Systems | Development | Analytics | API | Testing

A Software Engineer's Tips and Tricks #4: Collaborating on Visual Studio Code with Live Share

Hey there! We're back for our third edition of Tips and Tricks, our new mini series where we share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Catch up on the previous posts: All of our posts are super short reads, just a couple of minutes tops. If you don’t like one of the posts, no problem! Just skip it and check out the next one. If you enjoy any of the topics, I encourage you to check out the "further reading" links.

Maintaining Mobile App Quality at Scale with Mobile App Testing

The success of your mobile app depends not just on how well the application is working at first, but also on its consistent delivery of excellent user experience. Customers today have an extensive range of alternatives in this rapidly evolving & competitive mobile market. Any problem with the application's performance and user experience can lead to users being discontent with the mobile app. This results in users abandoning the application.

What is Intelligent Process Automation? 5 Key Facts

As generative AI grows in popularity and enterprises scramble to embrace new technology in a scalable, compliant way, it can be difficult to know the right path forward. Your enterprise has already invested in automating processes to free up resources and improve organizational efficiency, but is it enough? This is where intelligent process automation comes into play.

GitTogether | GenAI & Open Source | Kunal Deo

The resurgence of Artificial Intelligence (AI) in recent years owes much to a pivotal moment: the publication of a groundbreaking paper by Google. This event underscores the significant role of Open Source in advancing AI technologies. In this presentation, we delve into how Open Source is not just influencing but also shaping the landscape of Generative AI (GenAI). However, our focus extends beyond the traditional dichotomy of Open Source versus proprietary technologies. Instead, we explore the complementary nature of both realms in fostering the development of the AI ecosystem.

Introducing Cloudera's AI Assistants

In the last couple of years, AI has launched itself to the forefront of technology initiatives across industries. In fact, Gartner predicts the AI software market will grow from $124 billion in 2022 to $297 billion in 2027. As a data platform company, Cloudera has two very clear priorities. First, we need to help customers get AI models based on trusted data into production faster than ever.

ClearML Supports Seamless Orchestration and Infrastructure Management for Kubernetes, Slurm, PBS, and Bare Metal

Our early roadmap in 2024 has been largely focused on improving orchestration and compute infrastructure management capabilities. Last month we released a Resource Allocation Policy Management Control Center with a new, streamlined UI to help teams visualize their compute infrastructure and understand which users have access to what resources.

How ClearML Helps Teams Get More out of Slurm

It is a fairly recent trend for companies to amass GPU firepower to build their own AI computing infrastructure and support the growing number of compute requests. Many recent AI tools now enable data scientists to work on data, run experiments, and train models seamlessly with the ability to submit their jobs and monitor their progress. However, for many organizations with mature supercomputing capabilities, Slurm has been the scheduling tool of choice for managing computing clusters.