as these intelligent technologies infiltrate various industries is how work and labor will be affected. In this case, who – or what – will do journalism in this AI-enhanced and automated world, and how will they do it?
We might be on the right track to achieve a more comprehensive, human-level artificial intelligence. Applying this kind of learning to other tasks – perhaps applying it to signals…
In our lab at the University of Saskatchewan we are doing interesting deep learning research related to healthcare applications — and as a professor of electrical and computer engineering, I lead the research team. When it comes to health care, using AI or machine learning to make diagnoses is new, and there has been exciting and promising progress.
When artificial intelligence systems start getting creative, they can create great things – and scary ones. Take, for instance, an AI program that let web users compose music along with a virtual Johann Sebastian Bach by entering notes into a program that generates Bach-like harmonies to match them.