I’ve been doing a fair bit of tech strategy work recently and there are three key software tech trends that I’m following closely right now. [And yes, wearables and IoT are up there too, just slightly less interesting. 😉 ]
OK, so the tech industry moved forward leaps and bounds in 2014 – one Magic Leap in particular. This Augmented Reality startup raised an astonishing $US542M round of funding led by Google. The vision is spectacular – and the dynamic light-field display technology behind it is still fuzzy – perhaps we’ll see the early hardware hitting the market in 2018 timeframes? There’s a great round up of the company history on Gizmodo: How Magic Leap Is Secretly Creating a New Alternate Reality – well worth a read.
Also Satya Nadella’s regrouping Microsoft recently took the wraps off their latest AR advance – Hololens – apparently the Minecraft demo is amazing. Good to see Microsoft back innovating again after all this time…
The implications of AR finally fulfilling its promise go right to the heart of the traditional user interface – no longer will productivity applications be restricted by (touch)screens, keyboards and mice – the ability to interact with a full range of information in 3D overlaid real / virtual space has profound implications for how data is organised, presented and manipulated in future. Lots of opportunities, particularly in the Enterprise software market, to meet with the hardware when it arrives.
Another major trend during 2014 was more evidence that Machine Intelligence Will Eat The World. Leading the field is Numenta’s founder Jeff Hawkins who has had a prolific year of presentations during 2014 describing how the Hierarchical Temporal Memory model – based upon reverse-engineering the human neocortex into software – will become the predominant model for Machine Learning and Artificial Intelligence. There’s a fascinating recent GigaOm interview where he likens the current AI research field to the early days of computing – when multiple platforms gave way to a single dominant approach.
He also recently put forward a counterargument The Terminator is Not Coming, The Future Will Thank Us to Nick Bostrom’s more pessimistic outlook in SuperIntelligence: Paths, Dangers, Strategies (Really good read, recommended).
Other notable Machine Intelligence pioneers are a string of AI company acquisitions by Google including Deepmind, a British startup co-led by Kiwi Shane Legg, Vicarious Systems and IBM’s Watson team, now HQ’ed in New York.
US VC Shivon Zilis recently put out a really useful Machine Intelligence industry landscape which is a who’s who of the main players – essential reading for the sector. She is particularly insightful that the time is ripe for MI to provide a whole new class of opportunities for software vendors to add value to their existing product stack:“If I were looking to build a company right now, I’d use this landscape to help figure out what core and supporting technologies I could package into a novel industry application. Everyone likes solving the sexy problems but there are an incredible amount of ‘unsexy’ industry use cases that have massive market opportunities and powerful enabling technologies that are begging to be used for creative applications ” – Shivon Zilis, Investor, Bloomberg Beta
The applications for MI are only just starting to surface – self-driving autonomous cars is perhaps the earliest example showing how this technology will fundamentally disrupt existing economics, business models and lifestyles.
Not only does Machine Intelligence provide a whole new class of medium-term opportunities for software firms – people are starting to openly discuss its fundamental implications for humanity’s future. Enlitic founder Jeremy Howard absolutely nails it in his talk at TEDxBrussels: The Wonderful And Terrifying Implications of Computers That Can Learn – including an absolutely awesome demo of training up an AI to learn car pictures in 2 minutes.
And once again, I’d highly recommend watching Mark Sagar’s demo of BabyX at 2014’s TEDxChristchurch – mindblowing.
Finally, while 2014 was the year that Bitcoin technology went mainstream, people are starting to think about other applications for the underlying Blockchain technology. Basically the blockchain is a public ledger of all transactions in the Bitcoin network – which critically provides trust based upon mathematics rather than human relationships or institutions. There are already a large number of copycat digital currencies – however an early example of the technology’s wider use is Ethereum, a blockchain-technology-based platform and programming language tightly integrated with a new Ether digital currency. Ethereum raised US$12.7M in the Ether pre-sale back in September.
VCs are betting hard on this space – and although the economics of Bitcoin are still being debated, the underlying insight is that ANY financial or business transaction which previously relied upon centralised human institutions to maintain trust can potentially be transformed using a distributed blockchain-derived technology.
So, three major technology trends which will affect any software business looking to keep their product stack current in the medium term. How is your software business planning to capitalize on these opportunities?