Three technology challenges, trends and predictions for 2017

By Russell Stern | 5 January 2017

In 1999 Apple debuted their famous Tank TV commercial which bragged that the new PowerMac G4 was so powerful it had been banned for US export as a Super Computer. Contrast this to Apple's watch, which today offers similar computational power. Computational density has pretty much tracked Moore's Law since it was coined in 1965, but it’s only been in the past five or so years that the computational density has been capable of addressing some of our biggest technological challenges. With the advent of the smartphone we've seen one glowing example after another of how computational density has finally achieved critical mass.

This year three technology areas have overcome challenges and leapt forward as a direct result of increased processing density. They are dramatically changing the face of how we interact with the world around us. Artificial intelligence (AI) has been "a generation away" since Star Trek debuted on the small screen in the 1960s, today its weaving its way into our everyday lives. Add to that the explosive growth in the Internet of Things (IoT), which has led to little disks sprinkled around our homes that listen to our every word and thermostats that actually know when we're home to intelligently adjust our environment. Finally, we have security, which will benefit from both of the above as it rapidly becomes the second most common pervasive aspect of technology, next to that of computational capability.

AI

In 1968 Arthur C Clarke wrote 2001: A Space Odyssey with a lead character being an AI called HAL, a one letter shift paying homage to IBM. While the technological dominance of IBM in the late 1960s was unquestionable, there have been several periods in the last three decades where the future of the company had been seriously in doubt. It's then somewhat ironic that IBM has defined the field of AI with the introduction of Watson. Five years ago we watched with curiosity as Watson bested the top two human competitors, and at the end of the game we were left wondering what Watson might do next. Well, it's studying human cancer.

IBM’s Watson Health service leverages a machine intelligence platform deployed last year to a dozen cancer centres in the US. Watson has the collective intelligence of more than 20,000 cancer studies, thousands of patients' data, and a wealth of genetics information and insights. Watson "reads" every new paper and study on cancer as it’s published, submits its analysis to humans for review, prior to inclusion in its knowledge base. IBM has outlined over 20 distinct lines of business where they're applying Watson, and they're crafting APIs with the trend being to enable other companies to embed Watson in applications at all levels.

Internet of Things

With this increase in computing density we're now seeing the internet in everything from doorbells to front door locks, smoke detectors to thermostats, and now the personal assistants Google Home, and Amazon Echo. This market is in its infancy as extremely low power networks and silicon are evolving geometrically. Couple this with advanced natural language support, pervasive big data, and the possibilities are unlimited. Today we often interact with some of these devices using an application on our smartphones. Soon they will communicate with each other using ZigBee or near field communication (NFC). As these products interact with us they'll record these interactions looking for patterns and begin to apply predictive analysis to better deliver services to us in the future. Security is the final concern as these products proliferate they'll need secure methods to authenticate and communicate with each other and the internet. As we've seen recently with the Dyn DDoS attack, poorly managed IoT security can quickly lead to millions of pawned devices. 

Security

Security is quickly becoming a common thread through all technology solutions previously discussed. As we've seen in recent DEF CON shows the automotive Control Area Network (CAN) bus assumes all devices on it are trusted. A hacker need only compromise a single system on the CAN bus, and once in they often jump from system to system in an effort to control any system within the car. Earlier this year a study showed that only 14% of banks can detect credit card fraud in real time. That's why IBM acquired IRIS Analytics, a leader in this market with a rea- time fraud analytics detection engine. IBM plans on rolling IRIS's models into their existing counter fraud technology. Last month, Symantec agreed to acquire LifeLock for $2.3bn to expand their reach into the consumer security market. The point here is that security still represents a green field, and a major land grab is still underway.

So when it comes to predictions look for the application of AI in nearly everything moving forward from children's toys to that self-driving truck next to you on the highway. While AI worms its way into everything, those designing products are becoming more familiar with the concept of exposed attack surface, and crafting their products and processes to protect their customers. This leaves the Internet of Everything. We should expect to see smart clothing designed to facilitate powering an networking our devices, monitor and share our health data, and provide enhanced digital an personal security.

Russell Stern, president & CEO, Solarflare