In a world obsessed with the latest Star Wars blockbuster I wanted to look at how a Sci-Fi concept from many years ago is starting to become a consumer reality and is already part and parcel of today’s technology.

If you have not already guessed, the focus for this blog is how we bring intelligence to devices, specifically the flavours of artificial intelligence (AI) being used and integrated into our daily lives.

These areas of AI are what helped us love the Star Wars characters like R2-D2 and C3P0 giving them both personality and intelligence but also making them very useful companions. Granted they were not without their flaws; C3P0 ever annoying and over excitable vs the intelligence and wit of R2-D2 but limited to beeps and lights for communication.

So exactly how far off are we from having real life useful and intelligent companions with a personality we can love?

The Origins of AI

The concept of AI started a long time ago a galaxy far far away… no sorry getting sidetracked there. Actually, the origins of AI can be traced back as far as Greek mythology, however it was not until we started seeing the first mechanical computers around the 1940’s, that people started to think of the real possibility of one day a machine being able to replicate a person.

Staying on a slightly film orientated topic – last year’s blockbuster The Imitation Game told the story of Alan Turing and his creation used to crack the enigma code. One of the other areas Alan Turing pioneered was called the Turing Test otherwise known as the Imitation Game. This test was designed to identify if an Artificial Intelligence could “think” like a human and when questioned make an independent tester believe the AI was in fact another human.

Over the years since Turing we have seen AI development come and go, with one problem being that AI needs quite powerful computers and just as development gets going the developers run out of computing power. The other main issue was an over simplification of the task required leading to many failed attempts and predictions. Researchers have proved very good at making computers do things that humans find hard but not do things that humans find easy.

Which brings us to today

Today we have two groups of AI’s called Narrow AI and Strong AI. Strong AI attempts to perform general intelligent actions whereas Narrow AI is used to perform specific problem solving tasks.

Narrow AI

There are many examples of Narrow AI that are used globally across just about every industry. There are literally thousands of Narrow AI’s ranging from complex navigation aids like autopilot on an aeroplane to simple spell checkers within your word-processor. One that is found in almost every household with children is computer game AI. Also any approach that uses brute force to achieve a goal would be included in the Narrow AI. Check out the Reddit pages for Artificial and Agi for many more examples.

Strong AI

This where the Turing Test described above comes in and where the debate gets really interesting. From a simple point of view, we now have the power to replicate the human brain when comparing the human brain’s cortical columns (10^7 columns). A single 1GHz CPU would simulate 10,000 cortical columns, so 1THz should in theory do the job. The practical issue is how we emulate the human brain in code to use this CPU power. The word Imitation is key to the Strong AI arguments. There is a big difference between an AI imitating a human intelligence and the AI actually feeling and understanding like a human does.

We have seen some AI’s pass the Turing Test. This in itself is no mean feat, however these AI’s are specifically designed to pass the test – does this make them Narrow AI’s but with a task of being able to hold conversation, or can we really call them Strong AI?

How are the mega corps using AI?

Google, Microsoft and Apple have all thrust AI into our daily lives with integrations into tablets, PC’s, smart phones and other connected devices. These AI’s tend to be combinations of Narrow AI, however when they are combined we really start to see a bridge being created starting to span the gap between the Narrow AI functional focus and Strong AI’s breadth and depth.

None of these AI’s will pass the Turing test but for now I think that’s OK. The AI’s designed to pass the Turing test, whilst very impressive, probably won’t actually help our daily lives. What these AI’s are able to do is carry out some of the monotonous repeatable jobs we could do without, or often forget to do. Adding information automatically to calendars, tracking packages, letting me know “stuff” when I need to know, it may be small steps but the small steps are building momentum. For a while I tried to keep up with the voice commands on my phone but the rate of change is quite fast and I find myself trying things in the hope that it will work rather than checking beforehand.

The more these AI’s are used the more the developers can see and code for in the background, equally the bigger the data sets they are exposed too the more use we will get.

Who’s next after the big 3?

There are many other AI’s being created targeting consumers and this next group is really all about AI in the home. These aim to join together your IoT devices and expand on the same kind of functionality we have on our smartphones. These types of AI are becoming very popular, over Christmas we even had Mark Zuckerberg announcing his intention to build his own home AI.

