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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.

Track Errors in FastAPI for Python with AppSignal

When you first try a new library or framework, you are excited about it. However, as soon as you run something on production, things are less than ideal — an error here, an exception there - bugs everywhere! You start reading your logs, but you often lack context, like how often an error happens, in what line, etc. Fortunately, tools such as AppSignal can help. AppSignal helps you track your errors and gives you a lot of valuable insights.

Avoid flaky end-to-end tests due to poorly hydrated Frontends with Playwright's toPass()

In this video we'll dive into the world of flaky tests in Playwright and synthetic monitoring with Checkly. We examine a site with poor Frontend hydration patterns, their effect on test stability, and how to work around them. Learn how to avoid using artificial delays and implementing a retry mechanism with Playwright's 'toPass()' method to achieve stable testing instead.

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.

Cracked Screen? Here's What You Need to Know About Smartphone Repair

Life has an uncanny way of surprising us, usually when we least expect it. One of the most common and frustrating surprises is dropping our mobile phones. The sound of a phone hitting the ground is akin to a minor heartbreak, mainly when you pick it up to find a web of cracks sprawling across the screen. If this has happened to you, you're certainly not alone. But fear not! This comprehensive blog is designed to walk you through every step, from assessing the damage to preventing future mishaps.

Why you should monitor microservice mediator APIs

Microservice mediator APIs provide a flexible, scalable, and decentralized approach to microservices communication, enabling organizations to build robust, modular, and maintainable applications. They shield microservices from the details of the other implementations and promote loose coupling, helping to ensure autonomy, scalability, and independence among microservices.

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.

Continual Learning in AI: How It Works & Why AI Needs It

Like humans, machines need to continually learn from non-stationary information streams. While this is a natural skill for humans, it’s challenging for neural networks-based AI machines. One inherent problem in artificial neural networks is the phenomenon of catastrophic forgetting. Deep learning researchers are working extensively to solve this problem in their pursuit of AI agents that can continually learn like humans.