I’m old enough to have grown up in an era where having a personal Sony Walkman player and grooving to Michael Jackson and Madonna was a fad, and owning an Atari was considered to be a gaming paradise–-yes I admit a fondness towards Mario and the classic shooter games.
Fortunately, I wasn’t too old to learn and adapt when the 386/486/Pentium processors became affordable for mainstream use. I’m still nostalgic about my days in Bombay, when I was surfing websites of US universities on a dial-up modem (a state-of-the-art 28k model no less) and visiting the US Consulate offices to collect paper copies of marketing material for US universities for my selection to pursue an MBA program.
On a quick side note, way back then in the age of the dinosaur, I took a computerized GMAT exam, and the score was delivered in real-time in less than 60 seconds (the most suspenseful 60 seconds of my life). And, in the present day, I’m happy to see that the SAT is finally transitioning to a computerized version in 2023.
I still remember vividly my time as a graduate assistant at Oklahoma State University when I was helping build a neural network model for forecasting the success of box office Hollywood movies–the training data was purchased from a distributor in Los Angeles and shipped via two dozen floppy disks more than two weeks after we purchased through a paper form and paper check payment based process.
Fast forward to today’s world, where machine learning and artificial intelligence are being used for an amazing variety of real-world and real-time use cases–pothole detection, vehicle sensor calibration, financial fraud detection, product recommendation, customer service chatbots, marketing segmentation, document processing, sentiment analysis, next best workflow action, credit decisioning, and so many more.
For the past me, the days of the 386 processor and Windows 3.1, the technological future has arrived and we’re living in it. With the amazing thought that we’re just getting warmed up and the sky is literally the limit on how technology can be used to optimize and automate. A key example of this is Google Cloud’s exploration, commitment, and tagline, “Today, meet tomorrow” to inspire and bring together developers, leaders, builders, and dreamers in a worldwide virtual event such as Google Cloud Next ‘22. The event is packed with keynotes from industry luminaries and engages with Google developers that will explore dynamic content across various learning levels, and dive deep into technologies and solutions spanning the Google Cloud and Google Workspace portfolios.
So I leave this memorial to the past me with one question–what’s the use case that future me would like to automate?