Flipboard

DECEMBER 6, 2023

The following are some of the experiments that were conducted by the team, along with the challenges identified and lessons learned: Pre-training – Q4 understood the complexity and challenges that come with pre-training an LLM using its own dataset. The context is finally used to augment the input prompt for a summarization step.

Chatbots 168

Chatbots LLM Prompt Engineer Prompt Engineering 168

ODSC - Open Data Science

AUGUST 15, 2023

Troubleshooting Search and Retrieval with LLMs Xander Song | Machine Learning Engineer and Developer Advocate | Arize AI Some of the major challenges in deploying LLM applications are the accuracy of results and hallucinations.

Software Architect 52

Software Architect Data Scientist Data Science Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 9, 2024

This enables Domo to optimize model performance through prompt engineering, preprocessing, and postprocessing, and provide contextual information and examples to the AI system. The tools provide the agent with access to data and functionality beyond what is available in the underlying LLM.

Software Architect 128

Software Architect Generative AI AI AI 128