The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

The views expressed below are my own and do not reflect those of my employer or its clients. The underlying assumption is that the main objective of science and technology is to help solve the biggest challenges faced by humans, to name a few; climate change, cancer, incompetent rulers, etc. The objective is not necessarily the creation of maximum economic value (the two are not mutually exclusive in theory at least). The movement of science and technology is towards the shores of artificial intelligence (AI) coupled with the hope that it might unlock some of the biggest mysteries of our world. We can all agree that there is a lot of hype about AI.

Recruitment is a prime candidate for automation through artificial intelligence and machine learning, but what does this mean for the human side of hiring? The manual nature of many hiring processes has seen the recruitment sector jump to the front of the HR queue in terms of adopting artificial intelligence. Predictive recruitment analytics: are you ready for the future? Even though the market is still immature and uptake is at the earliest of stages, machine-learning software is making its presence felt. But how significant an impact is it likely to have on HR and recruitment over the next few years?

Yet most of the concerns about the rise of the robots are centered on distributional concerns. The robots might boost productivity growth and therefore the growth of economic output, but will they displace large swaths of workers? This first fear--that robots will massively displace labor across manufacturing and services industries--is a concern because in the future additional capital investment in all manner of robots may well supplant labor rather than supplement it. If robots can essentially replace a large chunk of labor, then businesses will stop hiring workers and instead replace them with robots. Imagine an economy-wide version of robots on factory floors.

On the one hand, it makes perfect sense why the Japanese tech conglomerate SoftBank would want to buy ARM Holdings, the chip designer that pretty much owns the mobile market. SoftBank offered 17 a share in cash for ARM (about 32 billion). That was 43% more than ARM's closing share price on Friday and 41% more than ARM's all-time-high closing share price. This could be the largest-ever tech acquisition of a European company. ARM helped propel the mobile device market forward by crafting designs for low-power microchips.

Fenwick & West was founded in 1972 in the heart of Silicon Valley--before "Silicon Valley" existed--by four visionary lawyers who left a top-tier New York law firm to pursue their shared belief that technology would revolutionize the business world and to pioneer the legal work for those technological innovations. In order to be most effective, they decided they needed to move to a location close to primary research and technology development. These four attorneys opened their first office in downtown Palo Alto, and Fenwick became one of the first technology law firms in the world.

Thanks to its ability to draw insights from huge and complex data sets at great speed, artificial intelligence (AI) is making the previously obscure into something measurable. It also offers the opportunity to create new experiences for consumers. But what does this mean in practice for marketers? Big data is nothing without equally big intelligence – that's true for people and for machines. It doesn't matter how much you know when you can't systematise and apply that knowledge to achieve something useful.

People respond differently to automated beings. Take my group of friends, for instance... The other day, while browsing online, I came across this clip of a robotic dog. When I shared it with the room, not everyone responded in the same way. Some felt sorry for Spot and sprang to its defence during the kicking episode, some thought it verged on creepy, while others were sceptical of its practical uses.

Artificial intelligence is hot, but also daunting. The latest advances -- known variously as cognitive computing, machine learning, and deep learning -- sound complicated and expensive. And they are, despite the enormous potential they bring to the marketplace. For many companies, the price tag and the commitment of resources are too high a hurdle. And for other reasons, even a giant like Apple is facing challenges.

Many brands these days count personalization as a top priority in customer experience. Customers value their time and look for efficiency, yet they still want experiences tailored to their needs. Automated service delivered through such technologies as IVR and click-to-chat buttons can ensure efficiency, and the prospect of connecting to an agent provides the human touch that customers continue to seek. Yet such practices may soon become a thing of the past with the emergence of chat bots, a power tool for brands that just may deliver the best of both automation and personalization accented by a human touch. Chat bots, defined simply, are a kind of service that people can interact with through a chat interface using textual or audio means. They possess an intelligence capability, such as the kind used in virtual assistant or live chat programs, and provide accurate answers through an artificial intelligence function.