We are excited to announce the launch of our AI Infrastructure Control Plane, designed as a universal operating system for AI infrastructure. With this launch, we make it easier for IT teams and DevOps to gain ultimate control over their AI Infrastructure, manage complex environments, maximize compute utilization, and deliver an optimized self-serve experience for their AI Builders.

We know it feels like all anyone talks about these days is artificial intelligence. Since the launch of ChatGPT in 2022, the professional world has been abuzz with reactions to this game-changing technology. It’s everywhere – and for good reason. Artificial intelligence (AI) and machine learning (ML) tools have been around for a while, but ChatGPT brought AI into the mainstream in ways that hadn’t been seen before.

Process orchestration, also called business process orchestration, is an approach to manage and organize multiple automated tasks or workflows within a business process, like ETL process orchestration. It involves coordinating data extraction, transformation, and loading tasks across various systems to create a unified data source.

Data modernization transforms an organization’s data into more usable and accessible formats, making it usable by modern applications and systems, such as cloud-native applications, IoT devices, and mobile applications. Data modernization also includes extracting, cleaning, and migrating the data into advanced platforms.

Whether you’re an analyst or non-technical, Yellowfin Stories and Present, our exclusive data storytelling features, make it easy to create and share data-led narratives with peers that provide insightful context, inspires action, and fosters a data-driven culture. Now, it’s no secret Yellowfin have been big believers of data storytelling since day one.

Do you know proactive fraud detection and prevention could save organizations up to a staggering $5.9 billion annually? However, gathering relevant data for this purpose is no easy task. Financial data integration plays a crucial role in the fight against fraud, enabling organizations to merge data from various sources and formats into a unified, consistent view. However, gathering relevant data for this purpose is no easy task.

If 2023 was the year of gen experimentation, 2024 is the year of gen AI implementation. As companies embark on their implementation journey, they need to deal with a host of challenges, like performance, GPU efficiency and LLM risks. These challenges are exacerbated in highly-regulated industries, such as financial services and telecommunication, adding further implementation complexities. Below, we discuss these challenges and present some best practices and solutions to take into consideration.