Oracle announced availability of its AI-trained voice with Oracle Digital Assistant. Now, enterprise customers can use voice commands to communicate with their enterprise applications to drive desired actions and outcomes, enriching the user experience with conversational AI, simplifying interactions and improving productivity. "Enterprises are demanding an AI-powered voice assistant that understands their specific vocabulary and enables naturally expressive interactions for its users," said Suhas Uliyar, vice president, AI and Digital Assistant, Oracle. "Most of all though, enterprises value a highly secure AI-powered voice assistant that stores their business' sensitive data in Oracle's second generation cloud infrastructure." Built on Oracle's next-generation infrastructure, Oracle Digital Assistant applies AI with deep semantic parsing for natural language processing (NLP), natural language understanding (NLU) and custom machine learning (ML) algorithms.

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.

In this video I talk about an AI that is used in Denmark to listen to emergency calls to detect heart attacks before humans so that emergency service can be dispatched earlier. If you would like more information on this topic, please feel free to visit my website and sign up for content updates! I write articles every week on various different topics such as Big Data, Artificial Intelligence & Machine Learning.

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.

According to Gartner, artificial intelligence (AI) is not defined by a single technology but by an array of capabilities and research, from advances in algorithms to abundant computing power and advanced analytical methods such as deep learning. It sounds like the voice that responds from a smart speaker when we ask about the weather or to tune into a podcast. A vast majority of CXOs are already relying on consumer technologies such as voice-activated digital assistants in their work, according to a recent survey by PwC. Imagine how much more powerful those virtual assistants could be with access to the collective knowledge of the enterprise and the ability to know individual users and what they need to work best. And imagine putting that power into the hands of users across the enterprise, in the meeting room, on a factory floor or in any device they use to do their jobs.

You don't want to lose an item tagged with a Tile Bluetooth tracker, but you'll at least have an easier time finding it in the near future. Tile is planning Google Assistant support that will let you directly ring your tracker from any device that supports the AI helper, making it just a matter of a quick voice command. You could find your keys just by asking your Nest speaker while you're frantically searching between the couch cushions.

One of the most hotly-debated issues around artificial intelligence is how the group of technologies will impact individual job roles, and whether AI is a "job killer" as opposed to a "job creator." For insights on this debate, Information Management spoke with Mike Maresca, managing director in Accenture's internal IT organization. That firm recent conducted research on the current impacts of AI on job roles and what organizations can expect in the near future. Information Management: Recent research from Accenture found that 29 percent of organizations have already had to redefine job roles due to the impact of artificial intelligence. What types of jobs or job roles are being most affected by this trend?

As we enter the next decade, autonomous driving and AI-powered vehicles will revolutionize the way we move. That's why transportation has become an integral part of the conversation at the GPU Technology Conference, the world's premier AI event. It's the combined effort of automakers, suppliers, startups, researchers and regulators. They'll all be gathering at GTC, running March 22-26, 2020, in San Jose, to discuss the latest advances and the roadmap for what's ahead. And we want to hear from you.

On August 9, 2019, the National Institute of Standards and Technology (NIST) released "U.S. Leadership in AI: A Plan for Federal Engagement in Developing.

Expedia Group has announced a collaboration with AI Singapore (AISG) – an inter-agency unit tasked to catalyse and grow the country's artificial intelligence (AI) capabilities – under its flagship 100 Experiments (100E) programme to develop an AI solution to transform the online search experience for Asian travellers. The first online travel platform to collaborate with AISG for 100E, Expedia Group will provide a team of experienced engineers, data scientists and marketers to work with the AISG's project lead, project managers and AI apprentices to enhance travel search query understanding and improve the accuracy of search query resolution in Asian languages. Today's search engines are efficient in understanding travel search queries and providing query resolutions in English, as English is the dominant language used online by 25 per cent of all Internet users. However, when dealing with travel search queries conducted in Asian languages such as Japanese, Korean, simplified Chinese and traditional Chinese, the performance of the search engines declines significantly and the accuracy of query resolution dips. For a start, the Expedia Group and AI Singapore project team will leverage natural language processing and machine learning to develop an AI-based model to enhance search query understanding and resolution in the Japanese language, before extending the model to other Asian languages to enhance online search efficiency.