Many of you probably know that I have my own bot -- but one of the more useful features of my bot is its ability to field private messages on my behalf. These messages get sent to me via Messenger, and I respond from within that context. Unlike email which I can and tend to put off indefinitely (sorry!), messages that I receive via MessinaBot stack up quickly, and therefore need to be addressed serially, as they're received. This forces me to respond in a relatively timely and brief fashion. Sometimes though, I get tougher questions that require a bit more thought. Given the frequency of questions that I receive related to bots, I asked Anne Cathrine Saarem whether she'd mind if I published my responses to her questions publicly.

In the climactic reveal of Interstellar, NASA pilot Joseph Cooper is sucked towards the singularity of a black hole. He falls into rows upon columns of unending prisms of bookshelves. Much book-thumping ensues and Cooper is able to communicate with his daughter across time, sending her precious data that saves the day. What's mind-bendingly fascinating about the bookshelf'place' (a Tesseract), is that it is infinite. A single event that occurs in any one bookshelf creates infinite consequences.

Mobile means that, for the first time, pretty much everyone on earth will have a camera, taking vastly more images than were ever taken on film ('How many pictures?'). This feels like a profound change on a par with, say, the transistor radio making music ubiquitous. Then, the image sensor in a phone is more than just a camera that takes pictures - it's also part of new ways of thinking about mobile UIs and services ('Imaging, Snapchat and mobile'), and part of a general shift in what a computer can do ('From mobile first to mobile native'). Meanwhile, image sensors are part of a flood of cheap commodity components coming out of the smartphone supply chain, that enable all kinds of other connected devices - everything from the Amazon Echo and Google Home to an August door lock or Snapchat Spectacles (and of course a botnet of hacked IoT devices). When combined with cloud services and, increasingly, machine learning, these are no longer just cameras or microphones but new endpoints or distribution for services - they're unbundled pieces of apps.

S. Somasegar is a venture partner at Madrona Venture Group and the former head of Microsoft's Developer Division. More posts by this contributor: Escaping the trough of disillusionment for virtual and augmented reality The intelligent app ecosystem (is more than just bots!) How to join the network Daniel Li is an investor with Madrona Venture Group. More posts by this contributor: The intelligent app ecosystem (is more than just bots!) How to join the network You can hardly talk to a technology executive or developer today without talking about artificial intelligence, machine learning or bots. While everyone agrees on the importance of machine learning to their company and industry, few companies have adequate expertise to do what they wanted the technology to do. Here are some insights into what we can expect in the coming years around ML and AI.

Now if these are not dominant steps toward a world of AI I don't know what is. Front this technology with a robot body and it becomes an intelligent being. Google Assistant, Amazon Echo, Apple Siri and the other personal virtual assistants are bringing all daily rituals, habits and requests together via one central point. You want to control the lights, heating, music, TV, or order the shopping, these tools are evolving to allow you to do any of the above firstly from an initial request, but then by learning what your habits are and when you require things. We are surrounded by AI, is it just a matter of time?

Here are a whole bunch of case studies and use cases, as a complete primer for AI in our industry. Predictive analytics allows Netflix to surface and finesse recommendations. This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription. Uniting information from diverse datasets is a common use of AI. Under Armour is one of the many companies to have worked with IBM's Watson.

Last week I attended IBM (IBM) World of Watson as both a speaker and an attendee, and today as I sit in my neighborhood Starbucks (SBUX) thinking about everything, all I can say is WOW! This was one of the most interesting, inspiring and amazing events I have ever attended. And we are still in the very early stages of Watson, Cognitive and AI. I invite you to follow me as I learn more and write more about the wonderful world of Watson, all the companies that work with it and how it will change our industries, our businesses and our lives. As a wireless analyst and columnist, I come at this world of Watson from the wireless, telecom, internet and television angle.

For most people, it is not easy to picture the buying and selling of cognitive capabilities that have traditionally been embedded in humans – things like judgment and decision-making. Yet, thanks to recent advances in machine learning, we face the very real possibility of precisely such a'market for intelligence'. Given the potential of this market to transform the entire global economy, we must all begin preparing – now – for its emergence. To be clear, machine intelligence is still in its infancy, and while some of the current applications are remarkable, none are transformational. For example, the recommendation engines employed by companies such as Amazon and Netflix – which learn our preferences and recommend which books we should buy or which movies we should watch – are a common application of machine learning.

Would you go on a business date at work? Would you think I was weird if I told you I did? Some apps are making this possible, so I decided to try it out. As a family man who has just entered his 40s, I am not going to be arranging romantic liaisons on my smartphone. But maybe I haven't completely missed the boat when it comes to the thrill of swiping, matching and meeting up with strangers. Shapr is an app that works like the dating app Tinder, but it's for making business connections rather than romantic ones.

When the world shifted from desktop to smartphones, one thing didn't change: the existence of a screen on both devices. The screen shrank, but it remained the medium through which we interact with computers. For Google, that meant its core online advertising business -- visible search ads on a webpage -- remained intact and lucrative. Today, Google may be at the beginning of a new shift -- one toward artificially intelligent virtual assistants, in which we use our voice to interact with technology instead of our eyes. The problem with voice assistants is they don't have a screen on which to display ads.