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PagerDuty Study Reveals Security Concerns Are Slowing Adoption of GenAI Among the World's Largest Companies

98% of top tech execs paused their corporate genAI initiatives to establish policies. Execs say that a trusted technology partner is key to incorporating genAI into their organizations.

Leveraging LLM/Gen-AI for Accelerating Left-Shift Operations Transformation

In today’s digital landscape, delivering a flawless customer experience is the ultimate competitive advantage. However, traditional methods of ensuring service resilience during operation can often be both expensive and cumbersome to maintain. This is where left-shift operations come into play—a powerful strategy aimed at instilling quality and resiliency in the early stages of building and delivering high-quality products and services..

AI Explainer: Feature Extraction

In a previous blog post, which was a glossary of terms related to artificial intelligence, I included this brief definition of "feature extraction": Let’s go a bit deeper on that. In the ever-expanding landscape of machine learning, feature extraction stands out as a crucial technique for enhancing the performance of models and uncovering valuable insights from complex datasets.

Generative AI with Ubuntu on AWS. Part II: Text generation

In our previous post, we discussed how to generate Images using Stable Diffusion on AWS. In this post, we will guide you through running LLMs for text generation in your own environment with a GPU-based instance in simple steps, empowering you to create your own solutions. Text generation, a trending focus in generative AI, facilitates a broad spectrum of language tasks beyond simple question answering.

How to automate image analysis with the ChatGPT vision API and Grafana Cloud Metrics

OpenAI’s ChatGPT has an extraordinary ability to process natural language, reason about a user’s prompts, and generate human-like conversation in response. However, as the saying goes, “a picture is worth a thousand words” — and perhaps an even more significant achievement is ChatGPT’s ability to understand and answer questions about images.

5 AI-Driven Tools That Can Improve Content Quality

Any concerns you had before clicking on this article about artificial intelligence (AI) generated content should be immediately dispelled. There were some noticeable concerns among writers about AI-generated content not being good enough. At the start, I despised using AI for the longest time and refrained from using it as I considered it an insult to my intelligence and skills. That was before I started using AI tools on a colleague’s request for the first time around two months ago.

The Impact of AI on Cybersecurity

Explore the fusion of Artificial Intelligence (AI) and cybersecurity, unlocking the secrets behind AI’s transformative influence in digital asset protection, during our exclusive webinar, “Enhance Your Cybersecurity by Harnessing the Power of AI.” Our product expert will discuss the wide-reaching impact of AI and teach attendees how to navigate dynamic cybersecurity trends and the ever-evolving threat landscape.

Steps to Taming Hybrid Cloud Complexity: Eliminating Visibility Gaps & Enabling Actionable AI-Powered Insights

For years “the move to the cloud” implied a singular event – a singular migration to a singular entity. It all sounded so simple. Yet, the “simple” act of moving to the cloud stands in stark contrast to the reality of today’s complex, hybrid IT estates where the overwhelming volume of data flows can make it challenging for IT teams to effectively pinpoint and rectify service incidents.

Advantages of an AI-Powered Observability Pipeline

The expenses associated with collecting, storing, indexing, and analyzing data have become a considerable challenge for organizations. This data is growing as fast as 35% a year, multiplying the problems. This surge in data comes with a corresponding rise in infrastructure costs. These costs often force organizations to make decisions about what data they can afford to analyze, which tools they must use, and how and where to store data for long-term retention.

Ubuntu AI | S2E4 | AI on public cloud: what should you know?

Weka report from 2024 showed that 47% of respondents will use the public cloud as the primary place to develop their machine learning projects. This is a result of a correlation of factors which include the need for compute power, easy scalability, and the ability to utilise existing infrastructure already in place on both hybrid clouds and public clouds. Join us to talk more about AI on the public cloud: what are the main benefits and what are the best practices an organisation could implement in order to easier adopt AI and leverage the most the public clouds.