Facebook(現Meta)の研究チームが2016年に開発したオープンソースのAIフレームワーク「PyTorch」は、画像生成AIのStable Diffusionを含む数多くのAIプロジェクトに利用されています。2022年9月12日、PyTorchが「PyTorch Foundation」という名称で独立し、Linux Foundationの下で統括されるプロジェクトに移行することが発表されました。
Social media giant Meta is facing a barrage of legal and regulatory woes that threaten to shake its foundation. At the center of the storm i...
Meta, formerly known as Facebook, saw the growth of its apps slow in recent years amid business struggles and constant comparisons to TikTok.
This poster visualizes the Foundation Encyclopedia Dialectica [F.E.D.] Dialectical Taxonomy and Systematic/~Synchronic Dialectic of the Total Ontological-Categorial Content of the Contemporary Cosmos, per the F.E.D. 'Dialectical Theory of Everything' Whole-Known-Cosmos 'Meta-Model Meta-Equation', as formulated via the algebra of the Seldonian 'First Arithmetic for Dialectic'.
META's AI Translation agenda and inclusive metaverse project allows communication in 200 languages with real-time translation.
fine-tuning LLaMA 2 for text generation, detailing each step from setting up your environment to implementing and evaluating your fine-tuned model. LLaMA 2, or Large Language Model Meta AI 2, is the second iteration of Meta AI’s language model series. It builds upon the foundation laid by its predecessor with improved architecture, training methodologies, and performance metrics. LLaMA 2 is designed to handle a wide range of NLP tasks out of the box, making it a versatile tool for developers and researchers. However, fine-tuning allows you to adapt the model to specific domains or tasks, thereby improving its accuracy and relevance.
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May 2024: This post was reviewed and updated with support for finetuning. Today, we are excited to announce that Meta Llama 3 foundation models are available through Amazon SageMaker JumpStart to deploy, run inference and fine tune. The Llama 3 models are a collection of pre-trained and fine-tuned generative text models. The Llama 3 Instruct fine-tuned […]
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The Wikimedia Foundation recently partnered with Facebook parent company Meta to improve the encyclopedia’s citations.
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Your next Microsoft Teams meeting could unfold in a fully immersive virtual world. Microsoft recently launched Mesh for Teams – a platform enabling remote
Artificial Intelligence (AI) has been making significant advancements in various industries, and one of the areas it has been revolutionizing is the creation
Poster described at: http://ceur-ws.org/Vol-1795/paper46.pdf Wikidata is the linked database of Wikipedia and its sister projects from the Wikimedia foundation. Wikidata can be queried by SPARQL queries. Either through the WikiData Query Service (WDQS: http://query.wikidata.org) or its SPARQL endpoint at: https://query.wikidata.org/bigdata/namespace/wdq/sparql. Both the WDQS and the SPARQL endpoint do not allow submitting federated SPARQL queries. In our efforts to make Wikidata the central hub of linked data in the life science, being able to submit federated queries can be an asset. Although federation is not supported from Wikidata, the SPARQL endpoint is accessible for other SPARQL endpoint that do support federation. We compare four federated SPARQL query patterns to query Wikidata in combination with other semantic web formats.
According to a report published by BleepingComputer, a hacker duped some PyTorch machine-learning framework users into installing malware.
Code Llama is a suite of large language models released by Meta AI for generating and enhancing code. It includes foundation models for general coding, Python specializations, and models tailored for…
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