Many of you may be vacationing. I would like to share my good wishes with all of you for a safe and relaxing holiday. Hopefully, we will get to meet on 11 – 12 October, 2021, when we plan to hold an in-person conference in Europe.
Working from home over the last year-and-a-half has given me a new-found respect for technology while throwing new light on the value of hardware. Be it a computer, a laptop, or a phone, each piece of primary and ancillary hardware, which is taken for granted in office, now has pride of place at home. Hardware, I have come to realise, is the underdog of the technology revolution. How does hardware augment our capability and intelligence? With AI, is it at all possible to define the limits of capability? With devices becoming so small, how does distributed computing power them so efficiently? Is it architecture or pure technology? How does computation and data storage come closer to the sources of data? These questions egged my interest in edge computing – the topology and location- sensitive form of distributed computing.
Media attention on edge computing is focused on expectations of improved response times and savings on bandwidth. I must admit, the first time I read about edge computing I wrongly assumed it was synonymous with IoT (may be the reverse, in hindsight!). Since then, a transaction has alerted me to the impressive scope of this distributed computing paradigm.
Like many aspects of technology, this client-server model of AI delivery has become commonplace through the COVID-imposed lockdowns. Our TV viewing schedule is predicated by the recommendations of smart engines. Our social media engagement could not be complete without the smart tagging and face/object recognition in our photo library. And the voice assistant devices make every interaction a breeze. Our hardware relies on data being uploaded to central servers, then being processed, and results being relayed back to it.
Now, let’s turn to connectivity. In my home and its neighbourhood on the outskirts of Bangalore, connectivity is an issue. Unforeseen disruption in phone and WiFi signals put stress on internet connectivity, impeding its utility.
This is where the new silicon design of edge computing plays its part in accelerating AI adoption. Multi-core systems featuring both high and low power cores are what AI is increasingly relying on to deliver optimal performance. Not just me in the suburbs, but several industries, like agriculture, which were beyond the reach of AI due to the lack of connectivity, may now be well served by edge computing. Suddenly, edge devices provide swift reach to industries that were not so far served by AI, offering dramatic and wide-ranging advantages.
Of course, for industries not exposed to AI, this enhanced level of data collection will need training and education in its uses and care. It is not just fear of the unknown that needs to be considered, but also the real fear of a potential data breach. There is no questioning that security of data being vital, the processes and procedures for accessing and evaluating data will need to be formulated and followed.
It would be interesting to hear feedback on the introduction of edge computing in various sectors across the world, and how it is changing work, employment, and other related factors. Put anecdotally – are you seeing businesses living life on the edge? Do share your edge(y) experiences. Your views may help others prepare and plan for changes effectively.
When you join the 2 September, 2021, Virtual Round Tables (VRT), do share your thoughts on edge computing during the networking breaks. I look forward to hearing your views on this exciting technology on hardware and AI adoption.
Till we meet virtually, for the VRT on September 2, and later at our in-person Section Conference on October 11 and 12, 2021.
Chair, IBA Technology Law Committee