Author: AI Generated Robotic Content

Posted by Yun Zhu and Lijuan Liu, Software Engineers, Google Research Large language model (LLM) advancements have led to a new paradigm that unifies various natural language processing (NLP) tasks within an instruction-following framework. This paradigm is exemplified by recent multi-task LLMs, such as T0, FLAN, and OPT-IML. First, multi-task data is gathered with each …

Read more “Cappy: Outperforming and boosting large multi-task language models with a small scorer”

This is a guest post co-written with Scott Gutterman from the PGA TOUR. Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Given the data sources, LLMs provided tools …

Read more “The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype”

Traditional barriers between data and AI teams can hinder innovation. Often, these disciplines operate separately and use disparate tools, leading to data silos, redundant data copies, data governance overhead and cost challenges. From an AI implementation perspective, this increases security risks and leads to failed ML deployments and a lower rate of ML models reaching …

Read more “Dive deeper into Gemini with BigQuery and Vertex AI”