Eye viewing digital information

If you are interested in machine intelligence, you are indeed living in exciting times. The first wave’s recent success stories are widespread knowledge now, such as IBM’s Watson, Google’s self-driving car, and Apple’s Siri.  The next wave looks likely to be more focused applications solving specific issues.

Business interest in machine intelligence continues to pick up as the practical applications become more evident (and achievable).  Many technologies are becoming mainstream, such as ‘Big Data’ tools and Google’s TensorFlow open source machine learning platform.  Some commentators on TensorFlow feel this shows that we are “at the end of the beginning“.

So far, many of the innovations have been experimental, but we are now starting to see the companies behind them mature in how they bring them to market.

What is MI (“Machine Intelligence”)?

We don’t use the “AI” word (Artificial Intelligence) any more.  AI was prominent a few decades ago but went underground when it failed to live up to the science-fiction-dream expectations.  Most people now call it “Machine Intelligence”.  It’s a subtle shift, mainly to remind us that it is still just machines (which don’t always get it ‘right’).

Everyone is possibly thinking of slightly different things when they say “Machine Intelligence”, but generally, they are talking about using algorithms to process data in ways that are intelligent and useful to humans.  The focus has shifted from trying to re-create the human brain to biting off specific tasks that can realistically be automated.

What’s hot?

Shivon Zilis from Bloomberg Beta meets with, and funds, many of the up-and-coming companies working in the machine intelligence ecosystem.  Recently she spent some time slicing-and-dicing the MI landscape in two ways:

  1. where the hot innovations are happening at the moment, and
  2. how those companies are bringing their innovations to market

MI is set to affect more and more industries, so it is worth taking some time to get up to speed, and these two lists are a good starting point to navigate the explosion of MI developments currently underway.

Currently trending are innovations in agents, autonomous systems, enterprise support systems, and industry-specific tools.  We are also seeing more corporates and developers meeting halfway – corporates are working on becoming more MI-literate, and developers are packaging their products to solve specific business issues.

Thanks to Shivon’s efforts, we have a much better understanding of the MI landscape with the following visual she created recently:

What will stick?

Not all of these innovations will succeed, and this will partly depend on how each can transition into a viable business.  The companies are approaching this in a variety of ways, and Shivon looked at those collecting data, mining data, and providing assistance, and categorised them by their level of specialisation:

  • Panopticons – aggregate broad big data
  • Lasers – collate data for particular industries
  • Alchemists – mine corporate data to find gold
  • Gateways – mine external data to find new opportunities
  • Magic Wands – use data and MI to fix a workflow
  • Navigators – use MI to improve real-world situations
  • Agents – use cyborgs and bots to help humans online
  • Pioneers – support intellectual expert developments

There certainly are some amazing things going on in the MI space and these are only the companies and research that are currently known about.  In an evolving market, there can often be the creation of whole new sets of needs, which will continue to propel advancements and focus in many converging areas.  This can make it hard to identify a particular “box” to put a company in.

As I have an interest in MI, I wanted to take a closer look at Shivon’s groupings and the companies in them, so I created a Thought Canvas based on her recent “Machine Intelligence in the real world” article.

Here’s what I came up with (click it to see and explore the live Canvas):

 

The Canvas is quite large so use your mouse to pan (click and drag) around the entire graph.  Click on the circles with an exclamation inside to see what suggested knowledge the contextual intelligence engine running in the background has discovered.

My insight: Amazing MI, but what about the humans?

Creating the above Canvas based on Shivon’s MI article gave me new breadth and depth to dig into the exciting developments in MI.  What’s more, I will continue to use and benefit from this effort, as the context of my Canvas evolves and provides me with new knowledge to investigate.

But, as I explored the related articles, the companies and their focus & offerings, I kept coming back to the same fundamental question:

It is us humans that will create the real value by using, and building on, the output of these new intelligent systems – where is the focus on developing the critical thinking and sense-making skills necessary to do this?

What these companies are doing is amazing.  They are unlocking potential new discoveries for business, health, and the good of the planet.  In life, parents try to help their children reach their full potential.  As the parents and influencers of these MI solutions, what do we need to do to help their discoveries reach their full potential?

Where does our company sit?

When I founded InsightNG, I was in need of a smart, intelligent tool that could help me figure out the right questions to ask and the right people to ask them to, in order to help me understand how I might be able to help my son walk some day.  The result so far is what we call “your smartest friend” – a personalized, intelligent, thinking tool that helps you gain greater clarity and deeper understanding when making important decisions, completing assignments or getting through personal challenges.

InsightNG would seem to be a mixture of “Bot Agent” and “Magic Wand” (from Shivon’s categories).  Our approach is to create a sustainable and valuable relationship between humans and intelligent machines.  On the surface, our platform helps humans find relevant and meaningful information and knowledge.  Extending and augmenting this basic need, it also helps them learn and enhance core 21st Century skills that they will need to discover new actionable insights, evolve their understanding and create value in their lives.

Like so many other companies in the MI space, we too are on a journey.  Into which bucket we are classified as a company in the future of MI, I believe it will depend more on the increasing complexities and interrelating needs of the humans we are helping, rather than the capability of our intelligent technology.

 

About Neil Movold

I am the founder and CEO of InsightNG. I have a career spanning across Canada, Australia, Bermuda and New Zealand. For most of my life, I have been keenly interested in how our human brains function at a cognitive level. When my son Jaden was born with Spina Bifida, my interest in human cognition became more focused, resulting in the creation of InsightNG. My current interests lie in the areas of social learning, open innovation, collective & contextual intelligence, knowledge discovery, findability and content visualization.