Artificial intelligence (AI) is making inroads in the healthcare industry in various ways. From improving medical diagnoses to finding new cures for diseases, AI is revolutionizing the way healthcare professionals approach their work. One exciting example of AI in healthcare is its application to electrocardiograms (ECGs), which are used to monitor and diagnose heart health. Researchers in northern Alberta, Canada, are utilizing AI to glean more information from ECGs and improve patient care and the healthcare system as a whole. ECGs are a standard test in hospitals, used to check the rhythm and electrical activity of the heart.

As video streaming, Alexa-type digital assistants and self-driving cars continue to permeate daily life, edge computing architecture has become foundational to enable these tasks. These data-intensive processes are fueled by a proliferation of Internet of Things (IoT) devices.. According to Statista, there will be 30.9 billion devices by 2025. These devices are becoming increasingly intelligent as well, with more analytics and decision-making capabilities at the device level. "There are more and more devices that need intelligent capabilities, especially to process AI at the edge," said Aditya Kaul, research director at Omdia.

To gain an insight into the key trends reshaping with artificial intelligence, Digital Journal spoke with Anil Kaul, CEO of AI and analytics company, Absolutdata. Kaul explains that businesses need a reset in 2021 and sees a variety of new technologies making their way to the forefront because of this. Digital Journal: How damaging has 2020 been for businesses? Anil Kaul: Since the downturn was triggered by a pandemic, the damage has been uneven. The economic turmoil has been devastating for many small businesses, but even large, well established corporations have felt the impact in uneven ways. The travel and hospitality sectors were hard hit, and analysts say it might take years to recover.

AI processing is changing the world order among CPU, GPU, and FPGA companies, with a host of AI processor startups joining the fray. The fight was once mostly in data centers, but they've all had to decamp to a new battlefield at the network edge. Driven by that premise, Blaize, an AI processor startup in El Dorado Hills, Calif., is heading straight to the edge with its just-announced AI hardware and software. The market forces sending AI inference to the edge are well understood. Privacy concerns, bandwidth issues (going back and forth between edge to cloud), latency and cost worries drive AI processing more and more edgeward.

It was just a few months ago that NRF looked at AI in retail, questioning whether 2020 might be the year that it finally took off. How quickly things can change. Artificial intelligence and its companion, machine learning, have been upended along with every other aspect of retail. And while AI's ability to anticipate the future might have been damaged by toilet-paper hoarding, bread-baking shoppers, it also might provide an unexpected roadmap for the future. Machine-learning based AI has been "thrown for a loop by the coronavirus," says Nikki Baird, vice president of retail innovation at Aptos.

Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long.

Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long; instead, many of these data-intensive processes must remain localized and processed at the edge and on or near a hardware device.

Compared to a few years ago, the artificial intelligence (AI) market is starting to solidify around real-world applications with the pace of change being faster than it ever has been before, as startups and technology providers rush to create platforms and targeted niche solutions for solving specific enterprise problems. According to a new report from Tractica, the rising tide of AI adoption across multiple industries will drive significant growth during the next decade, and the market intelligence firm forecasts that annual worldwide AI software revenue will increase from $3.2 billion in 2016 in 2016 to $89.8 billion by 2025. This forecast is a significant upgrade of Tractica's previous projection for AI market revenue, which was published in 2Q17, due to an improved outlook for a number of specific use cases across multiple industries. "Artificial intelligence is already key to how consumer internet companies operate today, allowing them to roll out hyper-personalized services by following an'AI first' strategy," says research director Aditya Kaul. "The rest of the market in the enterprise and government sectors is still catching up on adopting AI and has yet to fully understand its value, including the breadth and depth of use cases, the technology choices surrounding AI, and the implementation strategies."

Truly understanding your customer is the holy grail of those at the frontiers of personalisation. Unparalleled amounts of customer data enable machines to hold up a mirror to our preferences, understand our needs and sell us something relevant. Mass customisation can now reach new heights at a time when choice is infinite, especially online. "Personalisation 2.0 or, as some call it, hyper-personalisation, creates an ideal paradigm where we're now able to move away from just selling people something, to being able to anticipate a very discrete need, and make a highly relevant and curated offer at an exact time," explains Utpal Kaul, head of new product incubation at CWT. Over the last few years, huge advances in artificial intelligence (AI), machine and deep-learning, as well as algorithm neural networks, have made this possible.

The cruise line is on-boarding AI. Customers today want options and flexibility-- if businesses want to remain competitive and scale, that often means having vast, complex inventory. But that presents another challenge; ensuring that inventory-- whether it's clothing, hotel rooms, holiday packages, or otherwise-- is managed in a way that optimizes sales and revenue, which can be sold across a multitude of channels. At any given point, the US-headquartered Royal Caribbean Cruise Line has 4.5 million price points available. In an interview with Hospitality Net, Michael Goldner, Vice President of Revenue Management of the cruise line said there is a "price on everything".