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Meta is facing a copyright infringement lawsuit, with the plaintiff's attorney claiming that CEO Mark Zuckerberg approved the use of a dataset containing pirated e-books and articles to train its Llama AI model. This case is one of many copyright lawsuits against several tech giants accused of using copyrighted works for AI model training without authorization. In documents filed in the U.S. District Court for the Northern District of California on Wednesday evening, the plaintiffs reiterated Meta's actions from the end of last year.

ZhiYuan Robotics, in collaboration with the Shanghai Artificial Intelligence Laboratory and other institutions, has launched the AgiBot World dataset, the world's first million-level robot dataset based on real-world scenarios. Compared to Google's Open X-Embodiment, the scale of long-range data has increased tenfold, the scene coverage has expanded one hundredfold, and the data quality meets industrial standards. This open-source project, hailed as the 'ImageNet moment' in the field of embodied intelligence, showcases remarkable robotic capabilities, from arranging flowers in the living room to cooking in the kitchen and handling checkout in supermarkets.

Recently, at the 12th Digital Finance and Technology Finance Conference, part of the Zhongguancun Forum series of events, Ant Group's Deepfake detection solution was selected as a “Financial Technology Innovation and Application Case.” Leveraging its Tiantong Laboratory, Ant Group has constructed the first large-scale, high-quality, multi-modal Deepfake dataset in the industry, synthesizing over a million multimedia contents that fully simulate Deepfake attack samples in real-world financial risk control environments, becoming a benchmark for evaluating existing Deepfake detection in the financial sector.

Harvard University announced on Thursday the release of a high-quality dataset containing nearly one million public domain books, which anyone can use to train large language models and other AI tools. This dataset was created by Harvard's newly established Institutional Data Initiative and is funded by Microsoft and OpenAI. The included books are all works scanned by the Google Books Project that are no longer under copyright protection.

The New York Times and the Daily News encountered an unexpected twist in their copyright lawsuit: an OpenAI engineer inadvertently deleted virtual machine search data that could have been key evidence, adding a dramatic turn to this high-profile legal dispute. According to a letter submitted to the U.S. District Court for the Southern District of New York on Wednesday night, lawyers and technical experts for the two media companies had previously invested over 150 hours searching OpenAI's AI training dataset. However, on November 14, an OpenAI engineer accidentally deleted data stored on the virtual machine.

Recently, research teams from several Chinese scientific institutions have launched the super large-scale multimodal dataset named Infinity-MM, and based on this dataset, they have trained an outstanding AI model called Aquila-VL-2B. This breakthrough injects new momentum into the development of multimodal AI. The Infinity-MM dataset is astonishing in size, containing four major types of data: 10 million image descriptions, 24.4 million general visual instruction data, 6 million selected high-quality instruction data, and 3 million generated by G

A recent study led by the Technion-Israel Institute of Technology reveals that large language models (LLMs) may be more knowledgeable than they appear. Researchers found that LLMs' internal representations encode information about the correctness of their outputs, allowing them to identify the correct answer even when they ultimately generate an incorrect one. The research team focused on analyzing LLM errors in long text generation, which is more aligned with their real-world application scenarios. They constructed an error detection dataset to compare the model's outputs.

In the rapid advancement of artificial intelligence, an international research team is paving the way for the development of AI language models in Europe. They have launched a project called MOSEL (Massive Open-source compliant Speech data for European Languages), creating a comprehensive open-source voice dataset for the 24 official languages of the European Union. This initiative aims to promote the development of open AI language models in Europe, challenging the current dominance of English.

At the 2024 Beijing Cultural Forum, the Beijing Academy of Artificial Intelligence (BAAI) officially announced the release of the next-generation Chinese Internet corpus CCI3.0 (Chinese Corpora Internet), further promoting data co-construction and sharing. CCI3.0 includes a 1000GB dataset and a 498GB high-quality subset CCI3.0-HQ, marking another important update following the initial open-source release of CCI1.0 in November 2023 and the release of CCI2.0 in April 2024.

Recently, OpenAI launched a groundbreaking multilingual dataset designed to evaluate AI performance across 14 languages, including Arabic, German, Swahili, Bengali, and Yoruba. This dataset, named 'Multilingual Massive Multitask Language Understanding' (MMMLU), has been published on the open data platform Hugging Face, marking another significant advancement for OpenAI in the global AI landscape. Dataset link: https://huggingface

Zhiyuan Research Institute has launched a dataset called Infinity-Instruct, which comprises millions of instruction tuning data aimed at enhancing the performance of language models in dialogues and other areas. Recently, Infinity-Instruct has completed a new round of iterations, including the Infinity-Instruct-7M foundational instruction dataset and the Infinity-Instruct-Gen dialogue instruction dataset.

LAION launched Re-LAION-5B, the world's first AI training dataset that fully removes links to CSAM, aimed at addressing the issue of Child Sexual Abuse Material (CSAM). This dataset has been significantly improved over LAION-5B and is mainly divided into two versions: Re-LAION-5B Research and Research-Safe. A total of 2,236 CSAM links have been removed, including 1,008 from child protection organizations' lists. The dataset contains 5.5 billion pairs of text and images, designed to help

The German research institution LAION has created and released a new dataset, Re-LAION-5B, claiming to have removed links to suspected Child Sexual Abuse Material (CSAM). This dataset is a revised version of the old LAION-5B dataset, incorporating recommendations from the Internet Observation Foundation, Human Rights Watch, the Canadian Centre for Child Protection, and Stanford Internet Observatory. Re-LAION-5B is divided into two versions: Research and Research-Safe, with the latter additionally removing NSFW content. The dataset aims to support