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Understanding Google PaLM: Purpose and Functionality
Understanding Google PaLM: Purpose and Functionality
Promptitude Team avatar
Written by Promptitude Team
Updated over a week ago

Google PaLM is a next-generation large language model that excels in advanced reasoning tasks. It's a product of Google's breakthrough research in machine learning and responsible AI.

This model is designed to perform tasks such as code and math classification, question answering, translation, multilingual proficiency, and natural language generation more effectively than previous models. In this article, we'll delve into what Google PaLM is, how it works, and how it can benefit your business.

What is Google PaLM?

Google PaLM is a state-of-the-art language model that builds on Google's legacy of machine learning and responsible AI. It's designed to handle complex tasks by breaking them down into simpler subtasks.

This model is particularly adept at understanding the nuances of human language, including riddles and idioms, which require understanding ambiguous and figurative meanings of words rather than their literal meanings.

How Does Google PaLM Work?

Google PaLM works by leveraging three distinct research advancements in large language models:

  1. Multilingual translation: PaLM was pretrained on parallel multilingual text and a large corpus of different languages, making it excel at multilingual tasks.

  2. Coding: PaLM was pretrained on a large quantity of webpage source code and other datasets, enabling it to excel at popular programming languages like Python and JavaScript. It can also generate specialized code in languages like Prolog, Fortran, and Verilog.

  3. Language capabilities: PaLM's language capabilities can help teams collaborate across languages, making it a valuable tool for global businesses.

Evaluating Google PaLM

Google PaLM achieves state-of-the-art results on reasoning benchmark tasks. For example, it was evaluated on tasks such as WinoGrande and BigBenchHard and on benchmarks such as XSum, WikiLingua, and XLSum. On these benchmarks, it significantly achieved better multilingual results than previous large language models and improved translation capability over Google Translate in languages like Portuguese and Chinese.

Models

Model

Max Tokens

text-bison-001

✅ Maximum input tokens: 8,192

✅ Maximum output tokens: 1,024

✅ Training data: until February 2023

Generates text. Optimized for language tasks such as: Code generation, text generation, text editing, problem-solving, recommendations generation, Information extraction, data extraction or generation, AI agent, Can handle zero, one, and few-shot tasks.

chat-bison-001

✅ Maximum input tokens: 4,096

✅ Minimum output tokens: 1,024

✅ Training data: until February 2023

Generates text in a conversational format. Optimized for dialog language tasks such as implementation of chatbots or AI agents. Can handle zero, one, and few-shot tasks.

Google PaLM in Action

Google PaLM is used in other state-of-the-art models like SecPaLM and is implemented in generative AI tools like the PaLM API and Bard Reasoning. It's also powering generative AI features like email summarization in Gmail and brainstorming and rewriting in Google Docs.

Google PaLM is a powerful tool that can help businesses handle complex tasks more efficiently. Its advanced reasoning capabilities, multilingual proficiency, and coding skills make it a valuable asset for any business looking to leverage AI for improved productivity and collaboration.

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