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In recent years, the field of artificial intelligence has undergone tremendous changes, especially with large language models (LLMs) making remarkable progress in multi-modal tasks. These models have demonstrated strong potential in their ability to understand and generate language, but most current multi-modal models still adopt auto-regressive (AR) architectures, which limit inference processes to be rather monotonous and lacking flexibility. To address this limitation, a research team from The University of Hong Kong and Huawei Noah's Ark Lab has proposed a brand new model – FUDOKI, aiming to break these constraints. The core innovation of FUDOKI is

Recently, Meta's FAIR team and researchers from the Hebrew University of Jerusalem jointly released a new study indicating that reducing the reasoning time of large language models can significantly improve their performance in complex reasoning tasks. The research findings show that using shorter reasoning chains, the accuracy of AI models has increased by 34.5%, which challenges some assumptions in the current AI industry. Image source notes: The image was generated by AI and is licensed by Midjourney in this study, the authors point out that prolonged deliberation

Recently, Google officially released the open source framework LMEval, aimed at providing standardized evaluation tools for large language models (LLMs) and multimodal models. The launch of this framework not only simplifies cross-platform model performance comparisons, but also supports assessments in areas such as text, images, and code, showcasing Google's latest breakthroughs in the field of AI evaluations. AIbase has compiled the latest developments of LMEval and its impact on the AI industry. Standardized Evaluations: Simplified Cross-Platform Model Comparisons

Mistral recently launched its new Agents API, a framework designed for developers to simplify the creation of AI agents that can execute various tasks such as running Python code, generating images, and performing Retrieval-Augmented Generation (RAG). The launch of this API aims to provide a unified environment for large language models (LLMs) to interact with multiple tools and data sources in a structured and persistent manner.

At a critical moment when artificial intelligence and blockchain technology are rapidly converging, the open-source AGI research institution DMind is leading industry change with its innovative Web3-specific language models. Recently, the institution released two domain-specific large language models, DMind-1 and DMind-1-mini, which have been deeply optimized for Web3 application scenarios such as blockchain, decentralized finance, and smart contracts. The technical breakthrough in specialized AI models: the DMind-1 series of models represent an important advancement in the application of AI technology in vertical fields. Compared to traditional models...

ByteDance recently announced the official launch of its "Top Seed" program for recruiting top AI talent from the class of 2026. The program aims to recruit approximately 30 outstanding doctoral students. This initiative focuses on cutting-edge artificial intelligence, encompassing research areas such as large language models, machine learning algorithms and systems, multi-modal generation and understanding, and speech processing. ByteDance hopes to attract young talents with strong potential and passion in the field of large language model research. Unlike previous recruitment plans, this year's "Top Seed" program emphasizes no restrictions on academic background.

Zhipu BigModel's open platform has adjusted prices for several of its model offerings. GLM-4-FlashX, for example, is now priced at just 10 RMB per 100 million tokens. Built on a powerful pre-trained base, this model boasts exceptionally fast inference speeds and functional capabilities comparable to GPT-4, excelling in data extraction, generation, and translation.

Intel recently announced the open-sourcing of its AI Playground software, designed for local generative AI. AI Playground provides a powerful platform for running AI models on Intel Arc GPUs. It supports various image and video generation models, as well as Large Language Models (LLMs), significantly lowering the hardware barrier for AI applications by optimizing local computing resources. The project is available on GitHub and has attracted developers and AI enthusiasts worldwide.

Amidst the rapid growth of the AI industry, Chatbot Arena, a crowdsourced AI benchmarking project, is expanding its reach by officially launching a new company, Arena Intelligence Inc. According to Bloomberg, Chatbot Arena aims to leverage this new entity to secure more resources, significantly enhancing the platform's functionality and services. Founded in 2023, Chatbot Arena is primarily spearheaded by the University of California, Berkeley...

A new Gartner report predicts that by 2027, enterprises will utilize task-specific AI models three times more frequently than general-purpose large language models. While acknowledging the strong language processing capabilities of general-purpose models, the report highlights their decreased accuracy in tasks requiring deep understanding of specific business domains. Consequently, businesses are increasingly focusing on customized AI models to meet their unique needs. Image note: Image generated by AI, image licensing provided by Midjourney.

On April 15th, Hugging Face, the renowned open-source large language model platform, announced its acquisition of Pollen Robotics, marking its official entry into the physical robotics field. While specific transaction terms remain undisclosed, the acquisition will bring approximately 20 Pollen Robotics employees to Hugging Face. This represents the company's largest personnel acquisition to date, signifying its ambition in expanding its business areas. Hugging Face's co-founder...

Zhihu AI, a leading player in the Chinese large language model market, has officially begun its initial public offering (IPO) process, marking a significant milestone for the industry's 'Big Six' companies.

OpenGVLab has open-sourced the InternVL3 series of models, marking a new milestone in the field of Multimodal Large Language Models (MLLMs). The InternVL3 series comprises seven models ranging from 1B to 78B parameters, capable of handling text, images, and videos simultaneously, demonstrating superior overall performance.

The Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by renowned AI scientist Fei-Fei Li, has released its latest AI Index Report 2025. In its eighth year, this authoritative report highlights the narrowing performance gap between top AI models from China and the United States, the world's two most influential AI nations. The gap has shrunk to a negligible 0.3%, down from 17.5% in 2023. The report also features a ranking of Notable Models in 2024, with...