Don’t believe the hype (cycle) – part 3

Following on from part 1 (AI everywhere) and part 2 (Transparently Immersive Experiences) in this series, it’s time to take a look at the remaining group of technologies in the 2017 Gartner Hype Cycle – “Digital Platforms”.

This catch all includes several game-changers, such as:

5G
(maybe 10x faster than 4G, and much more reliable)

Digital Twin (digital replicas of physical assets, processes and systems, providing people with more powerful monitoring, analytical, and predictive capabilities)

Edge Computing (data processing at the edge of the network, such as on people’s laptops)

Blockchain (“federated ledgers” – devices allowing decentralised management of transactions. Not just crypto currency!)

IoT Platforms (joins the dots between IoT devices)

Neuromorphic Hardware (an AI chip that can operate on your personal device)

Quantum Computing (next level computing speeds)

Serverless PaaS (bit of a misnomer – you still need servers, but less work is required to optimise them for demand)

Software-Defined Security (reducing the human intervention in security)

And here’s where they all sit on the cycle:

Emerging-Technology-Hype-Cycle-for-2017_Infographic_R6A-1024x866-1.jpg

Picking through that list, it’s interesting how almost all of them represent incremental improvements over what we’ve already got.

Some appear on the surface to simply help us do what we can already do, but more quickly or more effectively.

Others are still very much in R&D (Quantum Computing), with the true value and implications of these technologies difficult to understand. For example the security implications of Quantum Computing is likely to be quite asounding, and not in a positive way. What the value of Quantum Computing will be for everyday people is hard to fathom, it’s an exponential change in processing power, and it’s very hard for humans to think in terms of exponentials.

Admittedly many of these improvements will be exponential in nature, and there’s no denying that they’ll have a impact far greater than we can imagine.

Here at Bilue we focus on building “inspired experiences on intelligent platforms”, and so we take the time to consider these emerging technologies alongside some which we use already – think Google Actions, Apple HealthKit, Amazon Web Services and the like. What’s interesting for us is that the barriers to participation for these existing platforms are incredibly low. At the risk of blowing our trumpet, our talented iOS and Android developers have no trouble turning their hand to Apple HealthKit, Google Actions, TensorFlow or AWS Lambda. So when we look at this list, we wonder both how easy they’ll be to put to use, and when they’re likely to be ready for production.

It’s also interesting to think about how some of these platforms might be combined to create new value as they become available. For example, we’re willing to bet that the current usage of IoT devices is trivial compared to where we’re going. Connected sensors sitting on an Intelligent IoT platform would be revolutionised with Neuromorphic hardware, with distributed, contextually aware intelligence creating something more akin to Skynet than turning lights bulbs on and off. It’s no surprise that we’re observing a doubling down on ethical AI; with Elon Musk already making great strides in this area, and a lot more work to come.

So…onto Blockchain. A good place to finish as this is arguably the buzziest technology on the whole hype cycle, and it’s remarkable that it hasn’t really captured the public imagination yet. The obvious reason is that it isn’t the easiest concept to grasp – the notion of a secure, de-centralised, distributed ledger is sufficiently unique to resist simple comparisons. Over simplified explanations might be doing more harm than good (we think this explanation from Business Insider is a decent starting point, and there’s enough opportunity that Gartner has developed its own readiness tool). Nevertheless, there’s enough activity in this space to claim that we’re past the tipping point, with an eye-popping $100 billion and climbing tied up in cryptocurrency managed without banks involved. The genie isn’t going back in the bottle.

Given that most of the Blockchain buzz has focused on crypto-currencies such as Bitcoin and Ethereum, newcomers might be forgiven for thinking this is Blockchains sole purpose. But the utility of Blockchain goes much further than this. For example, in this Huffington Post article they’ve highlighted five other uses including contract management, digital identity, cloud storage, digital voting and timestamped notaries. One of our clients is using it for agricultural exchanges, to reduce the time between providing grain and getting paid for it (long and complex supply chain). A vast number of start ups are starting to leverage this technology, and the possibilities are endless. Well worth staying close to, and we would argue that Blockchain is past the trough of disillusion, well beyond where they’ve placed it on the graph.

