Vision is one of the hottest area for AI development because vision can or will be used for a wide variety of consumer and industrial applications. Everything from security systems and retail monitoring solutions to manufacturing quality control and autonomous machines require vision AI. Xilinx has been developing chips and tools for AI development leveraging the company's expertise in programmable/adaptable platforms. Now, Xilinx is introducing the Kria System-on-Module (SoM) just for vision AI applications. A module or SoM is a predesigned system or sub-system with the required chips already mounted on a printed circuit board (PCB) that connect to other system components or interfaces.

Upon his retirement from veterinary practice--the last 2 decades of which he spent in specialty care where he helped to establish the model of a referral hospital--Neil Shaw, DVM, DACVIM, started thinking about how treatment protocols in general practices could be improved. His primary concern: how to scale what is done in specialty practices for use in general practices. Preventive care protocols are well established in general practice, Shaw says, but "models for treating common illnesses and injuries in primary care practice really have not been well established." "Not all cases need to be referred," he tells Adam Christman, DVM, MBA, in this episode of the Vet Blast Podcast. And he saw technology as the only way to accomplish that goal.

Machine Learning is one the growing fields and to learn the important concepts require solid foundation and conductive environment for...

The world around us is changing rapidly. With the arrival of industrial revolution 4.0, businesses of all sizes and types are increasingly capitalizing on advanced, intelligent technologies. They are taking advantage of automation to reduce time-consuming, tedious tasks, especially automating assembly line work. However, as such intelligent technologies are better performing than humans, it is necessary businesses must think of knowledge management for their employees. Knowledge is significantly a crucial aspect in achieving high-quality performance for employees.

The Covid-19 pandemic did more than just pause the world. It took away a fundamental aspect of being human -- touch. No more greeting familiar faces at work, no everyday commute rituals, no get-togethers, and worse, it kept, and is keeping, us from holding our loved ones, our family. Fatefully, in this Covid-induced skin hungry world, the familiarity of contact is kept alive by digital technology. Even as Covid-19 threatens to put modern lifestyle on the fringes and individual cocoons, we're in times where touch and connectedness is seeing new meaning and function.

Editor's note: Today's guest post comes from AI for healthcare platform Lumiata. Here's the story of how they use Google Cloud to power their platform--performing data prepping, model building, and deployment to tackle inherent challenges in healthcare organizations. If ever there was a year for healthcare innovation--2020 was it. At Lumiata, we've been on a mission to deliver smarter, more cost-effective healthcare since 2013, but the COVID-19 pandemic added new urgency to our vision of making artificial intelligence (AI) easy and accessible. Using AI in healthcare went from a nice-to-have to a must-have for healthcare organizations.

Are these buzzwords hitting your newsfeed? Yes or no, it is high time to get tuned for the latest updates in AI-powered business practices. Machine Learning Model Operationalization Management (MLOps) is a way to eliminate pain in the neck during the development process and delivering ML-powered software easier, not to mention the relieving of every team member's life.

Artificial intelligence is one of the most revolutionary technologies of our time, which is advancing as each day goes by. AI labs contribute to these advancements by housing scientists and researchers under one roof to study this disruptive technology for further developments. While there are quite a few AI labs across the globe, artificial intelligence researchers go perplexed when people ask them to rate the top labs in the world. And rightfully so, because they're all unique in the way they work. While every lab focuses on different domains of artificial intelligence, commercial AI labs like Google, Facebook, Amazon, Apple, and Microsoft, the U.S Big Tech, have set up dedicated AI labs too.

In the first experiment, the robot would learn how its own head moved, and assume that the human--s head was governed by the same rules. It would then observe the movement of the human--s head, including the direction that person was looking and what the person fixated on, and mimic those movements. In the second experiment, the robot experimented with moving food-shaped toys around on a table. Not only did the robot mimic the human--pushing the toys, sometimes sweeping them off the table top--it also occasionally used different means to achieve the same end result...

The Indian Institute of Technology Madras has developed a fellowship program to encourage early-career AI researchers. The Narayanan Family Foundation and the Institute's Robert Bosch Centre for Data Science and AI have teamed up to build a fellowship in Artificial Intelligence for Social Good. The application is available to artificial intelligence researchers who want to use their skills for the betterment. The Indian Institute of Technology Madras hopes to attract recent PhD graduates or newly qualified researchers in computer science, computational and data sciences, biomedical sciences, management, finance, and other engineering departments with outstanding educational achievements to RBCDSAI through this program, which is funded by the Narayanan Family Foundation. With India's largest network analytics and deep reinforcement learning study groups, RBCDSAI is a world's most prominent interdisciplinary research academic centre for Data Science and AI.