As Dreamforce draws to a close, the annual user super conference hosted by Salesforce put a shining spotlight on both its own technology offerings as well as the near 170,000 attendants. Certainly the scale of Dreamforce is far bigger than how Marc Benioff (Saleforce CEO) refers to it as a family reunion, unless of course we count entire towns as family. The 4-day event featured leading edge technologies, larger than life personalities, powerful humanitarian initiatives, and much more. But what else can we learn from this event?
As traditional media transforms into investigative journalism that digs deep into patterns that were previously only reserved for large journalism outfits with deep pockets (New York Times, Washington Post, Time, Forbes, etc...) Case in point, Business Insider, a relatively recent entrant in the investigative journalism space spends much effort into big data and analytics to dig up smart and salient trends. One such recent insight has focused on following the flow of engineering talent to predict the next wave of innovation. Where this has been keenly kept secret to maintain competitive advantage, the insights observed by talent migrations and their destinations we were able to formulate a thesis of the technologies of the future.
Virtual Reality, Augmented Reality
Certainly that Facebook's Mark Zuckerberg spent nearly $2 billion to acquire Oculus without a marketable product can only mean that the tech giant is betting heavily that this is a technology of the future.
Zuckerberg was quoted saying "we'll have the power to share our full sensory and emotional experience with people whenever we'd like," which makes us wonder whether the application of these technologies could be anything like we've witnessed in Minority Report.
Similar but not quite the same, Augmented Reality overlays virtual 3D graphics onto our view of the real world differs from Virtual Reality, which immerses us in 360 degree views of new worlds with little or no sensory input from the room our body is in. It's easy to imagine the fields of medicine and engineering enhanced by these technologies to achieve high degrees of advancements.
Twilio (2016's top performing tech IPO), Plivo, and Nexmo are but a few of the technology companies enabling developers to integrate telephone and SMS communication functions without needing to build backend infrastructure and interfaces. Traditionally an offline medium, telephony is now at the easy reach of developers and the resulting applications have been tremendous. Contextual communications is one of the biggest drivers of the CPaaS market as companies seek to improve the overall customer experience. Some common applications include: video-enabled help desks, SMS appointment reminders, and authentication services.
Integrating communication within ecommerce has the potential to completely revolutionize brand awareness techniques, customer acquisition and engagement, onboarding, and success journey.
Recent advancements in artificial intelligence and machine learning are enabling the automated understanding of the world in order to respond with calculated decision making. Although more work is needed, artificial intelligence is now a potential reality based on recent breakthroughs. Companies like Google and Facebook are embracing and pioneering these technologies in several forms, but the biggest impact will be when robots, drones and full automation take on a more pronounced role in the field of medicine.
Currently, machine learning is making strong advancements in a few fields:
- Autonomously driven vehicles
- Voice recognition and speech mechanics
- Object recognition in video and images
- Automated learning and decision making
Currently, the biggest impediment to advancement and growth in these fields is the limited number of professional who are capable of contributing. Certainly, that these project are inherently large and complex, as evidenced by Amazon's investment in the development of Echo equaling 1,500 engineers for 4 years, further stunts growth in these areas. However, the future of awe-inspiring technological advancement, based on these technologies, is bright.
These obstacles are surmountable as more computer science graduates come out with the required knowledge.
However, the most significant barrier is that the fuel that drives machine learning, data, is still of very limited supply. Machine learning algorithms require a tremendous amount of data that is currently only available to a handful of organizations worldwide, namely Facebook, Google, Amazon, Microsoft, Apple. The investment in the infrastructure needed to store and effectively analyze the data is high and can require several years before return on investment materializes into profits.
At Telmetrics, we seek to incubate many of these ideas to bring the technologies of the future to the salient present as we believe in the opportunities that they offer. By taking an open and collaborative approach, whereby clients and technology providers work together openly to find win-win solutions, we are able to capitalize on technological advancements of the future sooner. We build what we can and facilitate access to the rest. This is the philosophy that we've adopted long ago when we pioneered call tracking and attribution more than 25 years ago, and we see it continuing to pay off.
Rami Michael, P.Eng.