Learn how indexing, algorithms, deep learning systems, human raters, click and query data, and more shape Google's Search results.
RETVec is a state-of-the-art text vectorizer which works directly on text inputs to create resilient classification models. Models trained with RETVec achieve better classification performance with fewer parameters and exhibit stronger resilience against adversarial attacks and typos, as reported in our paper.
Google is countering with RETVec (Resilient & Efficient Text Vectorizer). Open sourced by Google Research, this approach “helps models achieve state-of-the-art classification performance and drastically reduces computational cost,” while supporting “every language and all UTF-8 characters without the need for text preprocessing.” This makes it ideal for on-device, web, and other large-scale use cases:
How to use BigQuery GENERATE_TEXT remote function
This feature looks to let you enter a prompt, which has to be longer than three words, like “A packing list for a camping trip with kids.” Google Keep should then return relevant bullet points.
The functionality sounds similar to the “List It” experiment in the first season of AI Test Kitchen. Introduced in 2022, you could “name a goal or topic and see how much LaMDA can break it down into multiple lists of subtasks.”
The functionality sounds similar to the “List It” experiment in the first season of AI Test Kitchen. Introduced in 2022, you could “name a goal or topic and see how much LaMDA can break it down into multiple lists of subtasks.”
