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Recently, MiniMax announced the launch of its new model MiniMax-M1. As the world's first open-source large-scale hybrid architecture inference model, it demonstrates outstanding performance in complex production scenarios, becoming a leader among open-source models. MiniMax-M1 not only surpasses domestic closed-source models but also approaches the level of the most advanced overseas models while maintaining the highest cost-effectiveness in the industry. A notable feature of MiniMax-M1 is its support for up to 1 million context inputs, comparable to the closed-source model G

Tencent has released the technical report on Qwen TurboS, revealing the core innovations and powerful capabilities of its flagship large language model TurboS. According to the latest rankings from the global authoritative large model evaluation platform Chatbot Arena, Qwen TurboS ranks seventh among 239 participating models, making it the top model domestically after Deepseek, and internationally trailing only Google, OpenAI, and xAI.

Recently, the domestic embodied intelligent start-up "Lingyu Intelligence" announced the completion of a multimillion-dollar seed round financing. This round was led by InnoAngel Fund, with participation from Shuimu Alumni Seed Fund and Horizon Ventures. The company was co-founded by Jin Ge, an alumnus of the Department of Automation at Tsinghua University, together with his team. It is committed to creating a benchmark for embodied intelligent applications, accelerating the real-world implementation of robots in industrial and home scenarios. Lingyu Intelligence, leveraging its technical accumulation in the field of robot motion control, has built a general solution covering data collection from the human side, actuators on the machine side, to intelligent operation platforms, bridging from level L0 to L4 of intelligence.

Scientists at Alibaba Group have introduced VACE, a universal AI model designed to unify a wide range of video generation and editing tasks. At the heart of VACE is an enhanced Diffusion Transformer architecture, innovating with a novel input format called "Video Conditional Unit" (VCU). VCU distills diverse modalities such as text prompts, reference images or video sequences, and spatial masks into a unified representation, and through a specialized mechanism coordinates different inputs to avoid conflicts. Concept decoupling enables fine-grained control.

In the field of AI art generation, diffusion models are transitioning from U-Net based architectures to Transformer-based architectures (DiT). However, the DiT ecosystem faces challenges in plugin support, efficiency, and multi-conditional control. Recently, a team led by Xiaojiu-z introduced EasyControl, an innovative framework designed to provide efficient and flexible conditional control capabilities for DiT models, effectively giving DiT models the power of ControlNet.

Tencent recently released the official version of its HunYuan large language model series – HunYuan-T1. This new model, built upon the medium-scale HunYuan base model and extensively fine-tuned, demonstrates significantly improved reasoning capabilities, particularly excelling in deep thinking and complex problem-solving. Since the launch of the HunYuan T1-Preview in February, users have experienced faster and more insightful processing. The official release marks a significant upgrade to the product line. The HunYuan-T1 development team leveraged the latest Turbo...

In the field of deep learning, normalization layers are considered an indispensable component of modern neural networks. Recently, research led by Meta FAIR research scientist Zhuang Liu, titled "Transformer without Normalization Layers", has garnered significant attention. This research not only introduces a new technique called Dynamic Tanh (DyT), but also demonstrates the effectiveness of Transformer architectures even without traditional normalization layers.

On March 13th, Sesame unveiled its latest speech synthesis model, CSM, attracting significant industry attention. According to the official introduction, CSM adopts an end-to-end Transformer-based multimodal learning architecture. It understands contextual information to generate natural and emotionally rich speech with stunningly realistic sound. The model supports real-time speech generation, processing both text and audio inputs. Users can also control features such as tone, intonation, rhythm, and emotion by adjusting parameters, showcasing high flexibility. CSM is considered a breakthrough in AI speech technology.

Artificial intelligence is rapidly integrating into our daily applications, and a startup called Flower Labs is revolutionizing how AI models are deployed and run. This Y Combinator-backed company recently launched Flower Intelligence, an innovative distributed cloud platform designed to serve AI models on mobile devices, personal computers, and web applications. At the core of Flower Intelligence...

Frustrated by the slow processing speed of large language models on long documents? Researchers from Tsinghua University have unveiled a groundbreaking technology – the APB parallel inference framework – that dramatically accelerates processing. Benchmark tests show this technology achieves a 10x speed improvement over Flash Attention when handling ultra-long texts. With the rise of models like ChatGPT, AI's ability to process vast amounts of text (hundreds of thousands of words) has increased significantly. However, this often comes at the cost of processing speed...