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Amap announced the launch of its HumanRig technology and the open-sourcing of the industry's first large-scale dataset specifically designed for 3D humanoid character rigging. This technology aims to reduce the cost of character animation production and drive the animation industry towards greater efficiency and automation. It serves as a key infrastructure for Amap in building immersive navigation experiences.

Wikipedia recently announced the release of a dataset optimized for AI model training, in collaboration with Kaggle, Google's data science community platform. This initiative aims to reduce the scraping of Wikipedia data by AI developers, conserving the platform's bandwidth and server resources. The dataset includes structured Wikipedia information in English and French, offering high machine readability for AI developers to facilitate modeling, fine-tuning, and data analysis. The Wikimedia Foundation stated that this data...

The Shanghai Artificial Intelligence Laboratory has released the open-source "Wanjuan Silk Road 2.0" multilingual multimodal corpus. Building upon the existing 5 languages (Arabic, Russian, Korean, Vietnamese, and Thai), this updated corpus adds three rare languages: Serbian, Hungarian, and Czech. It encompasses four modalities – text, images, audio, and video – totaling over 11.5 million data points and more than 26,000 hours of audio and video, making it a significant resource for low-resource multilingual multimodal research.

Bug fixing is a persistent challenge in software development. ByteDance's Doubao large model team has exciting news: they've launched Multi-SWE-bench, the first multi-lingual software engineering (SWE) dataset. This new dataset aims to evaluate and improve the ability of large models to automatically fix code errors. Multi-SWE-bench significantly expands the scope compared to previous single-language datasets. It covers not only Python, but also...

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.