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4 elements of AI copilots for incident management

Generative AI has immense potential to transform how IT operations, service management, and infrastructure teams function. However, integrating GenAI technologies, like copilots, often brings significant challenges, such as ensuring accuracy, addressing job displacement concerns, and demonstrating tangible value. Navigating the landscape of various vendors and implementation hurdles can be time-consuming and resource-intensive.

Embedded World North America 2024 Recap

Last week, a handful of Memfolks had the opportunity to travel to Austin to attend the first ever Embedded World North America1! Embedded World NA welcomed 3,500 visitors and 180 vendors across 3 days2. While it was surely a smaller showing than Nueremburg’s Embedded World, we still wanted to quickly touch on our takeaways from the event. In this post, we will cover what we learned from the first Embedded World North America.

Transform ITOps and incident management with AI copilots

There are many ways to apply generative AI to modernize IT operations. Advances in GenAI have paved the way for the development of AI-powered ITOps copilots, which have the potential to transform IT operations. AI copilots offer many benefits for IT, including improved decision-making, accelerated incident management timelines, and optimized workflows.

How Generative AI Is Revolutionizing Debugging

In the rapidly evolving landscape of software development, the integration of generative AI has become a game-changer for organizations striving to deliver high-quality software at scale. Among its many transformative applications, autonomous debugging stands out as a critical advancement, offering the potential to revolutionize the way development teams tackle errors and maintain operational efficiency.

How search accelerates your path to "AI first"

The combination of AI and search enables new levels of enterprise intelligence, with technologies such as natural language processing (NLP), machine learning (ML)-based relevancy, vector/semantic search, and large language models (LLMs) helping organizations finally unlock the value of unanalyzed data. Search and knowledge discovery technology is required for organizations to uncover, analyze, and utilize key data.

The Role of AI in Modern Job Applications: Tools and Techniques for the Digital Age

In the digital age, the landscape of job applications has evolved dramatically, and Artificial Intelligence (AI) plays a pivotal role in this transformation. Traditional paper resumes and cover letters have given way to dynamic digital tools designed to streamline and enhance the job application process. AI technologies are now at the forefront, offering job seekers and employers innovative ways to connect more efficiently and effectively.

Is AI Really What Home Health Providers Need Right Now?

If you want to make your vehicle go faster, you might be compelled to put in an engine that will give you more horsepower. But if that vehicle is a 20-year-old minivan with a suspension that can’t handle the extra horsepower, you’re not going to get anywhere, much less get there faster. You must first upgrade the suspension to be able to handle the higher-speed turns or you’re going to have a lot more problems to deal with.

Shaping the Next Generation of AI-Powered Observability

Observability is crucial for maintaining complex systems’ health and performance. In its traditional form, observability involves monitoring key metrics, logging events, and tracing requests to ensure that applications and infrastructure run smoothly. The emergence of Artificial Intelligence (AI) promises to revolutionize the way organizations approach observability.

PagerDuty Introduces Enterprise-Grade, AI-Powered Innovations to Future-Proof Operations and Improve Business Results

Strategic enhancements built on PagerDuty's strong AI heritage expand the PagerDuty Operations Cloud, empowering organizations by protecting them from revenue loss and improving customer trust.

An Introduction to AI Inference

As a straightforward definition, AI inference is the process of applying a pre-trained machine learning model to new, unseen data in order to generate predictions, classifications, or decisions. Unlike the training phase, where the model learns from a dataset, inference involves utilizing the learned patterns to analyze and interpret new inputs.