Newswire) Consumer Electronics Show - CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing platforms and artificial intelligence processors for smarter, connected devices, today unveiled NeuPro, a powerful and specialized Artificial Intelligence (AI) processor family for deep learning inference at the edge. The NeuPro family of processors is designed for smart and connected edge device vendors looking for a streamlined way to quickly take advantage of the significant possibilities that deep neural network technologies offer. NeuPro is a powerful and specialized Artificial Intelligence (AI) processor family for deep learning inference at the edge. It is designed for edge device vendors looking to quickly take advantage of the significant possibilities that deep neural network technologies offer. NeuPro extends the use of AI beyond machine vision to new edge-based applications including natural language processing, real-time translation, authentication, workflow management, and many other learning-based applications.

READ BLOG 6. LEARN HOW TO ADVANCE YOUR BUSINESS WITH AI Join us at the RE•WORK Deep Learning Summit in San Francisco January 25-26 to hear from the global AI pioneers at Google Brain, DeepMind, Tesla, and more, who will share their most cutting-edge research with over 850 attendees at the event. On Day 2, NVIDIA Inception takes over Startup Session where leading companies share how they advanced AI and DL in their businesses. Save 20% on your registration with the code NVIDIA20. REGISTER NOW 7. AI-INFUSED AUTONOMY MAKES LIFE ON THE ROAD EASIER AND SAFER FOR TRUCK DRIVERS Truck drivers haul most of the freight that traverses the U.S. With long hours, mounting demand to fulfill online orders, and the perils of navigating everything from snowstorms to rush hour traffic, it can be a stressful job. Episode 2 of our "I am AI" docuseries explores how PACCAR, the maker of Peterbilt, Kenworth and DAF brand trucks, is exploring AI to ease their burden. LEARN MORE 8. AI PUTS THE ZAP ON ENERGY BILLS Due to the complex and time-consuming nature of buying energy, many businesses choose not to work directly with suppliers.

Winter is coming, but fear not. According to the experts, we won't need Jon Snow to save us -- it's only coming for our machines. Gary Marcus, an AI expert and Professor of Psychology at NYU, Tuesday published a fascinating white-paper. It basically serves as a list of reasons why he thinks deep learning is shit and the community should abandon it and start over. Deep Learning is not enough, and we need to start over -- Hinton confirms what I have been saying for two decades. By the numbers, this is 10 percent of the reason this guy thinks we should all reconsider the idea of deep learning.

While you've been sleeping, artificial intelligence has been evolving. It isn't something to be afraid of -- yet. In actuality, AI has been present in numerous industries for a long time. As development improves and transforms, both with AI-based analytics, also referred to as deep learning, and user feedback, AI is evolving from being the villain in a bad action movie to helping people live a better life through sleep and health and wellness tracking. As AI innovation improves, so do the apps being implemented in daily life.

These are my opinions on where deep neural network and machine learning is headed in the larger field of artificial intelligence, and how we can get more and more sophisticated machines that can help us in our daily routines. Please note that these are not predictions of forecasts, but more a detailed analysis of the trajectory of the fields, the trends and the technical needs we have to achieve useful artificial intelligence. Not all machine learning is targeting artificial intelligences, and there are low-hanging fruits, which we will examine here also. The goal of the field is to achieve human and super-human abilities in machines that can help us in every-day lives. Autonomous vehicles, smart homes, artificial assistants, security cameras are a first target.

Eyes are said to be the window to the soul, but according to Google engineers, they're also the window to your health. The engineers wanted to see if they could determine some cardiovascular risks simply by looking a picture of someone's retina. They developed a convolutional neural network -- a feed-forward algorithm inspired by biological processes, especially pattern between neurons, commonly used in image analysis. This type of artificial intelligence (AI) analyzes images holistically, without splitting them into smaller pieces, based on their shared similarities and symmetrical parts. The approach became quite popular in recent years, especially as Facebook and other tech giants began developing their face-recognition software.

Are you interested in the field of Deep Learning? Here is a short and useful Review of Deep Learning Course A-Z Hands-On Artificial Neural Networks. If you are in the intermediate level people who know the basics of Deep Learning and Machine Learning, including the classical algorithms like linear regression or logistic regression and more advanced topics like Artificial Neural Networks, but who want to learn more about it and explore all the different fields of Deep Learning. This is one of the bestseller courses on Udemy where students enrolled more than 68120 and with a 4.5 star ratings. With this top-selling Deep Learning tutorial you will learn how to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts.

The use of Artificial Intelligence (AI) is on the rise in the technology sector and has become a buzz-worthy topic in many corners of our digital world. The application of AI in the medical field holds great promise for improving patient health, but will doctors and patients feel comfortable using it? Young startups have begun leveraging this technology to prove better health outcomes, but there's still a lot to do before we'll see AI used pervasively in the clinic. To date, the sweet spot in healthcare AI has been pairing algorithms with structured exercises in reading patient data and medical images to train machines to detect abnormalities. This training is called "deep learning." In the same way, algorithms are being used to sift through vast amounts of medical literature to inform treatment decisions where it would be too onerous a task to have a human read through the same journals.

Originally posted on The Horizons Tracker. Autonomous vehicles are becoming ever more capable, and if they are to be successful, and safe, when operating on our roads, they need extremely effective vehicle-to-vehicle communication. Researchers from New York University have partnered with HERE HD Live Map to ensure vehicles have accurate information on the status of lanes, obstacles, hazards and speed-limits in real time. The team are developing a deep learning based system that allows autonomous vehicles to navigate and respond to changing road conditions by pairing the data they're collecting from onboard sensors with that from the Here HD live maps. The kind of maps used by autonomous vehicles are accurate to within 10-20cm, and there is a strong requirement for these maps to be updated in real-time to ensure their accuracy.

You may have heard rumors about artificial intelligence (AI) potentially taking over our jobs. And the question is: Should you be concerned? In my opinion, we should be excited. AI -- especially "deep learning" technology -- brings new opportunities and innovation in the way digital marketing, sales, and customer support are handled. But what is deep learning?