Blood tests tell doctors about the function of key organs, and can reveal countless medical conditions, including heart disease, anemia and cancer. At major hospitals, the number of blood cell images awaiting analysis can be overwhelming. With over 10,000 beds and more than 8 million outpatient visits annually, Taiwan's Chang Gung Memorial Hospital collects at least a million blood cell images each year. Its clinicians must be on hand 24/7, since blood analysis is key in the emergency department. To improve its efficiency and accuracy, the health care network -- with seven hospitals across the island -- is adopting deep learning tools developed on AI-Ready Infrastructure, or AIRI.

Leaders in the AI community came together to release the 2019 AI Index report today, an annual attempt to examine the biggest trends shaping the AI industry, breakthrough research, and AI's impact to society. It also examines trends like AI hiring practices, private investment, AI research contributions by nation, researchers leaving academia for industry, and how much AI plays a role in specific industries. The report also notes strides in the reduction of the amount of time it takes to train AI systems and computing costs, two of the biggest hindrances to AI adoption rates. "In a year and a half, the time required to train a large image classification system on cloud infrastructure has fallen from about three hours in October 2017 to about 88 seconds in July, 2019," the report reads. The report is compiled by the Stanford Human-Centered AI Institute in collaboration with people from OpenAI.

This week, Facebook came under fire for having hired hundreds of contractors to listen to and transcribe users' conversations. Last week, a Vice Motherboard report revealed that Microsoft contractors were listening to audio recordings of personal conversations of Skype users who used the app's AI translation service and voice commands sent to Cortana, the company's AI-powered voice assistant. This comes no longer as a surprise. Microsoft and Facebook aren't not the first tech companies whose employees or remote contractors listen to users' voices. Amazon, Google and Apple have been caught doing the same thing with their voice assistants in the past year (and they've all used cleverly worded EULA's to gain users' consent without explicitly telling them humans will listen to their voice).

Data and AI need to be unified: the best AI applications require massive amounts of constantly updated training data to build state-of-the-art models. So far, Apache Spark is the only unified analytics engine that combines large-scale data processing with state-of-the-art machine learning and AI algorithms. Combining Spark AI topics, this conference is a unique "one-stop shop" for developers, data scientists, and tech executives seeking to apply the best tools in data and AI to build innovative products. The sessions and training at this conference will cover data engineering and data science content, along with best practices for productionizing AI: keeping training data fresh with stream processing, quality monitoring, testing, and serving models at a massive scale. The conference will also include deep-dive sessions on popular software frameworks--e.g., Delta Lake, MLflow, TensorFlow, SciKit-Learn, Keras, PyTorch, DeepLearning4J, BigDL, and deep learning pipelines.

This introduces a new high-performance, high capacity, reduced cost inference choice for data centers and machine learning service providers. It is the purpose-designed, open PCIe architecture of the DSS 8440 that enables us to readily expand accelerator options for our customers as the market demands. This latest addition to our powerhouse machine learning server is further proof of Dell EMC's commitment to supporting our customers as they compete in the rapidly emerging AI arena. The DSS 8440 is a 4U 2-socket accelerator-optimized server designed to deliver exceptionally high compute performance for both training and inference. Its open architecture, based on a high performance switched PCIe fabric, maximizes customer choice for machine learning infrastructure while also delivering best-of-breed technology.

Deep learning is applying statistics to get the greatest number of'right answers.' For those with limited time to evaluate a system, a quick way to do so is to run a good part, induce the defect, and rerun it.

With face recognition software taking over the world, every business wants to have a feature in their application that can detect and infer useful information from a picture or video to complement their product and services. Using proven, highly scalable, deep learning technologies that require no machine learning expertise to use, Amazon Rekognition makes it easy to add image and video analysis to your application. You can identify objects, people, text, scenes, and activities in images and videos as well as detect any offensive content. It also offers highly accurate facial recognition and facial search capabilities that you can use to identify, evaluate and compare faces for a wide range of cases of user authentication, counting of individuals, and public safety.

CVML Live Web Lecture Series Concept Artificial Intelligence and Information analysis (AIIA) Lab, AUTH is proud to launch the live CVML Web lecture series that will cover very important topics Computer vision/machine learning. Top scientists internationally will deliver these lectures, aiming at providing in-depth knowledge on various CVML topics. The 1-hour lectures will take place on Saturdays, to avoid conflicts with other intended registrant schedules/duties: a) Saturdays 11:00 EET (17:00 Beijing time) and b) Saturdays 20:00 EET (13:00 EST, 10:00 PST for NY/LA, respectively) for audience in the Americas. Each lecture will be announced at least 1 week in advance in various relevant email lists and in this page. Lectures will consist primarily of live lecture streaming and PPT slides.

Over the years, artificial intelligence has amazed everyone with numerous breakthroughs, and this year it was no different. The whole year, we witnessed awe-inspiring innovations in reinforcement learning, neural networks, among others. Tech companies from across the world benchmarked various leaps in artificial intelligence to further eliminated the doubts people had about achieving true AI. As a chronicler of the technological progress in the space of analytics, artificial intelligence, data science and big data, among others, Analytics India Magazine was on top of every jaw-dropping development. We bring to you the top 7 amazing AI advancements that changed the world forever.