Google PaLM AI technology Top Builders

Explore the top contributors showcasing the highest number of Google PaLM AI technology app submissions within our community.

PaLM 2: Google's Revolutionary Large Language Model

PaLM 2 is a groundbreaking large language model developed by Google, setting extraordinary standards in the realm of artificial intelligence. Outperforming its predecessors and other LLMs in various aspects, PaLM 2 showcases unparalleled capabilities in complex reasoning, multilingual translation, and coding expertise.

Release dateTBA
TypeLarge Language Model

Experience PaLM 2: Where Unparalleled Performance Meets Responsible Innovation

We have collected the best PaLM 2 resources to help you explore the capabilities and potential applications of Google's cutting-edge large language model. Unleash the power of PaLM 2 with these valuable resources and see for yourself the future of artificial intelligence.

Explore curated libraries and resources to help you build outstanding projects with PaLM 2, Google's transformative large language model.

  • PaLM 2 Documentation - Dive into the in-depth technical report of PaLM 2, providing valuable insights into its development and capabilities.

  • PaLM 2 Overview - Discover the key features, capabilities, and evolution of PaLM 2, Google's groundbreaking large language model.

  • PaLM 2 Developer Guide - Access a comprehensive guide to using Google's generative AI models like PaLM 2, offering a plethora of support and resources for developers.

Google PaLM AI technology Hackathon projects

Discover innovative solutions crafted with Google PaLM AI technology, developed by our community members during our engaging hackathons.

Retriever AI

Retriever AI

Retriever AI is an innovative software solution that leverages cutting-edge artificial intelligence technology to revolutionize the way users interact with their Windows operating systems. By leveraging the capabilities of OpenAl's Whisper Automatic Speech Recognition (ASR) system and ElevenLabs' advanced interaction the application delivers a transformative user experience. Users can interact with their computers using natural spoken language, receive auditory feedback, and carry out tasks without the traditional visual interfaces. At its core, Retriever AI is powered by advanced machine learning algorithms that enable it to understand and respond to user commands effectively. With a simple "Start" command, users can invoke Retriever AI to assist them in navigating their system, opening applications, searching for files, and much more. It is like having a personal assistant dedicated to making your computer interactions more efficient and enjoyable. The software is designed with a user-friendly interface that is easy to start and stop, and it's designed to be almost hands-free from the keyboard. Its design is meant for the visually impaired and blind, and it's geared toward being able to complete normal functions using natural language. In a digital world where efficiency and user experience are of utmost importance, Retriever AI serves as a valuable tool for enhancing productivity, simplifying tasks, and creating a more intuitive interaction between users and their Windows systems even if you aren't visually impaired or blind. Whether you're a professional looking for a smarter way to navigate your workspace, a student aiming for better efficiency, or just a casual user hoping to get more out of your system, Retriever AI is designed to meet your needs.

VBCST voice based customer support tool

VBCST voice based customer support tool

VBCST is a voice-based customer support tool that can talk to customers It can be used to manage business queries and replace boring customer agents at your business. VBCST is powered by a large language model such as palm 2 that has been trained on a massive dataset. This allows VBCST to understand customer queries and provide accurate and helpful responses. VBCST can also access metadata about the customer, such as their name, contact information, and purchase history. This information can be used to personalize the customer experience and provide more relevant support. VBCST is a cost-effective way to improve customer support. It can be used to handle a large volume of calls, freeing up human agents to focus on more complex queries. VBCST can also be used to provide 24/7 support, which can be a valuable asset for businesses that operate in multiple time zones. VBCST is easy to use. It can be integrated with existing customer support systems, and it does not require any special training. VBCST can be used by businesses of all sizes, and it is a cost-effective way to improve customer satisfaction. Here are some of the benefits of using VBCST: Increased customer satisfaction: VBCST can provide accurate and helpful responses to customer queries, which can lead to increased customer satisfaction. Reduced costs: VBCST can help businesses to reduce the cost of customer support by handling a large volume of calls. Improved efficiency: VBCST can help businesses to improve the efficiency of their customer support by providing 24/7 support and by freeing up human agents to focus on more complex queries. Personalized customer experience: VBCST can access metadata about the customer, such as their name, contact information, and purchase history. This information can be used to personalize the customer experience and provide more relevant support. Here for the project purpose we have made a customer support tool for tesla company and it can be used in different companies too.

Research assistant

Research assistant

This project revolves around the development of a research assistant using the Google Vertex AI Palm2 platform. The aim is to streamline the process of searching for and accessing academic papers from Google Scholar, providing researchers with a user-friendly and efficient tool. The research assistant is implemented as a Streamlit application, allowing users to input their search specifications and navigate through Google Scholar seamlessly. One of the key features of the research assistant is its automatic scraping functionality. Once the user provides their search criteria, the application scours Google Scholar across multiple pages, retrieving relevant papers. The scraped papers are then organized into a comprehensive dataframe, providing researchers with a structured overview of the available literature. Additionally, the application also selects and provides downloadable PDF versions of the papers, making it convenient for users to access and read the full content. To further enhance the capabilities of the research assistant, it integrates with Google Vertex AI and Langchain. Google Vertex AI is a powerful machine learning platform that enables users to leverage advanced AI models and tools. By integrating with Vertex AI, the research assistant allows researchers to create a knowledge base from the downloaded papers, enabling them to extract insights and answer questions related to the content. Langchain, another crucial component, provides additional functionality for knowledge extraction. It offers a range of AI models and tools specifically designed for language processing and analysis. Integrating Langchain with the research assistant expands its capabilities, allowing researchers to delve deeper into the papers and extract valuable information.