Adobe's Experience Cloud now incorporates AI and machine learning

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Software giant Adobe announced the release of its new customer service tool called Adobe Experience Platform. The platform gives enterprises greater data governance capabilities, general access to Adobe's Customer Data Platform service, and avenues for more personalized and impactful customer interactions, the company said. Adobe has revamped Adobe Experience Cloud to incorporate its AI and machine learning platform, named Adobe Sensei. The service will help businesses with digital marketing, advertising, analytics, commerce and more. In a release, the company called Adobe Experience"the industry's first open and extensible platform that stitches data across the enterprise," and said it gave organizations the ability to map out the potential customer experience through "customer journey orchestrations."


10 tech predictions for 2020 and beyond

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Gartner has unveiled its biggest predictions for IT organisations and users for 2020 and beyond. These predictions analyse how technology is changing society and the expectations of users. "Technology is changing the notion of what it means to be human," said Daryl Plummer, VP and Fellow at Gartner. "CIOs in end-user organizations must understand the effects of the change and reset expectations for what technology means." "This year's predictions help us move beyond thinking about mere notions of technology adoption and draw us more deeply into issues surrounding what it means to be human in the digital world," said Plummer.


6 essentials for fighting fraud with machine learning

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Data: As with all ML applications, quality data is foundational to building anti-fraud ML systems. Data sets are only growing larger, and as the volumes increase, so does the challenge of detecting fraud. Thankfully the adage that more data equals better models is true when it comes to fraud detection. The make-or-break factor is having a ML platform that can scale as data and complexity increase. Multiplicity: There's no single ML algorithm or method that works best for fraud detection.


The 4 Research Techniques to Train Deep Neural Network Models More Efficiently

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Deep learning and unsupervised feature learning have shown great promise in many practical applications. State-of-the-art performance has been reported in several domains, ranging from speech recognition and image recognition to text processing and beyond. It's also been observed that increasing the scale of deep learning--with respect to numbers of training examples, model parameters, or both--can drastically improve accuracy. These results have led to a surge of interest in scaling up the training and inference algorithms used for these models and in improving optimization techniques for both. The use of GPUs is a significant advance in recent years that makes the training of modestly-sized deep networks practical.


Artificial Intelligence Applications Most adopted AI Technologies

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Artificial Intelligence Application is a subject widely prevalent in the IT world for more than 4 decades and it was in the laboratory all through. AI is all about building intelligence into machines to enable it to perform human tasks with precision for the known operations. It also packs machines with a lot of data points for the machines to learn and handle unknown situations. AI simulates machines to work, learn, think and react like human beings. In this article let's see the applications developed using AI technologies.


Salesforce adds AI, interactive components to its email platform - MarTech Today

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Salesforce has announced updates to its Marketing Cloud email solution to support new inbox functionalities provided by several major Internet Service Providers (ISPs). The new features include Salesforce's AI solution, Einstein and interactive email capabilities that could serve as an alternative solution to AMP for Email. The interactive capabilities will be integrated from the company's acquisition of Rebel beginning early next year. Email consistently outperforms other digital channels as an ROI driver for marketers, but consumer expectations keep climbing. Studies show that personalization is a key driver of engagement and sales.


Can you sing like Freddie?

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People love singing with Freddie Mercury, but can you sing like Freddie too? We made an AI-powered singing challenge to find out. This experiment uses new, on-device machine learning models developed by Google Research to see how close your timbre, pitch, and melody are to Freddie's. Your audio doesn't get uploaded to servers to be analyzed, so your vocals stay private. FreddieMeter was made with The Mercury Phoenix Trust, a charity founded by Brian May, Roger Taylor, and their manager Jim Beach in memory of Freddie Mercury, who died in 1991 from AIDS-related causes.


Portrait-Painting A.I. Uses Brush and Canvas

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Artist Pindar Van Arman has been painting his entire life. But for the last 10 years he's been trying to delegate some of the work. Van Arman's bitPaintr project is a robotic system that paints portraits using customized robotic artificial intelligence. Unlike photo booth computer portraits - which are essentially just printers - the bitPaintr bot uses real brushes, paints and canvas. "It paints using it's own artificial intelligence and my artistic direction," Van Arman says on his intriguing Kickstarter page.


Investorideas.com Newswire - The AI Eye: Apple (Nasdaq:AAPL) and Salesforce (NYSE: CRM) Launch AI-Powered App, Intel (Nasdaq: INTC) Unveils oneAPI

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Apple (NasdaqGS:AAPL) and Salesforce (NYSE:CRM) have announced the launch of two new apps, including the AI-powered redesigned Salesforce Mobile App with features exclusive to iOS and iPadOS. "With Salesforce Mobile, Salesforce and Apple are empowering sales, service and marketing professionals on the go to deliver game-changing customer experiences, powered by AI. And with Trailhead GO, millions more can now skill up for free, anytime and anywhere, to learn in-demand skills and fill the jobs of today and tomorrow." Intel Corporation (NasdaqGS:INTC) has unveiled oneAPI, "a unified and scalable programming model to harness the power of diverse computing architectures in the era of HPC/AI convergence", and "a general-purpose GPU optimized for HPC/AI acceleration based on the Xe architecture". "HPC and AI workloads demand diverse architectures, ranging from CPUs, general-purpose GPUs and FPGAs, to more specialized deep-learning NNPs, which Intel demonstrated earlier this month. Simplifying our customers' ability to harness the power of diverse computing environments is paramount, and Intel is committed to taking a software-first approach that delivers a unified and scalable abstraction for heterogeneous architectures."


Building an open ML platform with Red Hat OpenShift and Open Data Hub Project – Red Hat OpenShift Blog

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The Open Data Hub project integrates a number of open source tools to enable an end to end AI/ML workflow. Jupyter notebook ecosystem is provided as the primary interface and experience to the data scientist. And the main reason for that is that Jupyter is widely popular amongst data scientists today. Data scientists can create and manage their Jupyter notebooks workspaces with an embedded JupyterHub. While they can create or import new notebooks, Open Data Hub project also includes a number of pre-existing notebooks called the "AI Library".