That concludes our assessment of the technologies on the 2017 hype cycle! We hope you’ve enjoyed reading it as much as we’ve enjoyed writing it. If you want to have a chat about any of the technologies on the hype cycle and how they could help you to grow your business, please feel free to get in touch. And if you disagree with our assessment, feel free to add your comments below – we love a good debate!

Don’t believe the hype (cycle) – part 2

 

Following on from the previous assessment of the Gartner hype cycle technologies falling under the AI everywhere banner, it’s time to look at the second batch of trends – “Transparently Immersive Experiences”. This category has a number of distinct technologies shoehorned under it – AR / VR, Connected homes and Nanotube electronics, not to mention Brain-Computer Interfaces, 4D printing and more.

Let’s take another quick glance at the hype cycle to see where these technologies sit:

Emerging-Technology-Hype-Cycle-for-2017_Infographic_R6A-1024x866-1.jpg

It’s a solid eight years since the UX community coined the phrase “the best interface is no interface”, and it’s taking a while for reality to catch up with the sentiment. While technology continues to get cheaper and lighter, we’re still a fair distance from being able to wear something comfortably for any length of time. But therein lies an interesting thought…as with Machine Learning in last week’s post, we have to ask; what constitutes success? Widespread, mainstream appeal of VR / AR is a long way off (read this BBC audience research if you’re in any doubt), but there’s still high potential for the technology to be very successful in narrow use cases in the near term. For example, we’re excited about Google Glass Enterprise Edition – you wouldn’t want to be the glasshole wearing one in a bar, but the benefits are obvious for someone needing to do their job hands-free, such as a surgeon, a mechanic or a field services worker – especially as it’s much lighter than, say, an Oculus Rift VR headset (36 grams vs 470 grams). And on the software side, Apple’s release of ARKit in iOS11 firmly marks Apple’s intention in the Augmented Reality market, and some of the work developers have produced to date is nothing short of amazing.

Brain Computer interfaces and Human Augmentation are other matters entirely. If you’ve read Tim Urban’s fascinating Neuralink blog post, you’ll know that the  10+ year timeline for BCI is probably fair. That hasn’t stopped our company founder & CEO Cameron Barrie giving it a good go though.

Connected homes and Virtual Assistants are another matter. Gartner has both those technologies at the “Peak of Inflated Expectations”, with the plateau being 5-10 years out. I’d like to challenge that – surely Google Home, Amazon Alexa and Apple’s HomePod devices qualify, and will be firmly in the mainstream if not this Christmas than next year?

My family has 13 devices connected to our wi-fi, but the Google Home device is the only one in the home automation category. When a couple of lightbulbs sets you back $139 and don’t solve a real problem (turning on a light switch is hard because..?) then I would tend to agree it’s a way off. But with devices such as Wemo mini smart plugs lowering the cost of entry, it’s a great time for the early adopters.

What’s really interesting is that voice assistants will be handing over a lot more power and control to the user and the intermediaries. Let’s say for example that you operate an airline. Right now you would market your product through a sophisticated marketing mix of paid, earned and owned media. But how on earth do you ensure that Google Voice sends business your way when asked about flights to London? A verbal answer isn’t ‘scannable’ in the same way a list of results is – the expectation is that the response will be more tailored and human. We’re expecting answers rather than a list of places where answers might be found. What’s more, everyone in the advertising ecosystem – including Google – will need to come to terms with these new dynamics. I put up with banners because they can easily be ignored, but no-one’s going to listen to an advert while they wait for their search result(s) to be read out.

