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Zhejiang University's TestSprite2.0 achieves breakthrough, automatically creating bug-free websites in 30 mins with 93% code accuracy. It streamlines testing via AI, supports cross-timezone automation, and is adopted by 6000+ teams.....

Kuaishou and Shanghai Jiao Tong University announced the open-source multimodal generation model Orthus at the ICML conference. The model is based on an autoregressive Transformer architecture and demonstrates excellent performance in text-image conversion tasks, with significantly improved computational efficiency compared to existing models. Orthus uses a unique architectural design, separating processing of text and image features through specific modal generation heads, and efficiently fusing them in a unified representation space. Research shows that the model outperforms professional models in image understanding and text-to-image tasks, while also demonstrating strong potential in application scenarios such as image editing, making it a breakthrough in multimodal generation.

NTU's 'WORLDMEM' model enhances virtual reality with long-term scene consistency via innovative memory mechanisms and conditional diffusion transformers.....

Chinese AI firm MiniMax raised $300M, reaching a $4B valuation. Backed by Shanghai state capital, it's now one of China's two $3B+ LLM companies. Founded by ex-SenseTime executives, with prior investments from Alibaba and Tencent, it's reportedly preparing for a Hong Kong IPO.....

PolyU & OPPO developed DLoRAL, a video super-resolution framework using dual LoRA: CLoRA for temporal consistency and DLoRA for spatial details. Its two-stage training balances quality and speed (10× faster inference), with open-source code/models available. Limited in tiny text recovery but promising for real-time applications.....

Hong Kong Polytechnic University and OPPO Research Institute jointly released the open-source video super-resolution framework DLoRAL, which generates high-definition videos in one step using diffusion models. The framework adopts a dual LoRA architecture: C-LoRA maintains temporal consistency between frames, while D-LoRA enhances spatial details. Through a two-stage training strategy, it optimizes temporal coherence and high-frequency information. Compared to traditional methods, DLoRAL improves inference speed by 10 times while maintaining smoothness, significantly enhancing image details, and providing an efficient open-source solution for video HD enhancement.

US insurers oppose a 10-year freeze on state AI regulation in the tax bill, fearing it undermines effective state oversight and consumer protections, with 40 AGs and 30 states using NAIC's AI model opposing.....

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

On June 30th, the world's first trillion-parameter large model for the power generation industry, Qinyuan, developed independently by the State Energy Group, was officially released. This innovative large model, with its unique full-stack independent and controllable characteristics, marks an important step forward for the power generation industry into a new era of intelligent decision-making. The Qinyuan large model aims to integrate the diverse scenarios, high complexity, and strong professionalism of the power generation industry, fully utilizing the State Energy Group's globally largest installed capacity and massive data resources. The launch of this model not only creates a new engine for multi-energy coordination and dynamic optimization, but also establishes an electricity

ByteDance's Seed Team recently released the impressive results of the 2025 full subject Gaokao test: the Dou Bao Seed1.6-Thinking model scored 683 in literature and 648 in science, meeting the admission threshold for Tsinghua and Peking University, and performed outstandingly in domestic and international AI model Gaokao tests. The test used the national new volume one and Shandong Province's independent proposition papers, with Dou Bao competing against five other top domestic and international AI models such as Google Gemini 2.5 Pro, DeepSeek R1, and OpenAI o3.

A major breakthrough in 3D modeling technology! The PartCrafter project co-developed by Peking University, ByteDance, and Carnegie Mellon University has officially been unveiled. It can generate high-precision, structured 3D models from a single RGB image, completely overturning the traditional complex process of segmentation followed by reconstruction. This technology not only improves generation efficiency but also infers the 3D geometry of unseen structures, showcasing immense potential for AI in the 3D generation field. The AIbase editorial team has compiled the latest information to provide you with an in-depth analysis of PartCrafter.

According to Science and Technology Daily, the world's first generative artificial intelligence radiology system integrated into clinical processes developed by Northwestern University School of Medicine is revolutionizing medical imaging diagnostics. This system can identify life-threatening conditions within milliseconds, providing an innovative solution to the global shortage of radiologists. The AI system has been fully deployed in 12 hospitals affiliated with Northwestern University. In five months of actual application in 2024, the system successfully analyzed nearly 24,000 radiology reports, increasing report generation efficiency by an average of 15.5%, boosting work efficiency for some doctors.