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For your eyes only: improving Netflix video quality with neural networks

The Netflix TechBlog

For example, we invest in next-generation, royalty-free codecs and sophisticated video encoding optimizations. Recently, we added another powerful tool to our arsenal: neural networks for video downscaling. How can neural networks fit into Netflix video encoding? Video encoding using a conventional video codec, like AV1.

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How AI and observability help to safeguard government networks from new threats

Dynatrace

It’s an approach that’s particularly powerful when teams use it to, for example, automatically identify patterns of security problems (such as unusual data flows) or find the root causes of issues. This blog originally appeared in Federal News Network. When we protect our systems, we’re also protecting them.

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Transforming Telecom With AI/ML: A Deep Dive Into Smart Networks

DZone

With the constant evolution of this sector, the dynamic duo of AI and ML is revolutionizing the telecommunications industry, propelling it towards greater network efficiency, unparalleled customer service, and fortified security measures. Here's an example of how machine learning can optimize network performance:

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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Certain service-level objective examples can help organizations get started on measuring and delivering metrics that matter. Teams can build on these SLO examples to improve application performance and reliability. In this post, I’ll lay out five SLO examples that every DevOps and SRE team should consider. or 99.99% of the time.

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Accelerate resolution of network issues with AI-powered event reporting based on SNMP traps

Dynatrace

Monitoring modern IT infrastructure is difficult, sometimes impossible, without advanced network monitoring tools. While the market is saturated with many Network Administrator support solutions, Dynatrace can help you analyze the impact on your organization in an automated manner. Sample SNMP-enabled device configuration. What’s next?

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Leveraging ML-Based Anomaly Detection for 4G Networks Optimization

DZone

Improving 4G Networks Traffic Distribution With Anomaly Detection Previous generations of cellular networks were not very efficient with the distribution of network resources, providing coverage evenly for all territories all the time.

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CSS and Network Performance

CSS Wizardry

In this post I want to look at how CSS can prove to be a substantial bottleneck on the network (both in itself and for other resources) and how we can mitigate it, thus shortening the Critical Path and reducing our time to Start Render. This is best illustrated with an example. Employ Critical CSS.

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