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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. The LLM then synthesizes the retrieved data with the augmented prompt and its internal training data to create a response that can be sent back to the user. million AI server units annually by 2027, consuming 75.4+

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Building In-Video Search

The Netflix TechBlog

In order to train the model on internal training data (video clips with aligned text descriptions), we implemented a scalable version on Ray Train and switched to a more performant video decoding library. These models are trained on large amounts of image-caption pairs via in-batch contrastive learning.

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Measuring the importance of data quality to causal AI success

Dynatrace

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. Because IT systems change often, AI models trained only on historical data struggle to diagnose novel events. That’s where causal AI can help.

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. There are several ways to provide explainability to models but one way is to train an explainer model based on each trained model.

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

Dynatrace

As a result, organizations are turning to AI to automate tasks—from code development to incident response—to reduce manual effort and human error, and to boost workforce efficiency. Artificial intelligence, including more recent advances in generative AI , is becoming increasingly important as organizations look to modernize how IT operates.

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IT carbon footprint: Dynatrace Carbon Impact and Optimization app helps organizations measure cloud computing carbon footprint

Dynatrace

As global warming advances, growing IT carbon footprints are pushing energy-efficient computing to the top of many organizations’ priority lists. Energy efficiency is a key reason why organizations are migrating workloads from energy-intensive on-premises environments to more efficient cloud platforms.

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Reignite Your SAFe® Journey with Flow Metrics

Tasktop

We must have a deep understanding of what changes will have the biggest impact on velocity, predictability, efficiency, throughput and so on.”. That’s why I’m so excited to see Flow Metrics added to the latest SAFe iteration. That’s why I’m so excited to see Flow Metrics added to the latest SAFe iteration. A Flow-Based System.

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