https://www.forbes.com/sites/ibm/2017/03/02/four-catalysts-to-spa...

https://www.forbes.com/sites/ibm/20...tion-in-artificial-intelligence/#1e096dfc172c

Four Catalysts To Spark The Next Wave Of Innovation In Artificial Intelligence

1) The rise of small data: AI solutions today require large amounts of public and proprietary data to train them to perform even the simplest of tasks, like recognizing an object. But diverse and industry-specific data isn’t always plentiful. In the future, AI experts believe smaller datasets will also enable AI innovation. This means AI systems could make decisions and provide results with less training.

2) The holy grail of unsupervised learning: While there are many ways to "teach" AI to augment humans, the ultimate goal is to build advanced reasoning systems that require minimal training, especially for research-intensive fields such as medicine or life sciences. Experts say that while completely unsupervised learning might be a far-fetched goal, we’re getting closer to it as scientists find success with new, less labor-intensive teaching technique.
One such technique is transfer learning, which allows AI engineers to apply a trained model to completely new types of problems with little additional training. For example, applying the same model to solve business problems across different departments of a company. These less supervised techniques allow a machine’s deep network to absorb information from the world without a lot of hand holding or manual inputs.