It’s not a surprise that in today’s challenging economic landscape, rising costs pose a significant threat to the telecommunications industry. Consider that in 2022, Bain Capital was predicting that Telcos would grapple with increased personnel and escalating operating costs due to inflation. And here we are.

Businesses that are best able to leverage data have a significant competitive advantage. This is especially true in financial services, an industry in which leading organizations are in constant competition to develop the most responsive, personalized customer experiences. Often, however, legacy infrastructure, data silos, and batch systems introduce significant technical hurdles.

The rise of AI brings unprecedented opportunities, deeply rooted in the transformative power of data. As organizations strive for smarter, faster outcomes—whether accelerating product launches, streamlining supply chains, improving customer experiences, or enhancing workforce productivity—they must address five key needs for enterprise AI adoption: Move/ Transform - To effectively adopt AI, companies need to bring together and transform data of all types from all sources.

Google regularly updates its developer policies to make sure Google Play is a safe and trustworthy platform for everyone. While this is unquestionably necessary and essential to protect users and their data, keeping up with the latest changes to ensure applications remain safe and compliant can feel a little overwhelming for developers.

Fivetran's new offering simplifies data lake table maintenance, delivering optimized, query-ready data that is always in sync.

In the digital age, understanding the pulse of public interest is crucial for web professionals. AnswerThePublic, a cutting-edge search listening tool, has emerged as a vital resource for tapping into the collective inquiries of internet users worldwide. With over 15 years of experience in content strategy, many experts have seen tools come and go, but AnswerThePublic stands out for its ability to transform raw search data into actionable insights.

After Twitter moved from Ruby to Scala in 2009, the story was born that Ruby on Rails can’t scale. The story goes that it lacks robustness, is a memory hog, and lacks the concurrency features you need to grow an application. This has been the prevailing wisdom for over a decade. And then along came Shopify, showing that, as Lutke says, Ruby on Rails is a framework that can process billions of events per day and evidently does scale. Ruby on Rails is an excellent candidate for scaling.

There are many ways AI can improve government case management processes. Examples include: AI capabilities often depend on a large language model (LLM), an advanced AI system that can understand, analyze, interpret, and generate human language. It uses deep learning techniques to predict and produce coherent text based on input prompts. A large language model trained on government agency data is capable of tasks like text extraction, translation, summarization, and conversational responses.

Enjoy reading this blog post written by our experts or partners. If you want to see what Databox can do for you, click here. Google “landing page statistics” and you’ll find plenty of statistics for landing page performance in all businesses, but not so much for specific niches. If you work in B2B SaaS or tech, you know that your audience has specific needs that a one-size-fits-all approach can’t meet.

We are excited to announce a tech preview of Cloudera AI Inference service powered by the full-stack NVIDIA accelerated computing platform, which includes NVIDIA NIM inference microservices, part of the NVIDIA AI Enterprise software platform for generative AI. Cloudera’s AI Inference service uniquely streamlines the deployment and management of large-scale AI models, delivering high performance and efficiency while maintaining strict privacy and security standards.