The one of the first “production” consumer AI’s is the Amazon Echo which uses Alexa (Amazons cloud AI). This is a small home based hub you can use to give voice commands too, one primary feature is that it can recognise voice from across the room (no others do this yet). Hot on its heals is LG’s SmartThinQ Hub which while has what I would say less AI however has a lot of smart connections into the LG range of appliances. If connecting your IoT fridge is high on your agenda….

LG SmartThinQ Amazon Echo

Then we have some other really exciting devices from small start-up’s rather than big recognised brands and are really pushing the innovation and integrations to new levels.

Jibo – the Social Robot.

The Jibo is one of a new breed of AI’s which are focusing on being useful around the home but also having a more personal touch. This is a premium device with a personality and nice set of features. The Jibo OS is not open source but there is an SDK for dev’s. If the demonstrations make it into production this looks like a very neat little AI that would be very cool to have at home.

Mycroft – Open Source AI

This is one to watch, the platform is Raspberry Pi based and is based on being open source. Like the Jibo, this is a hardware platform with a personal touch though quite visibly not as premium. The benefit of this open source (and Raspberry Pi platform) is that it’s quite cheap and there are lots of custom integrations already in work. The open source approach is what really appeals with Mycroft, the mega corps like Amazon, Microsoft and Google don’t always play well together. If you want to build a custom integration to your IoT devices, you can do.

The Game Changer?

The last consumer AI I want to cover comes from one of the most widely used platforms in the world – Facebook. The guys at Facebook have got two streams of AI both integrating into the FB chat application. The first is effectively a very clever way of advertising, let’s face it, making money out of “chat” if executed well will be a huge revenue stream especially when so many people are already on the platform. This new chat capability brings to life fictional characters and enables you to interact with them via the chat interface. The goal is to have your “liked” fictional stars message you about the show or movie (in character) as a way of getting consumers engaged at a whole new level. You can go to Facebook now and have a chat conversation with Miss Piggy from the Muppet show. I hate to admit it, but I actually found our little chat quite entertaining, here is a snippet….

The 2nd area that Facebook is developing (only available in California at the moment) is Facebook M. This sets itself apart from the other AI’s talked about today as it can actually carry out tasks for you. A recent Facebook blog covers the topic – here is the key point.

Unlike other AI-based services in the market, M can actually complete tasks on your behalf. It can purchase items, get gifts delivered to your loved ones, book restaurants, travel arrangements, appointments and way more. David Marcus – Vice President of Messaging Products at Facebook

I have even read about it sorting out disputes with Amazon and ordering breakfast. This is the kind of PA I think anyone could find a use for and it shows a real change in direction from the rest of the pack. The thing Facebook have cracked (at least in the limited beta) is how to handle any request, the secret sauce in all this however is a human.

The human element makes this one of the first hybrid AI’s where some requests are handled by the AI and some are routed to a human operator. The humans in this instance are all previous service desk type operators who bring the human touch to the experience. Over time as requests come in and are answered by humans the AI will be expanded to learn how to process them in the future. This cycle of improvement will drive down the cost of providing the service and increase the ability of the AI which in theory should let it scale up. Add to this the referral / advertising and general moneymaking side of this kind of AI / Personal Assistant and its clear why Facebook are pushing the boundaries. The question is will this innovation be enough to attract people into the Facebook ecosystem. The other vendors have hardware platforms with their AI built in, Facebook need to ensure that Facebook M so good that people download and use it rather than native capabilities.

Final thoughts

Over the last few years consumer AI has come a long way. It is no longer a gimmick rather it’s playing a major part in the strategy of major technology companies across the globe and more importantly, it’s actually becoming useful. Analysts are predicting that this field will overtake many current revenue streams and become even more important, take Gartner’s prediction for Microsoft as an example…

“By 2020, smart agents will facilitate 40% of interactions. Consumers will forget apps. The post app era is coming. By 2020, Microsoft’s strategy will be centred on Cortana instead of Windows.” Gartner

As for Strong AI’s, I can’t see us getting to a consumer version of a Strong AI in the near future so us Star Wars fans will have to wait a bit longer for that R2-D2 clone. However, it will be very interesting to see how the closed code based systems compare to the open source and hybrid systems coming to the market.

Personally, I quite fancy playing with the Amazon Echo and Mycroft systems but out of all these I look forward to what Facebook are doing the most. They seem to be bringing the most innovative changes to a competitive and quickly growing consumer AI landscape.

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