After decades of experiencing a slow burn, artificial intelligence innovation has caught fire to become the hottest item on the agendas of the world’s top technology firms.
The fuel for this fire? Necessity. “Faced with a constant onslaught of data, we needed a new type of system that learns and adapts, and we now have that with AI,” says Arvind Krishna, Senior Vice President of Hybrid Cloud and Director of IBM Research. “What was deemed impossible a few years ago is not only becoming possible, it’s very quickly becoming necessary and expected.”
As a result, leading tech companies, as well as scores of startups and researchers, have been racing to develop AI solutions that can provide competitive advantage by augmenting human intelligence.
Today’s flurry of AI advances wouldn’t have been possible without the confluence of three factors that combined to create the right equation for AI growth: the rise of big data combined with the emergence of powerful graphics processing units (GPUs) for complex computations and the re-emergence of a decades-old AI computation model—deep learning.
While we’re still only scratching the surface of what this trio can do together, it’s never too early to look ahead. We spoke with 30 experts to explore some of the catalysts for the next wave of AI advances. They identified a new equation for future AI innovation, one in which old variables get a makeover and new variables spur great leaps. Prepare for a formula that includes the advent of small data, more efficient deep learning models, deep reasoning, new AI hardware and progress toward unsupervised learning.