For decades, the shift towards Ecommerce has continued steadily across the globe, with growth consistently outpacing (and eating into) bricks and mortar retailing. The COVID pandemic has simply accelerated that shift. Yet many consumer goods companies are still behind the curve in their use of technology. Ella, my 12-year-old daughter, has illustrated this point to me several times during the past year. It begins when she shows me her phone and says, "look daddy, check out this new arts-and-crafts or room decor video on TikTok."

The development of the internet over the last few decades has resulted in a massive increase in the production of data and the unprecedented availability of computing power for corporate applications. Machine Learning and artificial intelligence (AI) techniques have been fuelled by these revolutions to emerge from being purely academic topics of investigation to be the basis for a new wave of products and services for the digital age. The paradigm-shifting opportunities presented to corporates by this emerging technology range from the ability to expose and extract insights and patterns from data lakes to replacing human beings in critical decision-making scenarios. However, with these opportunities also come novel risks and concerns that must be considered when contemplating the development and deployment of AI and machine learning agents. These include understanding how their trustworthiness may be measured, the ethics and policies required for their deployment and the cybersecurity implications of their widespread adoption.

After taking healthcare, education, and telecommunication sectors by storm, artificial intelligence (AI) is all decked up to revolutionize the consumer electronics industry within the next five years. As per IBEF'S industry analysis report, Indian consumer electronics market is expected to grow at 41 percent CAGR during 2017-20 to reach $ 400 billion. Evidently, the combination of AI and IoT into the market products is further going to fuel the exponential growth. Though some of the product segments, including smartphones, alarm clocks, watches, etc, have evolved into smart ones, many are going through a rapid AI transformation phase. The application of AI into the industry of consumer electronics opens up many growth avenues and opportunities.

London-headquartered BeMyEye has made another acquisition, its third in a little over three years. This time the retail execution monitoring service is purchasing Russian crowdsourcing and image recognition provider Streetbee. The acquisition will see BeMyEye launch "Perfect Shelf," which will use image recognition technology to lower the cost for consumer goods companies wanting to get "objective and actionable" in-store insights. These will typically include share of shelf and planogram compliance (the specific placement of products on a store shelf). More broadly, BeMyEye offers a platform to enable companies and brands to crowdsource various in-store data.

Over the past few decades, machine learning has emerged as the real-world face of what is often mistakenly called "artificial intelligence." It is establishing itself as a mainstream technology tool for companies, enabling them to improve productivity, planning, and ultimately, profits. Michael Jordan, professor of Computer Science and Statistics at the University of California, Berkeley, noted in a recent Medium post: "Most of what is being called'AI' today, particularly in the public sphere, is what has been called'machine learning' for the past several decades." Jordan argues that unlike much that is mislabeled "artificial intelligence," ML is the real thing. He maintains that it was already clear in the early 1990s that ML would grow to have massive industrial relevance.