One set of technologies notable by their absence are those driven by gesture based control. Products such as Leap Motion and Knocki were all the rage at one point, especially at a time when Microsoft Kinect and Nintendo Wii were becoming popular, and the arrival of wearables was expected to drive more of this behaviour. Fair to say this is no longer the case, and in the case of Leap Motion they’ve now firmly hitched their wagon to the VR horse

As a mobility focused company, our perspective is that it’s interesting to see “Transparently Immersive Experiences” being heralded as the next big thing. However, one of the main reasons smartphones have become so popular is that humans interface with them with virtually no movement or fuss. The interface is already very powerful, if not transparent. People can scan large quantities of data very quickly and discreetly, without worrying (too much) about who else is being nosey – it’s much quicker than listening to speech, and much more discreet. It’s great for just about every location you can think of, even under water. Our view is that it’s best to think of these emerging technologies as augmenting and supporting the mobile device rather than replacing it any time soon, at least until Brain Computing Interfaces come online in ~20 years! Time will tell…

Next up: the third and final part, the ultimate catch-all: “Digital platforms”. 

Don’t believe the hype (cycle) – part 1

 

The 2017 Gartner hype cycle is out and, while it should always be taken with a pinch of salt, it’s fun to decide for yourself whether or not you agree with their assessment. Before we get stuck in, it’s worth having a quick read of this interesting analysis of past hype cycles where the author assessed how accurate these predictions had been previously (spoiler: not very). But still; I think we can all agree that technology is moving at an ever increasing pace, which not only makes predictions harder to make with certainty, but also presents increasing opportunities to outflank competitors – or be outflanked.

So with that in mind, let’s take a look at this year’s hype cycle:

Emerging-Technology-Hype-Cycle-for-2017_Infographic_R6A-1024x866.jpg

Interestingly, for the first time Gartner has decided to sub-categorise most of these technologies into three buckets; AI everywhere, Transparently Immersive Experiences, and Digital Platforms. We’re going to tackle each of these over a series of three blog posts, starting today with AI everywhere.

The hype – or, dare we say, hysteria – behind Artificial Intelligence reminds us of the Big Data excitement about a decade ago. Everyone’s talking about it, very few can show results, it’s rarely well defined, and it’s being heralded as the answer to whatever problem you care to mention. This enthusiasm contrasts with a sense of the shine coming off, such as the AI poster child IBM Watson being uncovered as overhyped, and the lack of self-driving cars on the road several years since they were first announced with excitement. Such activity is highly indicative of the trough of disillusionment.

Maybe it’s because we’re early adopters by nature, but our feeling is that quite a few of the AI technologies are even further along the hype cycle than the trough of disillusionment. When we look at virtual assistants, the connected home and machine learning, we can see a positive pattern of widespread experimentation and learning, with the occasional commercial success and the broader pragmatism you’d expect to see on the slope of enlightenment. In any event, take note of the key used in the diagram: “Plateau will be reached in:”. What represents a plateau when it comes to e.g. machine learning? We expect it will fragment significantly for many years to come. Some basic aspects will become mainstream soon, while others will continue to build on these breakthroughs over the next few decades. In any event we feel we’re entitled to a more optimistic outlook than the graph indicates.

The aforementioned analysis of past hype cycles refers to the Gartner hype cycle as “mostly a reflection of industry consensus”, which is fair, but which also masks wildly varying opinion. The typical Creative Director might be quite comfortable inflating expectations around AI as part of a creative idea, but they’re not always around when such an idea needs to be built. In contrast, practitioners such as those at Bilue are already on the slope of enlightenment due to their first hand experience and their ability to better interpret the various success stories, such as with AlphaGo. We mix proven technology (especially e.g. Tensorflow and CoreML) with strategic intent to find utility with a decent prospect of success, rather than encouraging non-technical creatives or business leaders to go wild with ideas that may not be viable.

Our recommendation would be for companies to invest in multiple, small experiments to figure out which of these technologies can generate a return. Typically these might be in a narrow context, such as reducing call centre costs by a modest margin, or helping position your brand as being more innovative, but putting a strategic lens over the opportunity space can improve your strike rate return a stronger ROI.

Phil wrote an introduction to Artificial Intelligence a little over a year ago. The closing paragraph still stands up:

“In the short term…we can start looking for opportunities to exploit AI technologies as they mature and generate new forms of value. It’s important to get an early, solid understanding of how the opportunity can be exploited and, as with the technology waves that came before, a few well-chosen bets may pay off handsomely. She who dares wins, but let the buyer beware.”

Next up: Part 2 – Transparently Immersive Experiences

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