Google Cloud’s Latest AI, ML Updates and More

Source:-https://www.uctoday.com Artificial intelligence is used in loads of business scenarios. In some instances, organizations use data and machine learning to solve some of their most challenging problems, and have seen incredible returns. According to McKinsey Global Institute, the companies that absorb AI in their workflows by 2025 are set to dominate the 2030 world economy. McKinsey even forecasts colossal growth, predicting 120 percent above cash-flow increases, a fairly significant number that Google Cloud hopes to capitalize on. Recently the cloud

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Microsoft explains how it improved automatic image captioning in Azure Cognitive Services

Source:-https://venturebeat.com Microsoft today launched a new computer vision service it claims can generate image captions that are, in some cases, more accurate than human-written descriptions. The company calls the service, which is available as part of Azure Cognitive Services Computer Vision, a “significant research breakthrough” and an example of its commitment to accessible AI. Automatic image captioning has a number of broad use cases, first and foremost assisting users with disabilities. According to the World Health Organization, the number of

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Efficient MLOps in a Kubernetes Environment

Source:-containerjournal.com MLOps addresses the specific needs of data science and ML engineering teams without impacting Kubernetes If your organization has already started getting into machine learning, you will certainly relate to the following. If your organization is taking its first steps into data science, the following will illustrate what is about to be dropped on you. If none of the above strikes a chord this might interest you nonetheless, because AI is the new frontier and it won’t be long

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Opening The Door To Innovation With Data Superpowers

Source:-forbes.com Helping your data teams do their jobs means empowering them to work efficiently and without barriers. This article looks at how AI and ML technologies can empower your teams to help your business grow, and how to make modern data analytics work for you. Last week, I celebrated my first anniversary as general manager and VP of engineering for our data analytics platform here at Google Cloud. Despite all the unprecedented experiences we’ve had this year, we’re thankful to

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10 Ways AI Is Accelerating DevOps

Source:-forbes.com Startups offering AI-powered software development tools raise $704M over 12 months ending September 2019, according to a Deloitte report published earlier this year. IDC predicts the global market for custom application development services is forecast to grow from $47B in 2018 to more than $61B in 2023, attaining a 5.3% Compound Annual Growth Rate (CAGR) in five years. Poor software quality cost US organizations an estimated $319B in 2019, according to the Consortium for IT Software Quality’s report on

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Persistent Achieves AWS SaaS Competency Status

Source:-aithority.com Recognizes deep cloud-based expertise building digital mosaics across key verticals Persistent Systems has achieved Amazon Web Services (AWS) Software-as-a-Service (SaaS) Competency status. This designation recognizes that Persistent has demonstrated deep experience helping organizations design and build SaaS and cloud-native solutions on AWS. Persistent is a global solutions company that excels at delivering digital business acceleration and enterprise modernization for organizations across industries such as banking/financials services, healthcare and life sciences, and the industrial sector. Achieving the AWS SaaS Competency

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The 7-Step plan for successful AIOps implementations

Source:-softwaretestingnews.co.uk The idea of applying artificial intelligence and machine learning to more rapidly and accurately resolve IT incidents and manage alerts has been gaining steam in the past year. While AIOps, as it’s frequently called, has spawned an entirely new market of startups, many enterprise IT leaders are playing a cautious hand so far – and for good reason. There are risks, though. If an AIOps tool goes wrong out of the gates, IT and executive trust diminishes. That’s why

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What would machine learning look like if you mixed in DevOps? Wonder no more, we lift the lid on MLOps

Source:-theregister.co.uk And why do such a thing? Well, how else will you push your artificially intelligent software into production? Achieving production-level governance with machine-learning projects currently presents unique challenges. A new space of tools and practices is emerging under the name MLOps. The space is analogous to DevOps but tailored to the practices and workflows of machine learning. Why MLOps is Needed Machine learning models make predictions for new data based on the data they have been trained on. Managing

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Google Cloud reveals new offerings for telcos, pairs with AT&T

Source:-totaltele.com AT&T will be the first operator to explore the possibilities of Google’s Global Mobile Edge Cloud AT&T will be looking to maximise the potential of mobile edge computing after its latest deal with Google Cloud was announced on Thursday. The company will be seeking to leverage Google’s new Global Mobile Edge Cloud (GMEC) service. The new service will effectively bring Google’s Cloud capabilities to the edge of AT&T’s network, allowing greater implantation of Google’s varied tech, such as AI,

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The Pros and Cons of Google’s New AI Transparency Tools

Source:-insidebigdata.com In this special guest feature, Jay Budzik, CTO at ZestFinance, discusses the set of developer tools that Google launched that allow data scientists to create explainable ML models, and also the reality of these new tools and how they are likely to impact the financial services market. ZestFinance is a software company that helps banks and lenders build, run, and monitor fully explainable machine learning underwriting models. As CTO, Jay oversees Zest’s product and engineering teams. His passion for

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