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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. Failure to provide timely and accurate answers erodes user trust, hinders adoption, and harms retention.

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What the NIS2 Directive means for application security

Dynatrace

The Network and Information Systems 2 (NIS2) Directive, which goes into effect in Oct 2024, aims to enhance the security of network and information systems throughout the EU. NIS2 is an evolution of the Network and Information Systems (NIS) Security Directive, which has been in effect since 2016.

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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. That’s where causal AI can help.

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Causal AI use cases for modern observability that can transform any business

Dynatrace

That’s why causal AI use cases abound for organizations looking to build more reliable and transparent AI systems. Understanding complex systems Causal AI holds great importance for achieving full-stack observability in complex systems. More generally, causal AI can contribute to explainable and fair AI systems.

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Fueling the next wave of IT operations: Modernization with generative AI

Dynatrace

Teams require innovative approaches to manage vast amounts of data and complex infrastructure as well as the need for real-time decisions. Others involve introducing new threats as AI becomes more integrated into IT systems as a whole. At the same time, challenges remain as organizations aim to become more automated.

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RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

As organizations train generative AI systems with critical data, they must be aware of the security and compliance risks. Hybrid cloud infrastructure explained: Weighing the pros, cons, and complexities – blog While hybrid cloud infrastructure increases flexibility, it also introduces complexity.