Hey there! Have you ever found yourself scratching your head over unpredictable cloud data costs? It’s no secret that accurately forecasting cloud data spend can be a real headache. Fluctuating costs make it challenging to plan and allocate resources effectively, leaving businesses vulnerable to budget overruns and financial challenges. But don’t worry, we’ve got you covered!

In part one of this two part series, I reviewed the history of the chatbot, my 2003 patent, and the reasons why the conditions weren’t right for the type of chat experience we’re all now enjoying with ChatGPT. For part two, we get into what has changed and the different ways enterprises can drive modern chatbot experiences with ChatGPT.

In the digital age, data transfer is integral to operations for businesses of all sizes. While Extract, Transform, and Load (ETL) processes have become fundamental for moving raw data to destinations like data warehouses, the protocols you use to transfer these files can impact the efficiency and security of the entire operation. Dive into our comprehensive guide, as we shed light on the most popular file transfer protocols and their relevance in today's tech landscape.

The release of ChatGPT pushed the interest in and expectations of Large Language Model based use cases to record heights. Every company is looking to experiment, qualify and eventually release LLM based services to improve their internal operations and to level up their interactions with their users and customers. At Cloudera, we have been working with our customers to help them benefit from this new wave of innovation.

BigQuery ML inference engine lets you run inference over custom models, remote models, and pretrained models within your machine learning workflow.

You can now generate text embeddings in BigQuery and apply them to downstream application tasks using familiar SQL commands.