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A CIO's guide to practical AI applications

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There is plenty of talk about artificial intelligence in the enterprise, but a lot of it is not very practical. That's because enterprises aren't equipped with an army of data scientists to build and train new AI models. And it's not just the lack of qualified data scientists -- AI breakthroughs require massive amounts of relevant, annotated data. That doesn't mean however, there is no place for AI in your enterprise innovation strategy. Savvy CIOs are using in-market models and APIs by commercial and industry leaders to solve well-defined use cases, bringing immediate, measurable value to the organization.


12 tips for achieving IT agility in the digital era

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Pre-COVID, agility became an aspiration and rallying cry for organizations seeking to embrace emerging technologies and pursue technology-enabled innovation, often to stave off digital disruption in their industries. Once the pandemic hit, that nice-to-have became an existential necessity. "As CIO, I'm constantly looking at ways to become more agile and using IT as a strategic differentiator," says Scott duFour, global CIO at digital payment solutions company Fleetcor. "This goes beyond implementing agile methodology. It's the ongoing assessment of how we can run our current systems more efficiently to meet our digital transformation goals."


How do you turn data into profits - ET CIO

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Data and analytics capabilities have advanced leaps and bounds in the last few years. And no company wants to stay away from what data can bring to the table. Business have invested large amounts of money in gathering this information and building solutions on top this data. But have they really been able to reach where they wanted to? Have companies really been able to turn data into profits?


Leveraging the power of AI and machine learning for more resilient data centers - ET CIO

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By Sachin Bhalla According to Market Research Company Technavio, the global data center market size is poised to grow by $304.87 million between 2020 and 2024. It will grow at an even faster pace in the Asia-Pacific region. An S&P study reveals that between 2017 and 2022, the Asia-Pacific region would reach an estimated 10% CAGR compared to the global data center industry that is expected to clock a 7% CAGR. The data center industry is undergoing changes to serve the needs in today's business landscape. It comes to no surprise when we hear organisations discuss their plans to enhance their data center infrastructure with technologies like Artificial Intelligence (AI) and focus on automation to improve uptime while controlling costs--all of which are important for companies to drive operational efficiency and business resiliency.


AI in the cloud pays dividends for Liberty Mutual

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Liberty Mutual is one of the most experienced and advanced cloud adopters in the nation. And that is in no small part thanks to the vision of James McGlennon, who in his role as CIO of Liberty Mutual for past 17 years has led the charge to the cloud, analytics, and AI with a budget north of $2 billion. Eight years ago, McGlennon hosted an off-site think tank with his staff and came up with a "technology manifesto document" that defined in those early days the importance of exploiting cloud-based services, becoming more agile, and instituting cultural changes to drive the company's digital transformation. Today, Liberty Mutual, which has 45,000 employees across 29 countries, has a robust hybrid cloud infrastructure built primarily on Amazon Web Services but with specific uses of Microsoft Azure and, lesser so, Google Cloud Platform. Liberty Mutual's cloud infrastructure runs an array of business applications and analytics dashboards that yield real-time insights and predictions, as well as machine learning models that streamline claims processing.


Artificial intelligence: What is an AI product?

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Artificial intelligence has a vocabulary all its own. Just within the field of machine learning, you've got a bevy of terms and concepts to sort out: supervised versus unsupervised ML, deep learning and neural networks, and black box versus explainable AI. If you need to brush up on the lingo fast, try our AI cheat sheet. For a deeper dive, try the executive's guide to real-world AI. Because of this – and because of the outsized enthusiasm and hype that engulfs AI – there is some fundamental confusion around AI and related technologies.


What determines the cost of an AI project - ET CIO

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Artificial Intelligence holds the power to revolutionize the business and its operations. With the wonders this modern technology has done globally, no company wants to stay away from the fruits AI can bring. But before you develop, having an idea of the cost is important. And when you ask a consultant or a vendor how much a certain AI project would cost your company, a typical response is, "Well, it depends." To delve deep into what these dependencies are, ETCIO spoke with data, and AI experts are trying to find out what determines the cost of an AI project and what impacts the same.


Artificial Intelligence (AI) strategy: 4 priorities for CIOs

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It's an exciting and scary time to be a technology leader: Exciting for the endless opportunities offered by rapidly evolving digital technologies – and scary due to the associated feeling of FOMO (fear of missing out). Driven by the desire to tap unprecedented volumes of data for a broad array of real-world applications, many organizations see AI as a magic wand that CIOs can swing to generate customer delight and executive exhilaration. CIOs know better, of course. The challenges that come with any new technology hit technologists harder and faster than the optimism driving it. This is especially true with AI and related areas such as machine learning (ML), data science, deep learning, natural language processing (NLP), and cognitive intelligence.


Interview with Andrea Thomaz (co-founder of Diligent Robotics): socially intelligent automation solutions for hospitals

Robohub

Over the last 6-12 months, the demand has really skyrocketed such that we're barely keeping up with the demand for people wanting to implement robots in their hospitals. That's the reason why we're raising this round of funding, expanding the team, and expanding our ability to capitalize on that demand. A couple of years ago, if we were working with a hospital it was because they had some special funds set aside for innovation or they had a CTO or a CIO that had a background in robotics, but it certainly wasn't the first thing that every hospital CIO was thinking about. Now that has completely changed. We're getting cold outreach on our website from CIOs of hospitals saying "I need to develop a robotic strategy for our hospital and I want to learn about your solution."


Clean Harbors' CIO: Hybrid approach to the cloud is a win-win

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Soon thereafter Clean Harbors took a big leap to Microsoft Azure's AI Cognitive Services and Azure Machine Learning Platforms to gain valuable …