At Cloudera, we continuously strive to empower organizations to unlock the full potential of their data, catalyzing innovation and driving actionable insights. And so we are thrilled to introduce our latest applied ML prototype (AMP)—a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database.

Enterprises see embracing AI as a strategic imperative that will enable them to stay relevant in increasingly competitive markets. However, it remains difficult to quickly build these capabilities given the challenges with finding readily available talent and resources to get started rapidly on the AI journey.

Cloud transformation is ranked as the cornerstone of innovation and digitalization. The legacy IT infrastructure to run the business operations—mainly data centers—has a deadline to shift to cloud-based services. Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives.

We’ve all heard that data helps businesses make better decisions. The good news? This isn’t just speculation: research shows that companies who use data to drive decision making increase revenues by an average of more than 8%, are 23 times more likely to attract new customers, and are 19 times more likely to be profitable as a result.

The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. AI-powered automation is already driving significant margin growth by reducing costs.

AI is the next revolutionary technology that will accelerate the mission of the Department of Defense. Newly boundless in its applications, “AI” joins “cyber” and “cloud” as the most important information technologies that have arrived in the last 25 years.