Recently, the AI assistant Flow officially released version 2.0, introducing the new 'Featured Content' and 'Discover' sections that provide users with more intelligent and personalized high-quality content services. These features demonstrate the practical value of artificial intelligence platforms in both life and work, especially in addressing users' confusion and needs. With the continuous maturity of large model technology, Flow offers users a richer variety of information in graphic, text, and Q&A formats through AI Native Content (AINative). The new version's 'Featured Content'

Recently, Quark officially launched its self-developed intelligent dialogue assistant, CueMe. CueMe is a multifunctional smart assistant that integrates literary creation, knowledge acquisition, and emotional companionship, aimed at providing users with comprehensive information services. Leveraging advanced artificial intelligence technology, CueMe can meet users' diverse needs in learning and work, whether it’s writing essays, reports, or creating novels and copy, CueMe offers efficient support.

Google AI Studio has released a new native prompt library that integrates features such as long-text context, multimodal inputs (images, videos, audio), and structured outputs. The aim is to provide users with a rich and diverse experience across various fields including education, programming, and travel. This library includes practical features like recipe generators, math tutors, math homework generators, treasure hunt design, unit test generators, and travel suggestions, all designed to enhance user exploration and innovation through intuitive displays and comprehensive information. Users only need to log into Google AI Studio.

The research team at Tsinghua University has successfully developed the 'LongWriter' artificial intelligence system, which can generate coherent texts exceeding 10,000 words, paving new avenues for long-form writing and content creation. By constructing the 'LongWriter-6k' dataset, which includes 6,000 writing samples, the research team has increased the maximum output length of the AI model from approximately 2,000 words to over 10,000 words. This innovative achievement not only enhances the AI's performance in long text generation tasks but even surpasses larger-scale models.

Zhipu AI announces that the LLM GLM-4-Long, which supports ultra-long context lengths, is now available on the open platform bigmodel.cn. This model is designed specifically for processing long texts and can read the equivalent of two copies of 'Dream of the Red Chamber' or 125 papers in one go. It is widely applied in scenarios such as translating long documents, global analysis of financial reports, extracting key information, and building chatbots with ultra-long memory.

The Transformer architecture, a star in the field of artificial intelligence, has led a revolution in natural language processing with its self-attention mechanism at its core. However, when handling long contexts, the resource consumption of self-attention calculations becomes a bottleneck. To address this issue, researchers have proposed the Tree Attention method, which decomposes the calculation tasks through tree reduction to improve efficiency. This method not only reduces communication overhead and memory usage but is also 8 times faster than existing methods in a multi-GPU environment. The introduction of Tree Attention not only enhances performance.

Long context understanding is a key challenge in the field of natural language processing, especially when large language models (LLMs) handle text that exceeds their context window size. To address this issue, researchers developed the LooGLE benchmark test, aimed at assessing LLMs' capability to understand extremely long documents (averaging 19.3k words, comprising 776 articles across multiple domains). LooGLE includes 7 tasks that cover both short and long dependencies, evaluating model understanding across texts of varying lengths. The test data is sourced from open-access content after 2022.

The Tencent Yuanbao AI Assistant has introduced a new long text deep reading feature, providing users with professional content analysis for documents such as theses, financial reports, and research reports. After uploading content, users can receive core overviews, modular analyses, and chart summaries, allowing rapid comprehension of key information. The deep reading mode, leveraging Tencent's Hunyuan large model, supports the processing of 500,000-word long texts, generating illustrated analyses that include innovation point extraction, professional term search/translation, and DuPont analysis charts. This feature allows users to view deep reading content and the original text offline, enhancing reading efficiency. Powered by Tencent's trillion-parameter Hunyuan large model, it offers...

The standout feature of OpenAI's new model gpt-4o-64k-output-alpha is its ability to output up to 64K tokens at once, making it suitable for generating rich and detailed content, catering to writing, programming, and complex data analysis needs. However, this functionality comes at a higher API cost, with a fee of $18 per million output tokens, compared to just $6 for input tokens per million. This pricing strategy aims to match high computational costs and encourage responsible use of this powerful tool. The model is designed for creativity and research fields.

