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Why growing AI adoption requires an AI observability strategy

Dynatrace

As organizations turn to artificial intelligence for operational efficiency and product innovation in multicloud environments, they have to balance the benefits with skyrocketing costs associated with AI. An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance.

Strategy 219
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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. blog Generative AI is an artificial intelligence model that can generate new content—text, images, audio, code—based on existing data. What is generative AI? Learn more about the state of AI in 2024.

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment. At a glance – TLDR.

Big Data 321
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What is AIOps? Everything you wanted to know

Dynatrace

Artificial intelligence for IT operations (AIOps) is an IT practice that uses machine learning (ML) and artificial intelligence (AI) to cut through the noise in IT operations, specifically incident management. They require extensive training, and real-user must spend valuable time filtering any false positives.

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Copyright, AI, and Provenance

O'Reilly

Another group of cases involving text (typically novels and novelists) argue that using copyrighted texts as part of the training data for a Large Language Model (LLM) is itself copyright infringement, 1 even if the model never reproduces those texts as part of its output. What should copyright law mean in the age of artificial intelligence?

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To understand the risks posed by AI, follow the money

O'Reilly

Given that our leading scientists and technologists are usually so mistaken about technological evolution, what chance do our policymakers have of effectively regulating the emerging technological risks from artificial intelligence (AI)? But how much greater are the risks for the next generation of AI systems?

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You Can’t Regulate What You Don’t Understand

O'Reilly

In response, the Association for the Advancement of Artificial Intelligence published its own letter citing the many positive differences that AI is already making in our lives and noting existing efforts to improve AI safety and to understand its impacts. They write: “AI systems are becoming a part of everyday life.