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Unlock machine learning with these Amazon SageMaker examples

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Your first SageMaker application doesn't have to reinvent machine learning. A chatbot can be a good place to start. Organizations should use SageMaker to widen the capabilities of existing services that are already tied to AWS, said Svetlana Sicular, research vice president at Gartner. A chatbot to streamline customers' experiences or their internal operation is a good entry point as an Amazon SageMaker example. For internal use, a chatbot could aid in compliance checks, Sicular said.


AI common in the workplace by 2025, says Gartner - TechHQ

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Smart assistants could become common AI presences in the office. Artificial intelligence (AI) will become "mainstream" enterprise technology by 2025, according to Gartner analysts at its Digital Workplace Summit in London. As reported by ComputerWorld, AI programs will become commonplace in our offices, as investments in digital transformation continue, and applications of the technology continue to permeate business operations. In particular, digital voice assistants which have been well-received among consumers could serve as'receptionists' in the office environment, booking meeting rooms, or on-boarding new recruits, for example. In fact, Gartner expects 25 percent of digital workers to be using AI voice assistants within the next two years, and reportedly urged businesses to begin developing skills in their deployment, management, and security.


SIBOS19: machine learning - homines in machina

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GRANT: Trade finance is very paper-oriented business and has been for a very long time. I would describe the pace of technology driven change around trade finance as rather modest, certainly over the past couple of decades. "Machine learning is really just a term for something that's been around for years - coding a computer to take certain actions in certain scenarios." However the emergence of blockchain and machine-learning technology has already revolutionised the way we look at trade finance globally, providing us with a unique opportunity to shift gears. Certainly, at ANZ we have meaningful programs of work that leverage those two technology capabilities which impact a material component of our trade-finance business.


TensorFlow Tutorial For Beginners

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You have now successfully trained your model! That wasn't too hard, was it? You're not entirely there yet; You still need to evaluate your neural network. In this case, you can already try to get a glimpse of well your model performs by picking 10 random images and by comparing the predicted labels with the real labels. You can first print them out, but why not use matplotlib to plot the traffic signs themselves and make a visual comparison? However, only looking at random images don't give you many insights into how well your model actually performs.


Benefitfocus Delivers Expanded AI Capabilities

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Benefitfocus, Inc., a leading cloud-based benefits management platform and services provider, announced enhancements available on the Benefitfocus Platform powered by its artificial intelligence (AI) engine, BenefitSAIGE. BenefitSAIGE is the intelligence engine enabling several capabilities such as Smart Moments, utilization reporting, plan modeling, cost analysis and data quality reporting. With this announcement, medical carriers and voluntary benefits providers are equipped to offer an industry-leading AI-powered consumer benefits experience, featuring Smart Moments and Insights. Benefitfocus President & CEO Ray August introduced the enhancements at Carrier Place 2019, the executive forum for leaders from the nation's top health insurance carriers and voluntary and supplemental benefits providers held at The Sanctuary on Kiawah Island Golf Resort, at Kiawah Island, SC. In his keynote address, August highlighted the capabilities and value provided by BenefitSAIGE and emphasized the scale of AI-enabled operations demonstrated over the past week with 200K Smart Moment alert messages being generated by the MarketPlace Exchange integration engine.


5 ways to use artificial intelligence (AI) to improve business efficiency

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Regardless of a company's size or type, its executives typically look for ways to help it operate as efficiently as possible. They understand the link between efficiency and profitability. If employees waste too much time with drawn-out processes or complicated tasks, it'll be hard for the enterprise to remain profitable and adapt to challenges. Fortunately, artificial intelligence (AI) supports the need for effective business operations. Here are five ways enterprises can use AI for help: Chatbots are an increasingly popular option for businesses to try, and they use AI to work.


Global Artificial Intelligence Platforms Market 2019-2023 Rise in Demand for AI-Based Solutions to Boost Growth Technavio

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The global artificial intelligence platforms market size is poised to reach USD 6.95 billion by 2023, according to a new report by Technavio, progressing at a CAGR of over 28% during the forecast period. This press release features multimedia. "Apart from the rise in demand for AI-based solutions, the rising adoption of AI-enabled chips, the increasing interoperability among neural networks, and increasing convergence of AI with IoT and blockchain, are some other major factors that will drive market growth during the forecast period," says a senior analyst at Technavio. The market is driven by the rise in demand for AI-based solutions. In addition, increasing investments in R&D for AI technology are anticipated to further boost the artificial intelligence platforms market during the forecast period.


Separating Hype from Reality: Exploring AI in IT Service Management

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IT service teams have been under continuous pressure about two matters for quite some time now. On the one hand, they must to do more with less. On the other, they need to deliver superior customer service and reduce downtime. We have seen that the complexity of these issues has also increased to a significant extent. Artificial intelligence and machine learning are a helpful solution to all these issues.


Drone, AI And Big Data: Govt's Plan To Digitally Map India By Investing INR 1000 Cr In 5 Years

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Prof Ashutosh Sharma, secretary to the government (Ministry of Science and Technology) reportedly said that the government has initiated a project to digitally map the country with a resolution of 10 centimetres, using drones and technologies such as artificial intelligence and big data. The Survey of India, a part of the Department of Science and Technology, started on the project a few months ago and has chalked out a five-year plan to complete the project. The survey has started the exercise in Maharashtra, Karnataka and Haryana. "The project will be extended to other states but the respective government should show interest and also provide some financial support," Sharma said. The project, which is expected to cost INR 1000 Cr, is also mapping the entire Ganga basin from the beginning to the end, 25 km from either sides of the banks with an accuracy of 10 cm.


Harnessing machine learning to make managing your storage less of a chore

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While the words "artificial intelligence" generally conjure up visions of Skynet, HAL 9000, and the Demon Seed, machine learning and other types of AI technology have already been brought to bear on many analytical tasks, doing things that humans can't or don't want to do--from catching malware to predicting when jet engines need repair. As the scale and complexity of storage workloads increase, it becomes more and more difficult to manage them efficiently. Jobs that could originally be planned and managed by a single storage architect now require increasingly large teams of specialists--which sets the stage for artificial intelligence (née machine learning) techniques to enter the picture, allowing fewer storage engineers to effectively manage larger and more diverse workloads. Storage administrators have five major metrics they contend with, and finding a balance among them to match application demands approaches being a dark art. Throughput: Throughput is the most commonly understood metric at the consumer level.