Bots and virtual assistants are here to help us with everyday tasks, but because they are scattered across networks and devices, their usefulness remains limited. Now a new product from the developers behind Apple's Siri is looking to connect them and create the world's first virtual assistant marketplace. In Viv's first live demo, Dag Kittlaus demonstrated Viv working across the apps of their "friends" at Weather Underground, Venmo, ProFlowers, Hotels.com and Uber while onstage at TechCrunch Disrupt NY, the annual tech conference held this year in Brooklyn. "I just did four transactions in about two minutes, by talking," Kittlaus said simply after completing the demo. "What I just showed you is a small slice of where we see it headed. For developers, this is going to be the next big marketplace, the marketplace that works with the next generation of devices."

We are continuing to announce the speakers for Data Day Seattle 2016. We have 20 more speakers yet to announce. Check back regularly for updates. If you wish to speak at Data Day Seattle, there is still time to submit a proposal. John Akred is the Founder and CTO of Silicon Valley Data Science. In the business world, John Akred likes to help organizations become more data driven. He has over 15 years of experience in machine learning, predictive modeling, and analytical system architecture. His focus is on the intersection of data science tools and techniques; data transport, processing and storage technologies; and the data management strategy and practices that can unlock data driven capabilities for an organization. A frequent speaker at the O'Reilly Strata Conferences, John is host of the perennially popular workshop: Building A Data Platform.

As we age, we feel we've acquired wisdom from life's varied experiences. Machine learning is a form of artificial intelligence designed to recognize patterns that escape our attention. IBM Watson is assisting Swiss Re by enhancing understanding of potential loss exposures. Chubb 4D, a cognitive computing system, can discern possible fraudulent activities by third parties and identify factors affecting claims severity. Machine learning offers the means for insurance carriers and brokerages to augment the knowledge needed to make sharp underwriting, claims management, customer service and other profit-making decisions.

The Smart Data Online Conference will bring together the insights and training that are helpful in navigating new technologies shared across data management topics such as machine learning, cognitive computing, and artificial intelligence to name a few. It is in this event that we can connect you, the attendee, with the speakers who are working successfully with these new technologies in their daily positions.

As algorithm, machine learning and of course big data are more and more making the headlines and considering that we are inherently very much into what will be the next revolution, we wanted to gather our best readings on these hot topics right here. Our "Algorithm Weekly" will allow you to have an overview of what happened in the world of algorithms this week. To do so, we will pick the 5 best links from our Deep Algo Twitter account (feel free to join us now if you cannot wait for our Friday digest to come). Let's start with this week' selection: a first issue about human emotions, the future of publishing, a potentially deprecated UK banking application and science against poverty. Three developers have created an algorithm able to read human emotions with 99% accuracy.

In partnering with Knorr, we developed an online insights tool which helps consumers understand more about their personal flavour profile and provide them with tailored recipe recommendations. As Knorr already has over 178 years' worth of experience in the art of flavour, cognitive technology was the best fit to leverage this understanding, to identify the complex connection between flavour, our taste preferences and recipes. Interestingly, the cognitive technology that is behind the Knorr Flavour Profiler was recently designed at the Network and Information Sciences International Technology Alliance (ITA). The Cognitive Era is the next step in the application of science to understand nature and improve the human condition.

Singletons looking for love online often boil down their basic criteria to age, sex and location. But perhaps the first question they should be asking is what flavours they like. After all, our taste preferences are far more complex and individual to us, than a mere geographical location or number. The ability to analyse our individual taste preferences, match these with flavour and identifying recipes that suit our personal palate is actually a very complex problem to navigate. This is exactly what Knorr, Unilever's largest brand, has done with the launch of the Knorr Flavour Profiler.

Digital technologies can do more and more things better than us, by processing increasing amounts of data and improving their performance by analysing their own output as input for the next operations. AlphaGo, the computer program developed by Google DeepMind, won the boardgame Go against the world's best player because it could use a database of around 30 million moves and play thousands of games against itself, 'learning' how to improve its performance. It is like a two-knife system that can sharpen itself. That any apocalyptic vision of AI can be disregarded. The serious risk is not the appearance of some ultraintelligence, but that we might misuse our digital technologies, to the detriment of a large percentage of humanity and the whole planet.

This post is a discussion of Nick Bostrom's book "Superintelligence". The book has had an effect on the thinking of many of the world's thought leaders. In that light, and given this series of blog posts is about the "Future of AI", it seemed important to read the book and discuss his ideas. In an ideal world, this post would certainly have contained more summaries of the books arguments and perhaps a later update will improve on that aspect. For the moment the review focuses on counter-arguments and perceived omissions (the post already got too long with just covering those). Bostrom considers various routes we have to forming intelligent machines and what the possible outcomes might be from developing such technologies. He is a professor of philosophy but has an impressive array of background degrees in areas such as mathematics, logic, philosophy and computational neuroscience. So let's start at the beginning and put the book in context by trying to understand what is meant by the term "superintelligence" In common with many contributions to the debate on artificial intelligence, Bostrom never defines what he means by intelligence. Obviously, this can be problematic. On the other hand, superintelligence is defined as outperforming humans in every intelligent capability that they express. Personally, I've developed the following definition of intelligence: "Use of information to take decisions which save energy". Here by information I might mean data or facts or rules, and by saving energy I mean saving'free' energy.1 However, accepting Bostrom's lack of definition of intelligence (and perhaps taking note of my own), we can still consider the routes to superintelligence Bostrom proposes.

Over the past several years, Riot Games, which produces the immensely popular League of Legends, has been experimenting with artificial intelligence (AI) and predictive analytics tools to find the online trolls and make their games more sportsmanlike. "We used to think that online gaming and toxic behavior went hand in hand," explains Jeffrey Lin, lead game designer of social systems at Riot Games. "First, put the tools in the hands of the community and second, build machine learning systems that leverage the scale of data--contributed from the community through reports--to combat the problem." To learn how Big Data, automation and artificial intelligence will shape the future, download the HPE white paper "Big Data in 2016."