Search AI Products and News

Recently, Mita AI Search officially launched its brand new 'Reading Mode' feature, addressing the inconvenience users face when reading PDF documents on mobile devices. This feature has been meticulously developed over the past six months and is now available to users. Since the launch of 'Library Search', Mita AI Search has helped users conveniently find a wealth of valuable PDF documents. However, these documents often suffer from messy formatting and readability issues when viewed on mobile. To improve this situation, the Mita AI Search team began development six months ago.

In the world of artificial intelligence, the reasoning capabilities of machine learning models, particularly large language models (LLMs), have been a focal point for scientists. Recently, Apple's AI research team published a paper titled 'Understanding the Limitations of Large Language Models in Mathematical Reasoning,' shedding light on these models' limitations when addressing logical problems. In the paper, researchers demonstrate this through a simple mathematical question. They first posed a question about Oliver picking kiwis: as follows: Oliver picked 44 on Friday.

DiPIR is an innovative technology designed to address the technical challenges of seamlessly inserting virtual objects into real scenes. It achieves this by combining large-scale diffusion models with physics-based inverse rendering processes to accurately recover scene lighting information from a single image, allowing for the natural integration of virtual objects with their environments. The workflow of DiPIR includes constructing virtual 3D scenes, simulating interactions between objects and environments, and optimizing lighting conditions through diffusion models to ensure that generated images conform to real scenes. Its advantages include wide applicability, suitable for scenes under different lighting conditions, and the generation of highly realistic images.

Google DeepMind has released GameNGen, a fully neural network-driven game engine that revolutionizes traditional game image generation methods. GameNGen can generate game visuals in real-time based on player actions, achieving high-quality images that are nearly indistinguishable from reality, with smoothness close to the minimum frame rate perceptible to the human eye. This technology showcases the immense potential of AI in the game development field, which could change game development efficiency, provide personalized experiences, unlock infinite possibilities, and impact game hardware demands and creative approaches.

Claude, the AI large model developed by Anthropic, has introduced a LaTeX formula rendering feature that significantly enhances the clarity and professionalism of mathematical expressions. Key highlights include improved consistency in formatting, standardized display of mathematical equations and expressions, making them easier to understand. The incorporation of LaTeX greatly enhances the clarity of answers, especially suitable for scenarios requiring solutions to mathematical problems. This feature meets the high demands of academic and professional fields, allowing users to quickly generate complex mathematical expressions with simple command inputs.

SenseTime has collaborated with Shanghai Oriental Media Technology Co., Ltd. (SMT) to apply AI 3D motion capture technology and AR special effects rendering engine for the first time in the archery events at the Paris Olympics, jointly creating the 'InnoMotion AI Event Broadcasting Upgrade Solution.' This technology enhances the collection and visualization of archery event data through 3D motion capture and AR effects, providing viewers with a more in-depth and intuitive viewing experience.

The innovative application of Hierarchical 3D Gaussian in virtual reality and computer graphics significantly enhances visual effects, training speed, and real-time rendering capabilities. By constructing a hierarchical 3D Gaussian structure, it efficiently handles large-scale scene datasets, overcoming traditional methods' limitations in sparse scene processing. Utilizing chunked training and hierarchical optimization techniques, it processes te....

Glyph-ByT5 is a model focused on improving the accuracy of text rendering in AI-generated images. Recently, this model has been upgraded to version V2. The new version of Glyph-ByT5 not only enhances its functionality but also significantly increases support for multiple languages, now accurately rendering text in 10 different languages, which greatly enhances its applicability and accuracy in multilingual environments.

The research team proposed a simpler approach, IllumiNeRF: first, a diffusion model under specific lighting conditions is used to relight each input image, and then these relighted images are used to reconstruct a Neural Radiance Field (NeRF) to present new perspectives under the target lighting. They demonstrated that this strategy is surprisingly competitive and achieved state-of-the-art results in several relighting benchmarks.

Ideogram has secured $80 million in funding, attracting investment from Silicon Valley leaders. Its text rendering technology is outstanding, surpassing competitors like Midjourney. The introduction of the Magic Prompt feature lowers the barrier for user-generated content. The affordable pricing strategy contrasts sharply with its powerful features.