By Bill McLane With the rapid adoption of AI and the innovation that is happening around large language models we need, at the center of all of it all, the ability to take large amounts of data, contextualize it, process it, and enable it to be searched with meaning. Generative…

by David Dieruf Say you wanted to participate in the popular game show Jeopardy (it’s an American TV game show where contestants are given the answer and have to guess the question). To be on the show you need to know everything about anything. So you decide to dedicate every…

By Aaron Ploetz With all the buzz about large language models, vectors and vector search, it’s important to take a step back and understand how these artificial intelligence technology advancements translate into results for an organization and, ultimately, its customers. In an earlier article, I told the story of a…

By Bill McLane With all the talk about generative AI, the concepts behind what powers generative AI can be a little overwhelming. In this post, we‘ll focus on the one functional concept that powers the underlying cognitive ability of AI and provides machine learning models the ability to learn and…

By Yuqi Du Vector search is a powerful way to bring the magic of generative AI to your applications. And if you have the right tools, it’s not necessarily difficult. …

By Aaron Ploetz The journey to implementing artificial intelligence and machine learning solutions requires solving a lot of common challenges that routinely crop up in digital systems: updating legacy systems, eliminating batch processes and using innovative technologies that are grounded in AI/ML to improve the customer experience in ways that…

Using data APIs and advanced data modeling will make it far easier for JSON-oriented developers to connect to Cassandra. By Mark Stone All applications depend on data, yet application developers don’t like to think about databases. Learning the internals and query language of a particular database adds cognitive load, and…

By Bill McLane When building mission-critical applications such as financial services systems, transportation and logistics control systems, or supply chain management systems, it’s becoming increasingly important to modularize components within those systems and implement a distributed microservices architecture. At the foundation of any distributed micro services architecture there has to…

By Charna Parkey Real-Time AI Done Right: Timely Insight and Action at Scale In my previous blog post, I laid out the challenges of current AI architectures and the inherent limitations they impose on data scientists and developers. These challenges inhibit our ability to take advantage of the growth in real-time data, address increased consumer expectations, adapt to increasingly dynamic…