Author: AI Generated Robotic Content

Posted by Han Zhou, Student Researcher, and Subhrajit Roy, Senior Research Scientist, Google Research Prompting large language models (LLMs) has become an efficient learning paradigm for adapting LLMs to a new task by conditioning on human-designed instructions. The remarkable in-context learning (ICL) ability of LLMs also leads to efficient few-shot learners that can generalize from …

Read more “Batch calibration: Rethinking calibration for in-context learning and prompt engineering”

Posted by Nicholas Rubin, Senior Research Scientist, and Ryan Babbush, Head of Quantum Algorithms, Quantum AI Team If you’ve paid attention to the quantum computing space, you’ve heard the claim that in the future, quantum computers will solve certain problems exponentially more efficiently than classical computers can. They have the potential to transform many industries, …

Read more “Developing industrial use cases for physical simulation on future error-corrected quantum computers”

Palantir Artificial Intelligence Platform (AIP) enables new and existing customers to dramatically accelerate high-value AI use cases. To meet the intense requirements of the moment, we have introduced AIP Bootcamps. In these immersive, hands-on-keyboard sessions, participants can expect to go from zero to use case in just one to five days. The results speak for themselves. …

Read more “Deploying Full Spectrum AI in Days: How AIP Bootcamps Work”

Posted by Nicholas Rubin, Senior Research Scientist, and Ryan Babbush, Head of Quantum Algorithms, Quantum AI Team If you’ve paid attention to the quantum computing space, you’ve heard the claim that in the future, quantum computers will solve certain problems exponentially more efficiently than classical computers can. They have the potential to transform many industries, …

Read more “Developing industrial use cases for physical simulation on future error-corrected quantum computers”

Trends in the data space such as generative AI, distributed storage systems, unstructured data formats, MLOps, and the sheer size of datasets are making it necessary to expand beyond the SQL language to truly analyze and understand your data. To provide users with more flexibility of coding languages, we announced BigQuery DataFrames at Next ‘23. …

Read more “Build AI/ML and generative AI applications in Python with BigQuery DataFrames”