We humans like to think about time in eras. We define styles and trends of the past neatly into decades. We talk about the “Industrial Revolution,” the “turn of the century,” the “21st Century” and the “Information Age.” With the Internet of Things finally becoming a reality, I recently looked back at one description of our next big thing as the “Post-PC Era.”
The term "post PC" was first used by David D. Clark in 1999; considering the future of computing to be "inevitably heterogeneous" and a "network full of services.” Clark described a world where "everything" would be able to connect to the internet (including watches and toasters), computing would primarily be done through information appliances, and data would be stored by centralized hosting services instead of on physical disks. (Wikipedia)
Dave Clark, in 1999, had a long vision for the future that he apparently saw very clearly. When he described a post-PC era in which "everything" would be connected, he was talking about what we now call the Internet of Things.
When we briefly describe Tellient, we say “Analytics for Things,” which is pretty easy for people to understand and a great description of the near-term value of our platform for the companies that know they need IoT analytics for their IoT products. But when we sit down and have a longer discussion about where it all goes in 10 years, it is a much bigger vision. To help get the point across, I have hastily created this accompanying Technology Eras Infographic. It shows the shift in importance of key attributes from the PC era to the Internet Era to the Mobile Era to the IoT Era. It points out the most fundamental shift about to happen: Humans will not be the primary users of technology in the future.
In the PC Era, we humans made machines to help people process work faster than we could with telephones and paper. The key driver was competitiveness, and the biggest problem was that PCs were perenially too slow because the software could evolve at a faster pace than the hardware, demanding ever-increasing resources. The on-ramp to that era was software, and so Microsoft is the winner of that era. The Internet Era, by comparison, was about a giant haystack and people were looking for their needles, so the on-ramp to that era was search and the winner was Google. The Mobile Era was all about helping people communicate, so the on-ramp to that era was your contact list, and as the largest connected contact list on the planet, Facebook got to win that era.
Now we are entering the IoT Era, with its wearable technology, wifi toasters and self-driving cars. Look at it not from the perspective of the humans who will benefit from these advances in technology, but from the machines’ point of view. True, we humans may build the machines, but then we will expect them to get smarter – by themselves. AI, learning algorithms, predictive analytics and a host of other disciplines that all basically mean “the software part of our ‘smart’ devices” will all be applied to optimize the value of the machines we build. We aren’t going to centrally update the firmware of 50 billion devices; we are going to push that function to the edge of the network of these connected devices and let them organically improve themselves. Now, still looking at this from the point of view of a machine that has been told to evolve itself, where do you go? What is your “on-ramp” that enables you to achieve that activity?
A smart, connected machine will evolve itself by assimilating the most useful data and the most successful code from other machines in its peer group with the same purpose. In essence, it will add the DNA of other machines to itself. And how you measure what is the most useful data and the most successful code is a matter of IoT analytics as evidenced by outcomes. Analytics is already known to be important, but in the machine era, to a machine, it is the most important thing. Making the (probably very valuable) market for this DNA requires an IoT analytics platform to collect, analyze, correlate, identify, locate and transact all of the machine data to make it more useful to the machines themselves.
And that’s the long version of our vision for Tellient. Tellient is an analytics platform the way Google is a search engine; that is a very useful aspect of the platform, but the depth of value to our customers is far greater than that.