Santen Pharmaceutical Co., Ltd., the leader in ophthalmic drug development, has selected ArisGlobal to create a single global safety database and improve the efficiency and quality of their global safety vigilance processes. Santen Pharmaceutical's safety suite will include ArisGlobal's LifeSphere MultiVigilance (LSMV), LifeSphere Reporting and Analytics and LifeSphere Intake and Triage solutions to automate key safety vigilance activities, reduce costs, and increase compliance. "LSMV's advanced artificial intelligence (AI) and machine learning automates repetitive manual tasks, improving efficiency and compliance levels. Switching to LSMV makes our team dramatically more efficient," added Dr. Shimada, head of global safety vigilance at Santen Pharmaceutical. Santen joins more than 250 life science companies, including 9 regulatory authorities, who use ArisGlobal's safety, medical affairs, clinical and regulatory solutions, benefiting from rapid implementation on a multi-tenant cloud with upgrades delivered seamlessly.

G4 instances provide the industry's most cost-effective machine learning inference for applications, like adding metadata to an image, object detection, recommender systems, automated speech recognition, and language translation. G4 instances also provide a very cost-effective platform for building and running graphics-intensive applications, such as remote graphics workstations, video transcoding, photo-realistic design, and game streaming in the cloud. Machine learning involves two processes that require compute – training and inference. Training entails using labeled data to create a model that is capable of making predictions, a compute-intensive task that requires powerful processors and high-speed networking. Inference is the process of using a trained machine learning model to make predictions, which typically requires processing a lot of small compute jobs simultaneously, a task that can be most cost-effectively handled by accelerating computing with energy-efficient NVIDIA GPUs.

Deep Learning Innovator Earns Spot as One of "America's Most Promising Artificial Intelligence Companies" Blue Hexagon, a deep learning and cybersecurity pioneer, announced it has earned a spot on the coveted Forbes AI 50 list. As one of America's most promising artificial intelligence (AI) companies, Blue Hexagon is the only cybersecurity company that relies on deep learning (a subfield of artificial intelligence) 100% of the time for instant, real-time cyber threat detection. Modern malware is more adaptive than ever, and new variants are being created at a rate of more than 4 per second. The Blue Hexagon real-time deep learning platform addresses the limitations of perimeter defenses like intrusion detection systems (IDS) and sandboxes that cannot keep up with the daily onslaught of malicious malware variants. Launched in Q1 2019, the company is first to harness advanced deep learning for network threat protection and is proven to be greater than 99.5% effective in actual customer deployments in identifying attacks.

Inspur has announced the open-source release of TF2, an FPGA-based efficient AI computing framework. The inference engine of this framework employs the world's first DNN shift computing technology, combined with a number of the latest optimization techniques, to achieve FPGA-based high-performance low-latency deployment of universal deep learning models. This is also the world's first open-sourced FPGA-based AI framework that contains comprehensive solutions ranging from model pruning, compression, quantization, and a general DNN inference computing architecture based on FPGA. The open source project can be found at https://github.com/TF2-Engine/TF2. Many companies and research institutions, such as Kuaishou, Shanghai University, and MGI, are said to have joined the TF2 open source community, which will jointly promote open-source cooperation and the development of AI technology based on customizable FPGAs, reducing the barriers to high-performance AI computing technology, and shortening development cycles for AI users and developers.

Monclarity--the mind, body, and soul technology company--announced today that meditation app Mindwell is launching Artificial Intelligence into their predictive mood engine. The Mindwell app helps users record their current mental state, as well as how they feel after each mindfulness session. Additionally, through Mindwell's MoodShift feature, practitioners not only mark how they currently feel, but also select their target mood--focused, relaxed, or even energized. By leveraging individual and community demographic and psychographic information, Mindwell is the first meditation app that combines Artificial Intelligence and neuroscience-based techniques to more accurately predict which meditative experiences will help users achieve their desired mood outcomes. This press release features multimedia.

Mayo Clinic has entered into a 10-year strategic partnership with Google to use the tech giant's cloud platform to accelerate innovation through digital technologies. Terms of the deal were not disclosed. The Rochester, Minn.-based hospital said it selected Google Cloud to be the cornerstone of its "digital transformation." As part of the collaboration, Mayo Clinic will store patient data in the cloud and use advanced cloud computing, data analytics, machine learning, and artificial intelligence to advance the diagnosis and treatment of disease, hospital executives said in a press release. "Data-driven medical innovation is growing exponentially, and our partnership with Google will help us lead the digital transformation in health care," Gianrico Farrugia, M.D., president and CEO of Mayo Clinic, said in a statement.

Introducing--artificial intelligence--(AI) to sales training and coaching can provide a more individualized learning experience that can scale across the organization, according to Gartner, Inc. Creating a high-performing sales organization is difficult with traditional training and coaching technology as coaching content and recommendations are generally delivered by role to the sales organization and do not account for individuals-- learning styles. The use of complex--machine learning--algorithms and AI can guide reps and sales managers with recommendations for training and coaching based on their learning style. These technologies utilize branching, a method to guide an individual--s learning through a module based on responses, as well as adaptive learning, where the system directs the learner to appropriate training or coaching based on their interaction with the system. In a--Gartner survey--of organizations that are piloting or deploying AI technologies, 61% of respondents reported the resulting value delivered to the organization as significant. When asked how AI will improve their sales organization, respondents cited increased efficiency, cost reduction and improved revenue streams.

With Intent Recommendations, rather than manually training Watson Assistant you can upload pre-existing chat or call logs so Watson can train based on real user questions and utterance, creating more accurate interactions for your customers. Additionally, using the logs, Watson can identify new topics and highlight gaps in training, through unsupervised machine learning. For instance, your customer base might be saying, "How do I cancel my card?" or "My card was stolen", but your assistant doesn't recognize "cancel card". Watson will identify the new intent, "cancel card," to be trained on, which dramatically decreases the time it takes to train your virtual assistant. By surfacing these new intents, Watson will continue to get smarter and faster, as customer interactions change over time.

Ping An Insurance (Group) Company of China, Ltd. (hereafter "Ping An" or the "Group", HKEX: 2318; SSE: 601318) is pleased to announce Ping An Global Voyager Fund is leading an investment of US$15 Million in Riverain Technologies, a leading provider of clinical artificial intelligence software used to efficiently detect lung disease at its earliest stages. Riverain Technologies markets advanced artificial intelligence imaging software used by leading hospitals around the world. The software significantly improves a clinician's ability to accurately and efficiently detect cancer and other cell anomalies in thoracic CT and X-ray images. The company's suite of patented ClearReadTM software tools are FDA-cleared, deployable in the clinic or in the cloud, and powered by the most advanced artificial intelligence and machine learning methods available to the medical imaging market. Its products are relied upon by leading healthcare institutions, including Duke University, Mayo Clinic, University of Chicago, University of Michigan, and Veterans Affairs hospitals.

Stuttgart, Germany, and Yokohama, Japan – Automated driving technology is gradually providing more and more assistance to the driver – with the future aim of the car being able to take complete control. But there is more to it than that: "We want to make cars better drivers than people, and in this way to increase road safety. In other words, technology has to work more reliably than people," says the Bosch management board member Harald Kröger. That presents a major challenge, particularly in terms of surround sensing. The sensing system needs to provide the data and information of what is going on around the vehicle to enable the automated vehicle to choose the appropriate driving decision under the circumstances from a safety standpoint.