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Recently, Google officially launched its latest text-to-image model **Imagen4** through the Gemini API, marking an important milestone in the field of generative AI (AIGC). According to Google's official blog and community feedback, Imagen4 has achieved breakthroughs in generating text within images, solving a long-standing technical bottleneck in AIGC, and providing developers with a tool for creating high-quality visual content. It is reported that the model comes in two versions: **Imagen4** and **Imagen4Ultra**, with respective pricing details yet to be fully disclosed.

Hoje, o Hello, o Grupo Ant e a BYD, por meio de seus investidores, registraram conjuntamente a empresa Shanghai Zao Fu Intelligent Technology Co., Ltd. em Xangai. Esta nova empresa

, Google announced that its latest image generation model, Imagen4, has been officially integrated into the Gemini platform, bringing users enhanced capabilities for image creation. According to recent online information, Imagen4 has achieved significant breakthroughs in image details, text rendering, and color performance, making it one of the leading technologies in the field of AI image generation. This article will comprehensively analyze the far-reaching impact of Imagen4's integration on the Gemini ecosystem from technical highlights, functional applications, and user feedback perspectives. Technical Breakthroughs: Crisper, Smarter

The Gemini platform from Google has received a major update, officially integrating the latest Imagen4 image generation model. This upgrade allows users to directly generate high-quality images through simple prompts in chat conversations, marking a new stage for AI image generation technology where it becomes more intuitive and convenient. With Imagen4: A Leap in Image Generation Quality The Gemini platform now fully supports Imagen4, which is Google's latest text-to-image generation model, achieving significant improvements compared to its predecessor, Imagen3.

According to a new analysis, the power consumption of artificial intelligence is expected to reach nearly half of the total electricity consumption of global data centers by the end of 2025, meaning AI energy consumption will soon surpass bitcoin mining. The analysis was conducted by Alex de Vries-Gao, a Ph.D. student at the Environmental Institute of Vrije Universiteit Amsterdam. He has previously tracked the power consumption and environmental impact of cryptocurrencies and published related data on his website Digiconomist. Currently, AI has already accounted for a significant portion of data center energy usage.

En la era digital, la comodidad y seguridad de la identificación del usuario se vuelven cada vez más importantes. OpenAI anunció recientemente que está trabajando en una manera de

On May 21st, Tencent announced the comprehensive upgrade of its Hunchun large model matrix, marking the continuous enhancement of its technical capabilities in the field of artificial intelligence. This upgrade covers several aspects, including the upgrade of the flagship fast thinking model Hunchun TurboS, the deep thinking model Hunchun T1, and the launch of new visual deep reasoning model T1-Vision and end-to-end voice call model Hunchun Voice based on the TurboS base model. In addition, Tencent has also synchronized updates to Hunchun Image 2.0, Hunchun 3D v2.5, and a series of other models for game visual generation.

Recently, Tencent's Hunyuan T1-Vision has launched Yuanbao. The Yuanbao can deeply understand image content by its unique Hunyuan T1-Vision model and accurately capture key points behind the information. Users just need to take a photo and upload it, whether it’s an uncommon plant variety, a complex foreign language game interface, or a decision-making scenario requiring in-depth analysis.

Developed by TNG Technology Consulting, the DeepSeek R1T Chimera model has officially launched on the OpenRouter platform, providing global developers with efficient and powerful inference capabilities. This new open-source model combines the excellent inference capabilities of DeepSeek R1 with the high performance of V3-0324, marking another significant breakthrough in the balance of performance and efficiency in open-source AI technology. The following is compiled by AIbase.