Meta AI technology page Top Builders

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

Meta Platforms

Meta Platforms, Inc., formerly known as Facebook, Inc., is an American multinational technology conglomerate based in Menlo Park, California. The company owns and operates various products and services, including Facebook, Instagram, WhatsApp, Messenger, and Oculus, among others. Meta is one of the world's most valuable companies and is included in the list of the ten largest publicly traded corporations in the United States. It is considered one of the Big Five American information technology companies, alongside Alphabet (Google), Amazon, Apple, and Microsoft.

General
CompanyMeta Platforms, Inc.
FoundedJanuary 4, 2004
HeadquartersMenlo Park, California, U.S.
Area servedWorldwide

Key Products and Services

Meta Platforms offers a wide range of products and services that cater to various user needs. Some of their key products and services include:

  • Facebook: A popular social networking platform that allows users to connect with friends, family, and other people, share updates, photos, and videos, and engage in various online activities.
  • Instagram: A photo and video sharing platform that lets users capture and share moments, apply filters, and interact with others through likes, comments, and direct messages.
  • WhatsApp: A messaging app that allows users to send text messages, make voice and video calls, and share images, documents, and other media with friends and family.
  • Messenger: A messaging platform integrated with Facebook, allowing users to send messages, make voice and video calls, and engage in group chats.
  • Oculus: A virtual reality technology company that develops hardware and software products, including the Oculus Rift and Oculus Quest, providing immersive experiences for gaming, entertainment, and other applications.

Meta AI technology page Hackathon projects

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

The Effect of Model Configuration on HHEM Scores

The Effect of Model Configuration on HHEM Scores

PDF documents serve an important role in sharing and protecting information in today’s digital world. However, obtaining useful information from these pdfs documents can be difficult. Summarizing pdf documents enables users to quickly extract key information and gain a deeper understanding of the document’s content. Text summarization is a critical Natural Language Processing (NLP) task with applications ranging from information retrieval to content generation. Leveraging Large Language Models (LLMs) has shown remarkable promise in enhancing summarization techniques. While, automatically-generated summaries were riddled with artifacts such as grammar errors, repetition, and hallucination. Hallucination in text summarization refers to the phenomenon where the model generates information that is not supported by the input source document. Hallucination poses significant obstacles to the accuracy and reliability of the generated summaries. Detecting these hallucinations of LLMs for pdf summarization is a critical issue to evaluate summarization factual consistency rate. In the proposed project, we introduce LLM-based application called Cloudilic-HHEM that contains the following contributions: Enable users for chatting with different uploaded pdfs to extract useful and meaningful information, Summarizing pdf documents by different LLMs Like GPT 3.5, Google Gemini and LLAMA 2, Using Vectara-HHEM model to detect the score of hallucination of the used LLM in text summarization, Using dynamic temperatures when calling LLMs to compute the relative of hallucination score with the temperature parameter of LLM, The project has been presented by good stremlit GUI for user experience.