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.
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.
TraceMark’s sustainable sourcing monitoring platform provides transparency into global supply chains about the sourcing of raw materials.
Carto’s conversational GIS relies on BigQuery to provide information to generative AI, while BigQueryML connects to Vertex AI and PaLM2.
