As we get close to Q4 in 2016 and the release of Gartner’s Top Ten Tech Trends for 2017, I thought it’d be good to take a look back at what they predicted for 2016 to refresh our memories plus share a few articles from the world this week. First, the news:
Uber is now letting riders experience their autonomous cars in Pittsburg. This article highlights what the experience is like – while the writer felt safe for most of his drive, he was glad he could override the technology a couple of times as well. It’s pretty cool to see the technology being leveraged, including LiDar on every vehicle.
The income and poverty report for 2015 came out this week, and good news: we’re as rich as we were in 1998. Aside from the cheeky and insightful analysis from the New Yorker, there is good news in the report, although tempered. I’ve not had a chance to finish it yet, but you can find the entire thing here if you’d like to dig in.
I, apparently, need to get a job with Wells Fargo … well, no, I don’t because I missed the window to cash in on a $124M bonus package for defrauding customers, costing the company a nearly $200m fine.
Microsoft beat Facebook in, of all places, Github with open source code submissions. Why is that a big deal? Well, this is the company that, under Gates and Ballmer, tried their hardest convince CIOs that open source was rife with issues. Well, under Nadella that has changed.
There are two articles worth a look this week from HBR: to succeed in tech, women need more visibility and how cybersecurity is every executive’s job. Definitely take the time to read the first article, as it points to an ongoing epidemic of sorts for tech companies: the highest-profile losses in tech are those at the senior level. Women at these levels “often are less satisfied with their careers, perceive that they are unlikely to advance at their current organizations, or believe they must change jobs in order to reach the next level.”
A round up of some Apple articles for the week: first, I’ve downloaded iOS 10 and between the price of the 7 for lack of innovation and some of the “features” of that new OS, it might be enough to push me off the platform, but at least I was able to get it to install. Next, apparently the “boys” of 1 Infinite Loop are rethinking autonomous cars. I used quotes there because then there’s this piece on leaked emails that shows how Apple is still a sexist and toxic workplace for women. There are a few others, including how Apple will leverage ear buds to make Siri smarter, that the age of Apple is over, and what’s next for Apple now that smartphone sales continue to decline, much less stratechery’s look at beyond the iPhone. But I feel like I buried the lead there – Cook may be much admired, but there’s critical work to be done at Apple to get rid of the “bro” culture that we thought was only an epidemic as Unicorns.
There’s a good piece this week about the state of computer science education in the United States. While it’s important to look at how primary education is filling the pipeline of secondary education in computer science (and, thereby, industry), we also need to face the reality that we’re moving towards a degree-less future in development in part and figure out how to enable future success without straddling another generation with unnecessary debt.
Tesla and Elon Musk have been in the news of late (what with the acquisition of Solar City). Curious about the future of the company? Check it out here. Hint: we’re back to autonomous cars.
For those afraid of AI, Venture Beat has an opinion piece this week about how it can actually save us from future stock market failures.
Now for Gartner:
Gartner defines a strategic technology trend as one with the potential for significant impact on the organization. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization’s long-term plans, programs and initiatives.
The top 10 strategic technology trends for 2016 are the device mesh, ambient user experience, 3D printing materials (hmmm), information of everything, advanced machine learning, autonomous agents and things, adaptive security architecture, advances system architecture, mesh app and service architecture, and IoT platforms
The Device Mesh
The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses. The device mesh includes mobile devices, wearable, consumer and home electronic devices, automotive devices and environmental devices — such as sensors in the Internet of Things (IoT).
While devices are increasingly connected to back-end systems through various networks, they have often operated in isolation from one another. As the device mesh evolves, we expect connection models to expand and greater cooperative interaction between devices to emerge.
Ambient User Experience
The device mesh creates the foundation for a new continuous and ambient user experience. Immersive environments delivering augmented and virtual reality hold significant potential but are only one aspect of the experience. The ambient user experience preserves continuity across boundaries of device mesh, time and space. The experience seamlessly flows across a shifting set of devices and interaction channels blending physical, virtual and electronic environment as the user moves from one place to another.
3D Printing Materials
Advances in 3D printing have already enabled 3D printing to use a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceuticals and biological materials. These innovations are driving user demand, as the practical applications for 3D printers expand to more sectors, including aerospace, medical, automotive, energy and the military. The growing range of 3D-printable materials will drive a compound annual growth rate of 64.1 percent for enterprise 3D-printer shipments through 2019. These advances will necessitate a rethinking of assembly line and supply chain processes to exploit 3D printing.
Information of Everything
Everything in the digital mesh produces, uses and transmits information. This information goes beyond textual, audio and video information to include sensory and contextual information. Information of everything addresses this influx with strategies and technologies to link data from all these different data sources. Information has always existed everywhere but has often been isolated, incomplete, unavailable or unintelligible. Advances in semantic tools such as graph databases as well as other emerging data classification and information analysis techniques will bring meaning to the often chaotic deluge of information.
Advanced Machine Learning
In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend.
DNNs (an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear “intelligent.” DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.
Autonomous Agents and Things
Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. While advances in physical smart machines such as robots get a great deal of attention, the software-based smart machines have a more near-term and broader impact. VPAs such as Google Now, Microsoft’s Cortana and Apple’s Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.
Adaptive Security Architecture
The complexities of digital business and the algorithmic economy combined with an emerging “hacker industry” significantly increase the threat surface for an organization. Relying on perimeter defense and rule-based security is inadequate, especially as organizations exploit more cloud-based services and open APIs for customers and partners to integrate with their systems. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfill the adaptive security architecture.
Advanced System Architecture
The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. Providing this required boost are high-powered and ultraefficient neuromorphic architectures. Fueled by field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic architectures, there are significant gains to this architecture, such as being able to run at speeds of greater than a teraflop with high-energy efficiency.
Mesh App and Service Architecture
Monolithic, linear application designs (e.g., the three-tier architecture) are giving way to a more loosely coupled integrative approach: the apps and services architecture. Enabled by software-defined application services, this new approach enables Web-scale performance, flexibility and agility. Microservice architecture is an emerging pattern for building distributed applications that support agile delivery and scalable deployment, both on-premises and in the cloud. Containers are emerging as a critical technology for enabling agile development and microservice architectures. Bringing mobile and IoT elements into the app and service architecture creates a comprehensive model to address back-end cloud scalability and front-end device mesh experiences. Application teams must create new modern architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible and dynamic user experiences that span the digital mesh.
Internet of Things Platforms
IoT platforms complement the mesh app and service architecture. The management, security, integration and other technologies and standards of the IoT platform are the base set of capabilities for building, managing and securing elements in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital mesh and ambient user experience and the emerging and dynamic world of IoT platforms is what makes them possible.
I was in the midst of a conversation with a colleague yesterday when we both noticed an ant on the wall next to us. We both watched it for a few moments before I “helped” it to the ground so it could get where it was going faster. It reminded me of this TED talk by Deborah Gordon where she explores how ant life provides a useful model for learning about many other topics, including disease, technology, and the human brain.