Today’s IT teams are struggling to make sense of organizational data that has been compiled piecemeal and often stored within disparate storage solutions. Often this information needs to be aggregated and presented in a unified format, yet pulling data from multiple data sources and displaying it in a coherent way can be onerous and error-prone. The challenge is compounded when the data resides in different databases, and possibly within different clouds.

In recent years, cybersecurity has faced increasingly sophisticated threats, making it crucial for organizations to develop robust systems for threat detection and response. One emerging technology that holds promise in this domain is ChatGPT, an advanced natural language processing model developed by OpenAI. In this blog post, we will explore how ChatGPT can be leveraged to enhance threat detection and response in cybersecurity.

This is the third in a series of posts on adding an in-game chat room with React. In the first post, we added a chat room to a game of tic-tac-toe. In the second, we used Presence to add typing indicators that show us when the other person in the chat is typing. With all of that in place, this post will build on our chat app even further.

The rise of AI and LLMs in our world is revolutionizing the applications we’re building and the customer experiences we’re delivering. This is one of the pivotal moments in our industry where we cross over an intersection in our technology evolution to enter a new journey with a paradigm shift. Past intersections were the rise of mobile, the rise of the cloud, and the rise of microservices, among others. Some people may even say that AI is as revolutionary as the birth of the internet.

Ready or not, AI workflow automation is poised to transform business operations from the shop floor to the C-suite in the AI economy. The situation is a byproduct of the generative AI boom. And yet, so many companies have hardly scratched the surface of AI automation’s full potential in their business operations. The more these companies get AI workflow automation to work for them, the more agility, efficiency, productivity, and economies of scale they’ll get back for themselves.

For business and IT leaders, digital transformation in the financial services industry continues to pose a challenge but is necessary to keep pace with changing regulatory requirements, consumer demand, and budget constraints. It's also important to prevent operational areas from growing their expenses unintentionally. In the typical boom and bust cycle, banks can feel pressure to roll out new financial products, services, and business lines.

Casework is an intricate process that involves the assembly and management of a myriad of files, tasks, and personnel. At its core, casework aims to build a comprehensive narrative or profile, drawing together disparate pieces of information to construct a cohesive whole. The complexity of case management arises from the diverse data sources and numerous stakeholders involved in the process.

Across the industry, organizations are attempting to find ways to implement generative AI in their business and operations. But doing so requires significant engineering, quality data and overcoming risks. In this blog post, we show all the elements and practices you need to to take to productize LLMs and generative AI. You can watch the full talk this blog post is based on, which took place at ODSC West 2023, here.

Your opportunity to create a loyal fanbase is locked behind disparate data silos. It’s time to call an audible.

In the ever-changing realm of software development, the concept of mock objects often emerges as a source of optimism amidst the tumultuous testing and debugging process. These simulated objects are not just mere jargon in a developer’s vocabulary; they are vital instruments that imitate the behavior of actual objects in controlled settings.