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How to run a custom version of Spark on hosted Kubernetes

O'Reilly Media - Data

integrates with K8s clusters on Google Cloud and Azure. We will help you deploy code that hasn't even been reviewed yet (if that is the adventure you seek). This post will help you try out new (2.3.0+) and custom versions of Spark on Google/Azure with Kubernetes. Learn how Spark 2.3.0+ This is the blog post for you, my friend!

Azure 179
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How guardrails allow enterprises to deploy safe, effective AI

CIO

Google has finally fixed its AI recommendation to use non-toxic glue as a solution to cheese sliding off pizza. The company uses the GPT-4 family of gen AI models on the Azure OpenAI service, and decided to go with the guardrails available within that platform to build its Rebot chatbot. It can be harmful if ingested.

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Review of Industrial IoT Solutions – Part I

Perficient

It would take way too long to do a comprehensive review of all available solutions, so in this first part, I’m just going to focus on AWS, Azure – as the leading cloud providers – as well as hybrid-cloud approaches using Kubernetes. Introduction. Edge computing and more generally the rise of Industry 4.0 Solution Overview.

IoT 69
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Airline Reservation Systems and Passenger Service Systems: Navitaire, Amadeus Altea, SabreSonic and more

Altexsoft

Except that we are describing real-life situations caused by small failures in the computer system. And that episode was not a one-off. If passengers are stranded at the airport due to IT disruptions, a passenger service system (PSS) is likely to be blamed for this. The first generation: legacy systems.

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Should you build or buy generative AI?

CIO

For generative AI, that’s complicated by the many options for refining and customising the services you can buy, and the work required to make a bought or built system into a useful, reliable, and responsible part of your organization’s workflow. Since the release of ChatGPT last November, interest in generative AI has skyrocketed.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. However, the concept is quite abstract.

DevOps 145
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Automated Claims Processing: Using RPA and Machine Learning to Manage Insurance Claims

Altexsoft

And when it comes to decision-making, it’s often more nuanced than an off-the-shelf system can handle — it needs the understanding of the context of each particular case. The insurance industry is notoriously bad at customer experience. Not in China though. Of course, not.