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Large Language Models (LLMs) have achieved significant progress in complex reasoning tasks by combining task prompts with large-scale reinforcement learning (RL), as demonstrated by models like Deepseek-R1-Zero, which directly apply reinforcement learning to base models, showcasing strong reasoning capabilities. However, this success is difficult to replicate across different base model families, especially within the Llama series. This raises a core question: what factors lead to inconsistent performance of different base models during reinforcement learning? How does reinforcement learning perform in

OpenAI recently announced that, despite initial testing, it will not adopt Google's TPU chips on a large scale. TPU (Tensor Processing Unit) is a custom ASIC chip developed by Google for machine learning tasks, designed to accelerate the training and inference of neural networks. TPU uses a dataflow-driven architecture, enabling efficient matrix multiplication pipeline computing and reducing memory access latency. Image source note: The image is AI-generated, provided by the licensing service Midjourney. OpenAI stated that it will continue

According to NetEase Technology, JD.com's layout in the field of embodied intelligence is accelerating rapidly. The embodied intelligence brand JoyInside under JD.com has reached cooperation with more than ten leading robot companies, becoming the core engine for JD.com to seize the smart robot market. According to insiders, JoyInside is supported by JD's large model technology, focusing on providing smart interaction capabilities between robots and consumers. Its product strategy focuses on scenario-based applications such as one person, one dog, and one toy. Since its launch, the brand has successfully attracted leading enterprises from multiple niche fields to join.

Recently, Hon Hai Precision Industrial Co., Ltd. (commonly known as Foxconn) submitted a trademark registration application for "FoxBrain" to the Trademark Office of the National Intellectual Property Administration. This AI inference large model is not only Foxconn's first attempt but also the first AI model of this type in Taiwan. According to public information, the international classification of this trademark is scientific instruments, and it is currently in the "waiting for substantive examination" status. "FoxBrain" is an AI inference large model launched by the Hon Hai Research Institute, covering data analysis

Honor's official Weibo account @MagicOS announced that Honor has successfully deployed the world's first edge-side voice large model. This technological advancement is not only a breakthrough for Honor, but also hailed as a 'renewal of AI voice technology'. This significant achievement will make its debut on the overseas version of the upcoming Honor Magic V5. Honor's technological innovation is the result of its in-depth efforts in the field of artificial intelligence. It is reported that Honor has published two academic papers at the prestigious international conference InterSpeech, which have attracted widespread attention from the academic community.

Tao Tian Group announced yesterday at its 'Hard-Core Youth Tech Festival 4.0' event that its independently developed hundred-billion-parameter recommendation large model, RecGPT, has officially gone live. This innovative achievement will comprehensively upgrade the 'You May Also Like' information flow on the mobile Taobao homepage, providing users with a more accurate and personalized recommendation experience through AIGR (Generative Recommendation) technology. The launch of RecGPT marks an important step forward for Taobao in the field of e-commerce recommendations. Test data shows that the recommendation feed equipped with the RecGPT large model performs excellently, with real user click-through rates

On June 30, Baidu officially open-sourced its latest ERNIE Bot Large Model 4.5 series, which includes a total of 10 models, including a mixture-of-experts (MoE) model with 47B and 3B activation parameters, as well as a dense model with 0.3B parameters. This open-source release allows developers to use these powerful models for free and provides pre-trained weights and inference code, making it easy for developers to apply them in various scenarios. During this release, Intel also demonstrated its strong technical support. By leveraging the OpenVINO toolkit, Intel provided efficient optimization for the ERNIE Bot Large Model.

Welcome to the AIbase [AI Daily Report] section! Spend three minutes a day to learn about the latest AI events, helping you understand AI industry trends and innovative AI product applications. For more AI news, visit: https://www.aibase.com/zh1. Baidu officially releases the WENXIN Large Model 4.5 series and fully opens it to the public, featuring ten new models with various parameter configurations. These models are trained and inferred using the PaddlePaddle framework, achieving a FLOPs utilization rate of 47%, and perform well in multi-modal text tasks.

Recently, Baidu officially announced the open-source release of its WENXIN Large Model 4.5 series, launching a total of ten models, including mixed expert (MoE) models with 47B and 3B activated parameters, as well as dense models with 0.3B parameters. This open-source initiative not only fully publicizes the pre-trained weights but also provides inference code, marking a significant advancement for Baidu in the field of large models. These newly released models can be downloaded and deployed on platforms such as PaddlePaddle Starry Sky Community and Hugging Face. Additionally, Baidu Intelligent Cloud's Qianfan Large Model Platform also provides