The implications of advancing technology to a point where its applications can mimic, assume or replace the role of people, to a point where humankind is no longer needed to guide such developments, leads to a multitude of questions about what this means for the future of society.
Last year was huge for advancements in artificial intelligence and machine learning. But 2017 may well deliver even more. Here are five key things to look forward to.
This archive contains many of Turing's letters, talks, photographs and unpublished papers, as well as memoirs and obituaries written about him. It contains images of the original documents that are held in the Turing collection at King's College, Cambridge.
The TERMINUTER app is an automated cognitive meeting minutes tool, mainly based on speech-to-text technology. The app automatically writes and structures meeting minutes with decisions and to-dos and even alerts you if owners or deadlines are not defined.
If we are going to make systems that are going to be more intelligent than us, it's absolutely essential for us to understand how to absolutely guarantee that they only do things that we are happy with.
The coming-of-age of artificial intelligence, 'social robots' and big data is having a massive impact on the way decisions are made in organisations. It follows that if we are to maximise know-how and expertise, the outputs from this technology-enabled channel must be integrated into how we work. Augmenting judgment and experience in this way also supports the move towards evidence-based decision making.
Can machines (e.g. robots) act and behave like humans? More to the point, do we want them to? Making them more and more like us humans could be a blueprint for another flawed species!
Google doesn't rely on any one strategy, but deploys a number of them to create an intricate-but powerful-innovation ecosystem that seems to roll out innovations by the dozens.
You may think you choose to read one story over another, or to watch a particular video rather than all the others clamouring for your attention.
But in truth, you are probably manipulated into doing so by publishers using clever machine learning algorithms
If you need to do a job more than once then automate it - or so the wisdom goes. And now the growing availability of intelligent, automated software - or bots - is making automation a reality for businesses of all sizes.
In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. This animated presentation explains machine learning in simple to follow graphics.
As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. The discussion tends toward a Manichean guessing game: which jobs will or won't be replaced by machines?
Teaching computers to understand casual, contextual conversation in every language and accent is key to this quest to normalise our interactions with computers and to place Google even more squarely at the centre of our lives.
The use of machine learning, expert systems and analytics in combination with big data, is the natural evolution of what has been two different disciplines. They are converging.
Despite improvements in cognitive technologies, that dream managerial scenario is still far from reality. Decisions that executives face don't necessarily fit into defined problems well suited for automation.