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.

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

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.

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.

Decision intelligence focuses on making more accurate and more efficient decisions based on the knowledge of how actions lead to outcomes. If you've ever been faced with decision fatigue over what to wear in the morning or gotten frustrated with a group's lack of consensus over where to eat for lunch, you understand how crucial time can be in decision-making. Decision intelligence, a crucial field of data analytics, aims to reduce the time to decision and help eliminate the uncertainty organizations can be making changes. Decision intelligence is officially on the hype cycle. Gartner proclaims it a top data and analytics trend for 2021, but we predict it will move quickly from trend to established principle.

Udemy Coupon - Machine Learning Regression Masterclass in Python, Build 8 Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard English [Auto-generated] Students also bought Deep Learning Prerequisites: Linear Regression in Python Learn Regression Analysis for Business Regression Analysis / Data Analytics in Regression Regression Analysis for Statistics & Machine Learning in R Machine Learning for Beginners: Linear Regression model in R Preview this Course GET COUPON CODE Description Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries. Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience. Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years. According to a report released by Research and Markets, the global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020.

Cerebras Systems product manager for AI Natalia Vassilieva holds the company's WSE-2, a single chip measuring almost the entire surface of a twelve-inch semiconduor wafer. Cerebras Systems, the Sunnyvale, California startup that stunned the world in 2019 by introducing a chip taking up almost the entirety of a twelve-inch semiconductor wafer, on Tuesday unveiled the second version of the part, the Wafer Scale Engine 2, or WSE-2. The chip, measuring he same forty-six square millimeters, holds 2.6 trillion transistors, which is more than double the count of the original WSE chip. It is also 48 times the number of transistors of the world's biggest GPU, the "A100" from Nvidia. The WSE-2 has 48 times as many transistors as Nvidia's latest GPU for AI, the A100.

A collaboration from UoC Berkeley, Stanford University and Facebook offers a deeper and more granular picture of the actual state of poverty in and across nations, through the use of machine learning. The research, entitled Micro-Estimates of Wealth for all Low-and Middle-Income Countries, is accompanied by a beta website that allows users to interactively explore the absolute and relative economic state of fine-grained areas and pockets of poverty in low and middle-income countries. The framework incorporates data from satellite imagery, topographic maps, mobile phone networks and aggregated anonymized data from Facebook, and is verified against extensive face-to-face surveys, for purposes of reporting relative wealth disparity in a region, rather than absolute estimates of income. A map of global poverty, weighted towards the most affected areas. The system has been adopted by the government of Nigeria as a basis for administering social protection programs, and runs in tandem with the existing framework from the World Bank, the National Social Safety nets Project (NASSP).

In 2018, in late October, a distinctly odd painting appeared at the fine art auction house Christe's. At a distance, the painting looks like a 19th-century portrait of an austere gentleman dressed in black. Contained in a gilt frame, the portly gentleman appears middle-aged; his white-collar insinuates that he is a man of the church. The painting seems unassuming, something expected at an auction house that sells billions of dollars of painting each year. However, upon closer inspection, things get a bit odd.