Nobody should doubt the impact of data science and deep learning on our lives. In the last 15 years, we have been part of a mega Industrial Revolution that scientists call as the largest Human Intelligence Movement of mMankind. There are four major drivers of this revolution. They are:
- AI and Analytics
Take out one of these ingredients, and the whole building or magnificent ‘dream’ of the Future crumbles under its own weight. Out of these, only electricity is the dinosaur in the room, chronologically speaking. But, the other three are technologically so dynamic in nature that we fear that the Sun may blow out of their existence soon- if data becomes irrelevant to us.
The trajectory of how data decays is not that easy to explain or comprehend. But, let’s try putting things in perspective at least by using numbers.
According to a report, 30% of the personal data that you have produced in the last 2 years would have been already lost to phenomenon called ‘web information decay’. What’s that? Your posts from 2012 on Facebook, Twiiter, or Instagram may not make sense to you in 2019. You may not even realize that why you even posted it online! But it’s there, and it’s filling the data storage centers. It risks eating into our present data science capabilities.
Here is a crazy scenario that may happen by 2022.
Surely, the Computers would run on Computer Vision, Edge and Quantum Computing and Neural Networking technologies. So, the computers of 2025 may be much smaller and smarter than what we see today.
AI and Analytics are having a gala time, taking all the investments and funding from the various mega innovators of the world. They are also enjoying the attention of the talent group wanting to join their forces with AI and Analytics projects.
Where we may lose out is DATA. It’s always said that data is perennially susceptible to maximum decay or degradation and it risks losing the sheen with time in front of other crazy developments happening in the Industrial Revolution 5.0.
Winding the clock forward to 2030 –
We have Super-computers that can computer at 1000x the speed of today’s devices. We also have AI and Analytics—but fail to control the loss of data to decay and degradation. If that continues to happen, we are staring at a sure shot black hole situation where the Deep Learning Data Science community would cannibalize itself to sustain its massive infrastructure and network.
And, we can’t let that happen.
You can aim to work for a data processing company that uses Data Science and Deep Learning to safeguard data from becoming obsolete in the future.