Nvidia's ChatQA2 model, optimized from Llama3, addresses key challenges in AI long-text context understanding and retrieval-augmented generation by extending the context window to 128K tokens and employing a three-phase instruction tuning process. It significantly enhances instruction adherence, RAG performance, and long-text comprehension. In the InfiniteBench evaluation, ChatQA2 demonstrated accuracy comparable to GPT-4-Turbo-2024-0409 and surp....

Recently, Apple's research team and Meta AI researchers have jointly introduced a new technology called LazyLLM, which aims to enhance the efficiency of large language models (LLMs) in long-text reasoning. As everyone knows, current LLMs often face slow processing speeds when dealing with long prompts, especially during the pre-filling phase. This is primarily due to the modern transformer architecture's computational complexity, which grows quadratically with the number of tokens in the prompt

iFlytek's Spark has introduced the Spark Pro-128K large model, equipped with ultra-long text processing capabilities, significantly enhancing the value of AI large models in practical applications. The ability to handle long texts is a crucial direction for the development of AI large models, particularly important for industries such as finance, healthcare, and research, enabling rapid understanding and generation of vast amounts of information to improve work efficiency.The API for the Spark P

On July 10th, the AI assistant "Stellar Flow" was officially launched, designed specifically for research professionals, university faculty, and students. "Flow" aims to serve as a smart search assistant for users, offering multifunctional services including intelligent search, knowledge Q&A, smart reading, and creative assistance, with the goal of enhancing efficiency in work and study. "Flow's" official website showcases multiple features of this product. In the field of academic research, rea

On July 3, 2024, the Shanghai AI Lab, in collaboration with SenseTime Technology, the Chinese University of Hong Kong, and Fudan University, officially released the next-generation large language model, InternLM2.5. The InternLM2.5-7B model has been open-sourced, and models of other scales will be released in sequence. The Shanghai AI Lab promises to continue to provide free commercial licenses and support community innovation with high-quality open-source models.The model has significant improv

Yesterday, Kimi Open Platform under the Moon's Dark Side announced the public test of Context Caching technology. This technology can reduce the cost of using large text flagship models by up to 90% for developers, without changing the API price, and significantly improve the response speed of the model. Context Caching is an efficient data management technology that allows the system to pre-store large amounts of data or information that may be frequently requested. This way, when you request t

'Chengpian' has garnered widespread attention since its launch by Baidu Wenku at the end of May, thanks to its comprehensive AI Native product features. It integrates multiple functionalities including professional knowledge retrieval and Q&A, ultra-long image and text understanding and generation, deep editing and organizing, and cross-modal creative freedom, fulfilling users' complete needs for research, creation, and editing in professional fields.

Baidu plans to offer free access to its long text capabilities, with a character range between 2 million and 5 million. After the upgrade, Baidu Wenxin Yiyan will provide broader text processing capabilities. This initiative will be officially implemented next month and is of great significance to users. The opening of Baidu's long text capabilities will greatly enhance users' text processing efficiency and convenience.

The internal test of the 360 Smart Brain's 5 million words long text processing feature will be integrated into the 360AI Browser, providing support for various document types. Users will enjoy convenient text processing services on their mobile devices.

🚀 Large model companies are competing to upgrade, making the focus on handling 'long text' a new trend. 📈 The article emphasizes that the challenge of context length is actually related to the Transformer structure. 📚 Long text technology will bring deeper applications to the fields of finance, justice, and scientific research.

Meta has released the Llama2-Long model, which does not increase computational demand when processing long texts while still maintaining excellent performance. The model employs continuous pre-training, improved positional encoding, and data mixing strategies to reduce computational overhead by up to 40%. It performs outstandingly on both long and short tasks, surpassing other long-context models and has the potential to revolutionize the field of natural language processing. The model shows significant improvements in encoding, mathematical, and knowledge-intensive tasks, even surpassing GPT-3.5. The release of the Llama2-Long model provides a powerful solution for handling long texts.