Without a doubt, 2023 has shaped up to be generative AI’s breakout year. Less than 12 months after the introduction of generative AI large language models such as ChatGPT and PaLM, image generators like Dall-E, Midjourney, and Stable Diffusion, and code generation tools like OpenAI Codex and GitHub CoPilot, organizations across every industry, including government, are beginning to leverage generative AI regularly to increase creativity and productivity.

In recent years, governments across the globe have recognized the transformative potential of artificial intelligence (AI) and have embarked on initiatives to harness this technology to drive innovation and serve their citizens more effectively. These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm.

Artificial intelligence (AI) and large language models (LLMs) have come a long way since their inception in the 1950s. From the pioneering research of English mathematician and logician Alan Turing to the recent breakthroughs achieved by models like GPT-3/GPT-4, AI has undeniably transformed industries and revolutionized human-computer interactions.

In the dynamic world of machine learning operations (MLOps), staying ahead of the curve is essential. That’s why we’re excited to announce the Cloudera Model Registry as generally available, a game-changer that’s set to transform the way you manage your machine learning models in production environments.

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI.

The greater tech community was front row for a high-stakes corporate saga this past weekend, complete with more plot twists than the Succession series finale.

Of the many things one might take for granted, access to banking and financial services may not immediately come to mind. But as a thought experiment, imagine trying to buy a home or a car without the ability to take out a loan. Try depending on cash payments from your employer, or relying on alternative banking solutions like short-term payday loans, check-cashing services, and prepaid debit cards.

Have you ever wondered how massive business and consumer apps handle that kind of scale with concurrent users? To deploy high-performance applications at scale, a rugged operational database is essential. Cloudera Operational Database (COD) is a high-performance and highly scalable operational database designed for powering the biggest data applications on the planet at any scale.

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? The vast tapestry of data types spanning structured, semi-structured, and unstructured data means data professionals need to be proficient with various data formats such as ORC, Parquet, Avro, CSV, and Apache Iceberg tables, to cover the ever growing spectrum of datasets – be they images, videos, sensor data, or other type of media content.

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.