Introducing six Rootly AI features: focus on the incident, leave the paperwork to us
Say hello to smarter incident management with smart summaries, mitigation message suggestions, and our new conversational assistant! 🚀✨
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Using AI-Powered Functional Testing Tools for Faster QA Automation Testing
Software automation testing has changed dramatically in the last several years, with an obvious trend toward automated testing techniques. Although manual testing processes are still an essential part of the testing process, test automation adoption has become more and more important in many situations. The fact that an astounding 97% of application testers have already included automated testing into their processes serves as evidence of this evolution. Developers are using AI-powered functional testing solutions to speed up QA automation testing procedures as they realize how important this trend is.
How to Make the Most of Your Salesforce Value: What to Try to Implement
Nowadays, leading a business means having to do with customer data a lot. Since Salesforce is one of the main on-cloud CRM platforms out there, and chances are that you have already used it and continue to build customer relationships through it, there is huge potential in the system. Uncovering this potential is a part of success, so get ready to collect some new tips on how to better support clients, sell, market, connect with partners, and more.
Large Language Models (LLMs) Retrieval Augmented Generation (RAG) using Charmed OpenSearch
Large Language Models (LLMs) fall under the category of Generative AI (GenAI), an artificial intelligence type that produces content based on user-defined context. These models undergo training using an extensive dataset composed of trillions of combinations of words from natural language, enabling them to empower interactive and conversational applications across various scenarios.
New Release: Integrated GenAI, Enhanced Monitoring, and More
Selector is excited to give a sneak peek into new features to be included in our forthcoming Spring Release. This release highlights key innovations focusing on integrated generative AI (GenAI) to enable guided troubleshooting and automated incident remediation. It also includes enhancements to several existing features, such as root cause analysis, native monitoring, and observability capabilities.
Embark on your AI adoption journey with help from a master orchestrator
In all my blog posts so far, I have been providing suggestions on how to expedite your AI adoption journey. I believe it is now time to describe what we are doing here at Digitate: Helping enterprises to become a ticketless business. Even though this is the same adoption journey that I have been describing, it has a different perspective; I’m turning my focus “lens” from outward to inward.
Machine learning vs. AI: Understanding the differences
For a long time, AI was almost exclusively the plaything of science fiction writers, where humans push technology too far, to the point it comes alive and — as Hollywood would have us believe — starts to wreak havoc. Cheery stuff! However, in recent years, we’ve seen an explosion of AI and machine learning technology that, so far, has shown us a fun side with people using AI for creating, planning, and ideating in a big way.
Azure Open AI Landing Zone Blueprint
In recent years, artificial intelligence (AI) has emerged as a pivotal technology to advance cloud computing, driving innovation and greater efficiency. Among the myriad of AI services available, the Azure OpenAI Service, born from the collaboration between Microsoft and OpenAI, stands out for its robust capabilities and seamless integration with cloud environments.
How to make a chatbot: Dos and don'ts for developers in an AI-driven world
Every day the world is becoming increasingly powered by artificial intelligence. In fact, you’d struggle to find tech companies that have not announced AI integrations into their tech stack in one way or another. Cynics might say this is a passing phase, but the reason AI is so popular is that it’s a versatile set of capabilities that can help solve a lot of problems.
PostgreSQL for AI applications
If you’re working with AI, you’re working with data. From numerical data to videos or images, regardless of your industry or use case, every AI project depends on data in some form. The question is: how can you efficiently store that data and use it when building your models? One answer is PostgreSQL, a proven and well-loved database that, thanks to recent developments, has become a strong choice to support AI.