2020 has been a landmark year. The pandemic was an unprecedented event affecting (and in some ways bringing together) the entire populace of the world. Suddenly, everyone around the globe has a common topic that was affecting their minds. The usual news of technology advances and innovations were buried under the “breaking” news of the covid-19 onslaught.

But in many ways, I also believe that 2020 will be a landmark year that allowed many, hitherto accepted norms, to be disrupted. WFH became a common parlance. In the past, many things – including data security, intellectual property and accountability – were cited as reasons why people had to come to a place of work, the pandemic suddenly eased up many of these ‘reasons’. And once the shackles are broken, they cannot be easily put back again.

On the technology front too, cloud, big data, IoT, Blockchain, AR/VR etc have been making great strides. But I believe that AI/ML will probably be one of the most disruptive and innovative technologies that will shape the next decade. To be fair, AI/ML has already gained a lot of traction and there are companies that already use AI as a strategic advantage to gain market share. However, just like the iPhone made the phones ubiquitous and android allowed pretty much everyone to have a phone, I believe that AI/ML is waiting for the tipping point to go mainstream. 

In a sense Machine Learning or Artificial Intelligence are enormous tools that not many know how to yield. The challenge is machine learning is not the ability to predict, but the usefulness of the prediction. Prediction by definition is an estimate of something that will happen in the future – which by definition is – as yet – unknown. 

Predictions can usually be accurate if there are scientific rules behind it – which might yet be undiscovered. What goes up must come down – is a great prediction based on the rules of gravity. However, it does not – obviously – apply to spacecraft which foray beyond the earth’s gravitational force. I believe that the challenge is in defining the context in order to improve the outcomes of the prediction. 

As we embark into the new year, I will use this blog to have a conversation around how we can apply AI and ML in real world scenarios to impact things around us.