It is worth noting that GPT-4 is currently more expensive per token (prompt length) and slightly slower in response generation. So far we are extremely impressed with the improved accuracy of the GPT-4 responses. In addition, we have been experimenting with completely new and more demanding use cases. We have been rapidly testing and comparing our previous prompts against both GPT-3.5 and GPT-4. We wanted to see how GPT-4’s increased reasoning and longer prompt support improved our integration-based use cases. What we’ve seen so farĪt SnapLogic, we have been prototyping a variety of integration and automation use cases using ChatGPT (GPT-3.5) to connect intent expressed in business language with technical implementation to realize the business goal. We are now actively exploring the use of GPT-4 to enhance our platform capabilities further. Our Iris AI solution, trained against over 7 petabytes of metadata, has already provided tremendous value to our customers over the last six years. We have helped pioneer the incorporation of AI and ML technology to streamline the integration, automation, and orchestration of data flows across enterprises.
Large language models (LLMs) like GPT-4 can assist organizations to simplify and automate the integration of business processes and unify data across applications into data warehouses for reporting and for descriptive and predictive analytics.Īt SnapLogic, our vision is to deliver frictionless integration and automation.
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