With the emergence of ever-cheaper and robust hardware, 5G connectivity around the corner, and most importantly, a growing list of real world use cases, we can all agree that Internet of Things (IoT) solutions for enterprise are here to stay. But is that where it ends? Is the end goal of having interconnected devices simply because sounds like something that could be useful to have, perhaps to monitor some sort of reading in a production environment, or simply get timely updates in a supply chain process? IoT will play a much more important role in our future, primarily for the following reasons. Not only are IoT projects ultimately most valuable as big data projects (we are essentially collecting large amounts of data from these IoT devices after all), but ultimately, all IoT projects will apply machine learning (ML) and artificial intelligence (AI) to the data collected in order to truly move the game forward.

New Delhi: In recent months, the government has taken several steps to raise the bar on good governance in the corporate sector. Minister of state for corporate affairs P.P. Chaudhary, 65, an expert on constitutional matters, said in an interview that the government was working on a host of measures that will improve transparency in companies' affairs and improve ease of doing business in the country. For long, the corporate structure has been abused by some for tax evasion and money laundering. Do you think the steps taken so far effectively address this problem? We are gradually tightening the procedures.

IBM has been on the AI journey for a long time, but the path has not always been smooth. My experience in the consulting business has taught me that successful practitioners need to be flexible and quick to make course corrections. We at IBM have learned along our AI journey, and here are three lessons that come to mind from my own interaction with clients and business colleagues. Remember the adage: garbage in, garbage out. We've acknowledged that the results of data analysis are sometimes misleading or even inaccurate.

Technology, human ingenuity and deep pools of financial capital are aligned in an important mission: bringing artificial intelligence (AI) to global healthcare. If investor enthusiasm is any gauge, the mission is advancing quickly. No fewer than 300 healthcare AI startups have closed funding deals in the last five years--nearly 45 percent of them first equity rounds by startups just entering the space.1 In several respects, however, the mission is generating too much heat and too little natural intelligence. Technological assets on AI's frontier are often over billed in the media and poorly validated.