As an IBM futurist and influencer, I was honored to be part of the World of Watson event (#ibmwow) two months ago in Vegas. Since then, one presentation has been rambling around my soul and my brain. Shannon Vallor, is Chair of the Department of Philosophy at Santa Clara University, and author of Technology and the Virtues. She gave a brilliant talk on AI, Ethics and the Future of Human Flourishing. She pinpointed why AI raises ethical questions we must answer, and conversations we must have.

The report is lengthy but interesting reading. According to Deloitte's Technology, Media and Telecommunications predictions, more than 300m smartphones – or more than one-fifth of phones sold globally in 2017 – will come with machine learning capabilities. But in addition to smartphones, other mobile devices will be able to perform machine learning tasks even without connectivity. Machine learning capabilities are forecast to arrive in tens of millions of drones, tablets, cars, VR or AR devices, medical tools, internet of things (IoT) devices and unforeseen new technologies. As well as the evolution of machine learning, Deloitte predicts that by the end of 2018, spending on IT as a Service (ITaaS) for data centres, software and services will reach in excess of €520bn worldwide, up from €344bn in 2016.

AI developers are making amazing advances. Witness the excitement around AI's progress in search, cancer diagnosis, genomic medicine, autonomous vehicles, Go, smart homes, machine translation, and even lip reading. Progress in such complex problems raises hopes for the development of general-purpose AI that can be deployed in a wide range of intelligent, open-ended interactions with people like computer interface, customer service, planning and advice. It is easy to imagine an enhanced Apple Siri, Amazon Alexa or IBM Watson that engages in conversations with people to answer questions, fulfill commands and even anticipate needs. In fact, unless you watch marketing videos with a very critical eye (like the latest one for Alexa shown below), you might even believe that AI has already reached this point.

How Does Machine Learning Work? One of the hottest trends in the technology sector right now is called machine learning.

Back in October 2015, Google announced that a new system, named RankBrain, will become an integral part of their search engine. The story was first presented in a Bloomberg article. RankBrain is one of the newest additions to Google's algorithm (but not an algorithmic update). It represents a machine learning system that should help Google understand search queries better. So far, Google has provided us with very limited information regarding RankBrain. Due to this fact, we have been left with a lot of room for speculation. Here are some facts and presumptions when it comes to this revolutionary system. This is a machine learning system that should provide users more relevant results to their queries. RankBrain is an automated system that is able to learn by itself without any human interference. Furthermore, a great thing about it is that it can learn from its mistakes and continuously improve its results. Have in mind that this wasn't Google's first project involving machine learning. Google news is based on the same concept.

In yet another episode of man versus machine, an artificial intelligence developed by Carnegie Mellon University has been absolutely dismantling a team of professional poker players, accumulating a staggering lead of almost $800,000. The showdown takes place as part of the "Brains vs. Artificial Intelligence" competition which pits a group of four poker pros against the crafty supercomputer Libratus in a heads-up game of No-Limit Texas Hold'em slated to continue for 120,000 hands. Gary Vaynerchuk was so impressed with TNW Conference 2016 he paused mid-talk to applaud us. Since January 11 when the contest initially kicked off, the players have now passed the midway point of the the race, having completed almost 65,000 hands in total. What is more intriguing is that so far Libratus has managed to keep an impressive lead over its human opponents, stacking up a profit of $794,392.

Zweben: As these large technology companies had all the compute power and data streams, it is not surprising that the current momentum for AI started there. But the availability of abundant, affordable compute power in the cloud, and free and open source software for big data and machine learning means that AI is quickly spreading beyond these companies. I think that soon the major constraint will be the ability of companies to attract the talent to work on all the projects they want to undertake.

The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises. A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.

Mark Zuckerberg and Priscilla Chan's $45 billion philanthropy organization is making its first acquisition in order to make it easier for scientists to search, read and tie together more than 26 million science research papers. The Chan Zuckerberg Initiative is acquiring Meta, an AI-powered research search engine startup, and will make its tool free to all in a few months after enhancing the product. Meta could help scientists find the latest papers related to their own projects, while assisting funding organizations to collaborate with researchers and identify high-potential areas for investment or impact. What's special about Meta is that its AI recognizes authors and citations between papers so it can surface the most important research instead of just what has the best SEO. It also provides free full-text access to 18,000 journals and literature sources. Meta co-founder and CEO Sam Molyneux writes that "Going forward, our intent is not to profit from Meta's data and capabilities; instead we aim to ensure they get to those who need them most, across sectors and as quickly as possible, for the benefit of the world."

As people increasingly leverage technology to mediate their lives, from music to news, dating prospects to social feeds, artificial intelligence is quickly becoming the backbone for our future experiences and decision-making. Will this improve our lives or will we soon live in a homogenized world, where chance, error, diversity and serendipity are overridden by algorithms? We'll leverage real-life scenarios and examples from Facebook, Pandora and StarCraft to discuss ways developers are addressing these concerns, and discuss how (and if) we can help humanity avoid the "suburbanization of the mind."