Planning inspectors recommended against a Hitachi-built nuclear power plant in Anglesey on the basis that it could dilute the island's Welsh language and culture, it has emerged. Hitachi scrapped plans to build a 20bn nuclear power plant at Wylfa in 2020 over cost concerns after failing to reach a funding agreement with UK ministers. Keir Starmer's government has vowed to make it easier to build major infrastructure projects by reforming the planning system and stopping campaigners from launching "excessive" legal challenges. The prime minister unveiled plans for a historic expansion in nuclear power this week, vowing to "push past nimbyism" and make sites across the country available for new power stations. Nuclear industry figures believe that the fate of Hitachi's proposed plant at Wylfa demonstrates the problems with the UK's planning system.

Bharti Patel is SVP, Head of Engineering at Hitachi Vantara, heading the company's cutting-edge data and infrastructure product offerings. She was previously CTO at Austin-based Alen where she led digital transformation and exponential growth for medical-grade HEPA air purification systems. Prior to that, she spent 20 years at IBM where she led large global R&D teams across ecommerce, mobility, client platforms, and – most notably – data and storage management. While she is proud to say she is a developer at heart, Patel is best known for her passion for driving innovation that creates exceptional customer experiences. Now back in the data space, Patel is leveraging Hitachi's long-term history in AI and domain specific data to embed generative AI to further differentiate the company's next gen infrastructure systems.

Manufacturers are finding AI is no longer the answer to automating operations and improving product quality. While AI can increase the defect detection rate by up to 90% over human inspection, it's useless if manufacturers cannot obtain the information they need when they need it. Without a faster process, they continue to run the risk of unplanned shutdowns and production errors. "The challenge manufacturers have with AI is actually validating and verifying the return of investment," says Shunichi Kagaya, Sr Engineer at Hitachi, a leader in #digital and #IoT solutions. "Manufacturers understand the value of #data and they want to use it.

Manufacturers are finding AI is no longer the answer to automating operations and improving product quality. While AI can increase the defect detection rate by up to 90% over human inspection, it's useless if manufacturers cannot obtain the information they need when they need it. Without a faster process, they continue to run the risk of unplanned shutdowns and production errors. "The challenge manufacturers have with AI is actually validating and verifying the return of investment," says Shunichi Kagaya, Senior Engineer at Hitachi, a leader in digital and IoT solutions. "Manufacturers understand the value of data and they want to use it. But they don't understand how."

For this smaller group of patients, physicians may have limited clinical decision-making experience or evidence-based guidance for choosing drug combinations. The solution is to expand the number of patients to support development of general principles to guide decision-making. Combining patient data from multiple healthcare institutions, however, requires deep expertise in artificial intelligence (AI) and wide-ranging experience in developing machine learning models using sensitive and complex healthcare data. Hitachi, U of U Health, and Regenstrief researchers partnered to develop and test a new AI method that analyzed electronic health record data across Utah and Indiana and learned generalizable treatment patterns of type 2 diabetes patients with similar characteristics. Those patterns can now be used to help determine an optimal drug regimen for a specific patient.

On the factory floor, machine downtime is a disaster – production can slow to a crawl or a complete stop, wasting precious time and money. To dodge downtime, manufacturers typically plan rigorous maintenance regimes – fixing problems before they even occur. That's great for keeping production running at full pace, but costly in terms of having the right experts and spare parts to hand at all times. Preventative maintenance is labour intensive and expensive. Have faith in data – and artificial intelligence.

Today, advances in agronomy combined with smart agriculture technology have improved crop yields and sustainability. Enhancements in animal husbandry technology, improved breeding, nutrition and disease management help ensure optimal growth and performance of livestock. In spite of these innovations, the agricultural industry still faces significant challenges in producing enough food and getting it safely to market. These include changing weather patterns, water shortages, urbanization, population growth, complex environmental regulations, and dwindling available agricultural land, among others. In addition, food waste is a significant drain on the global food supply.

Artificial intelligence (AI) and video analytics are rapidly becoming integral parts of our lives, transforming corporate activities, and creating many opportunities to improve the human condition. Recent developments in the field have led some experts to suggest that the ability of AI has moved beyond recognition to cognition, where AI is not only able to grasp concepts but find deeper or "hidden" meaning from images. Dr. Shin'ichi Satoh of the National Institute of Informatics (NII) and Dr. Tatsuhiko Kagehiro, head of Hitachi's Lumada Data Science Laboratory, met to discuss the current state and next wave of advancements in this field and to explore the possibilities of social application. Dr. Satoh is a leading expert in video analytics research and AI that leads to customer collaborative creation, and Dr. Kagehiro is director of Hitachi's Artificial Intelligence Innovation Center, which conducts research and development. Mr. Tomoaki Yoshinaga, Senior Researcher at the Lumada Data Science Laboratory, moderated the discussion.

As CEO of Hitachi Vantara, Gajen helps solve clients' problems by bringing to bear Hitachi's unrivaled industrial expertise across sectors. You might not think saving the world's tropical rainforests is a data challenge, but the urgent task of protecting the last remaining two million square miles of forest is precisely that. What is more, the challenge holds vital lessons for anyone tackling a data project with seemingly insurmountable odds. Logging, much of it illegal, strips the planet of more than 32 million acres of natural forest every year. If you ever imagined literally trying to find a needle in a haystack, then you might be able to contemplate what it is like to find a chainsaw in forested areas the size of Australia.

That's where Hitachi hopes to employ GlobalLogic's engineering know-how in manufacturing, energy and other sectors to expand further outside Japan, said Gajen Kandiah, chief executive of Hitachi Vantara, the firm's digital infrastructure segment. "Unfortunately, you only hear about a small group of companies that are maximizing data," he said. "You don't hear about the 99% that isn't." The Morning Download delivers daily insights and news on business technology from the CIO Journal team. Digital services and the data analytics that power them have been a competitive advantage for many companies during the pandemic, with global supply chains upended and employees and customers interacting virtually.