Japan-based technology major Fujitsu has announced its new research centre in India. The research centre located in Bengaluru aims to strengthen focus on research and development (R&D) into artificial intelligence (AI) and machine learning (ML) technologies, as well as quantum software. Fujitsu India, in a statement, said the number of its researchers will reach 50 by fiscal 2024. The Group will expand its research fields into security and other areas. It will also conduct software R&D in collaboration with Fujitsu's global network of research centres in areas including Japan, Europe, and the United States to create software for global distribution, the company said in a statement.

Data, technology, and people are at hand to make artificial intelligence and machine learning available to all commerce companies. To be certain, artificial intelligence and its sub-field, machine learning, have gone through cycles of inflated expectations followed by disappointments. For example, in the 1950s and 1960s, the United States government funded research for the machine translation of languages. The hope was that Russian-language documents could be instantly translated to English. But by 1966, a report from the Automatic Language Processing Advisory Committee, a government team of seven scientists, essentially killed machine translation research in the U.S. for about a decade.

A recently developed data science pathway for fourth-year radiology residents will help prepare the next generation of radiologists to lead the way into the era of artificial intelligence and machine learning (AI-ML), according to a special report published in Radiology: Artificial Intelligence. AI-ML has the potential to transform medicine by delivering better and more efficient healthcare. Applications in radiology are already arriving at a staggering rate. Yet organized AI-ML curricula are limited to a few institutions and formal training opportunities are lacking. Three senior radiology residents at Brigham and Women's Hospital (BWH) in Boston recently helped devise a data science pathway to provide a well-rounded introductory experience in AI-ML for fourth-year residents.

A recently developed data science pathway for fourth-year radiology residents will help prepare the next generation of radiologists to lead the way into the era of artificial intelligence and machine learning (AI-ML), according to a special report published in Radiology: Artificial Intelligence. AI-ML has the potential to transform medicine by delivering better and more efficient healthcare. Applications in radiology are already arriving at a staggering rate. Yet organized AI-ML curricula are limited to a few institutions and formal training opportunities are lacking. Three senior radiology residents at Brigham and Women's Hospital (BWH) in Boston recently helped devise a data science pathway to provide a well-rounded introductory experience in AI-ML for fourth-year residents.

Business leaders, your service providers are gaining bottom line and value for AI. Are they sharing these with you? A recent HFS study showed us that organizations use AI-ML (artificial intelligence and machine learning) to reduce operational costs (see Exhibit 1). Your service provider partners are reducing their costs with AI-ML, too. Are they passing the savings along to you? Maybe, and maybe not.

The world is going digital at an unprecedentedly fast pace, and the change is only going to go even faster. The digitalization means everything is moving at lightning speed – business, entertainment, trends, new products, etc. The consumer gets what he or she wants instantly because the service provider has the means to deliver it. While the conveniences and benefits of this digital era are many, it also brings with it several negatives. One of the most significant and destructive threats it poses is that our private information is at risk like never before.

In the last few years there have been numerous developments involving Artificial Intelligence (AI) and Machine Learning (ML), and the ways in which both are being used are constantly expanding. On the video editing front software and tech giants have been heavily investing in AI and ML, and as a result it has fueled a wide range of innovations. Several years ago IBM made headlines when it created a movie trailer using its Watson supercomputer. Using ML, Watson'learned' from other movie trailers and subsequently curated and identified video footage that could be used in the trailer for the horror film, Morgan. Since then AI and ML have been used frequently to curate videos for editing. Recently Google released its Clips camera that uses AI to automatically record short video clips that it thinks will be interesting.

In many ways, we're close to a tipping point in the development of artificial intelligence technologies, with fleets of self-driving cars, hive drones, automated retail experiences, and more. Companies of every size now must grapple with how AI will affect and possibly eliminate their sector, and how they can adapt and leverage AI and machine learning (ML) to disrupt themselves before they get disrupted. While it's crucial for companies to start participating in the AI movement or risk getting left behind, it's important to do so strategically to ensure AI initiatives are truly helping to achieve ultimate business goals. AI-ML will make many of our day-to-day lives better and more productive by augmenting what we do already in much more accurate and efficient ways. Tech innovators like Uber, Google, and Facebook are making big bets on AI through acquisitions and internal organizational makeovers that make AI a strategic priority.

In many ways, we're close to a tipping point in the development of artificial intelligence technologies, with fleets of self-driving cars, hive drones, automated retail experiences, and more. Companies of every size now must grapple with how AI will affect and possibly eliminate their sector, and how they can adapt and leverage AI and machine learning (ML) to disrupt themselves before they get disrupted. While it's crucial for companies to start participating in the AI movement or risk getting left behind, it's important to do so strategically to ensure AI initiatives are truly helping to achieve ultimate business goals. AI-ML will make many of our day-to-day lives better and more productive by augmenting what we do already in much more accurate and efficient ways. Tech innovators like Uber, Google, and Facebook are making big bets on AI through acquisitions and internal organizational makeovers that make AI a strategic priority.