On the Road to AI-First: The Five Speed Bumps Businesses Must Navigate
Becoming an AI-first organization requires that businesses today get foundational digital transformation
Topic: From Our Experts
Top articles from our RTInsights Experts
19 Women in Real-time Analytics and AI to Watch in 2024
2024 is going to be a big year for real-time data and AI. Here are 19 women to watch who are moving the technology, business, and ethics
How to Fix AI’s Hallucinations Problem: Corral It With Facts
A key to cracking the hallucinations problem is adding knowledge graphs to vector-based retrieval augmented generation (RAG), a technique that injects an …
Want AI? It’s Going to Require a Healthy Dose of Real-Time Data Streaming
AI and machine learning are going to shake up how companies operate, and streaming data amplifies the leverage that can be gained from these powerful
What’s the future of GenAI? Checking in with Industry Leaders
As we look ahead, the success of Generative AI will be measured not by its ability to grab headlines or fuel grandiose visions but by its capacity to quietly …
Considerations and a Blueprint for Responsible AI Practices after a Year of ChatGPT
Responsible AI requires that organizations address process, technology, people, and governance issues, according to speakers at the recent AI
The Technical Evolution of Apache Kafka: From LinkedIn’s Need to a Global Standard
Today, Apache Kafka is a widely used technology, with applications ranging from real-time data processing to stream processing, event sourcing, and messaging …
Let’s Get ‘Phygital’: A $216-Trillion Market Emerges
The growing use of digital twins that converge the physical and digital aspects of an entity is giving rise to a new phygital market.
Governing the Use of AI
When it comes to governing the use of AI, compliance starts from the top. It is vital that AI policies are not developed in a vacuum and that company …
Open Source and the Data Lakehouse: Apache Iceberg and Project Nessie
The data lakehouse concept presents a harmonious fusion of the strengths of both data lakes and data warehouses.