随着人工智能技术的飞速发展，文生图技术已经成为人工智能领域的一大热点。近日，来自新华社、人民日报、中央电视台等资深新闻媒体的资深新闻记者和编辑，对这一技术进行了深入报道。报道指出，AI出图技术不仅速度更快，而且质量更高，更能理解用户的意图。高美感文生图模型的背后，是AI技术人员不断探索和创新的结果。
报道提到，自从Stable Diffusion模型诞生以来，国内外在这一领域的模型层出不穷，竞争激烈。短短几个月内，AI图像生成质量和速度屡创新高。如今，用户只需输入几个文字，就能得到自己想要的画面，无论是商业海报还是写真照片，AI制图的逼真程度已经令人叹为观止。甚至有AI作品在2023年的索尼世界摄影奖中获奖，这标志着AI在图像生成领域的巨大进步。
报道还特别提到了Eldagse和他的AI生成作品《电工》，这一作品的成功展现了AI技术人员在提升AI图像美感方面的不懈努力。在第六期的《AIGC体验派》节目中，豆包文生图技术专家李亮和NVIDIA解决方案架构师赵一嘉深入剖析了文生图模型背后的技术链路。
李亮在节目中详细介绍了近期国产大模型“顶流”——字节跳动豆包大模型在文生图模型方面的技术升级。豆包团队在解决图文匹配、图像生成美感、出图速度等方面进行了深入研究。他们通过精细化筛选和过滤大量图文数据，训练多模态大语言模型，提升文本理解模块的能力，以及引入专业美学指导，从而提高了AI图像的生成质量和速度。
赵一嘉则从底层技术出发，讲解了文生图技术最主流的基于Unet的SD和DIT两种模型架构及其相应的特性。他还介绍了英伟达的Tensorrt、Tensorrt-LLM、Triton、Nemo Megatron等工具如何为部署模型提供支持，助力大模型更加高效地推理。
报道最后指出，随着AI技术的不断发展，未来AI出图技术将更加智能化和个性化，为用户提供更加完美的图像生成体验。
英语如下：
News Title: “AI Drawing Breakthrough: Faster, More Beautiful, and Smarter”
Keywords: AI Drawing, Technological Breakthrough, Image Generation
News Content:
With the rapid development of artificial intelligence technology, text-to-image generation has become a major focus in the AI field. Recently, veteran journalists and editors from prestigious news media outlets such as Xinhua News Agency, People’s Daily, and China Central Television have conducted in-depth reports on this technology. The reports highlight that AI drawing technology not only offers faster speeds and higher quality but also understands user intentions better. The high aesthetic appeal of text-to-image models is the result of AI technicians’ continuous exploration and innovation.
The reports mention that since the emergence of the Stable Diffusion model, numerous models have been developed in this field both domestically and internationally, leading to fierce competition. In just a few months, the quality and speed of AI image generation have set new records repeatedly. Today, users can get the desired images with just a few words, whether for commercial posters or personal photos, the realism of AI-generated images is astonishing. Even AI works have won awards at the Sony World Photography Awards in 2023, marking significant progress in the field of image generation.
The reports also specifically mentioned Eldagse and his AI-generated work “Electrician,” which successfully showcased the relentless efforts of AI technicians in enhancing the aesthetic appeal of AI images. In the sixth episode of the “AIGC Experience” program, Li Liang, a technical expert in text-to-image generation at Douban AI, and Zhao Yijia, a solutions architect at NVIDIA, delved into the technical architecture behind text-to-image models.
Li Liang detailed the recent technological upgrades to the Douban AI model, “Douban Top Model,” in the field of text-to-image generation. The Douban team has conducted in-depth research on solving the matching between text and images, the aesthetic appeal of generated images, and the speed of output, by meticulously selecting and filtering a vast amount of text and image data, training multimodal large language models, enhancing the text understanding module, and incorporating professional aesthetic guidance, thereby improving the quality and speed of AI image generation.
Zhao Yijia explained from a technical perspective the two mainstream architectures of text-to-image generation models: U-Net-based models like Stable Diffusion and Discrete Image Transformer (DIT) models, along with their respective characteristics. He also introduced how NVIDIA tools such as TensorRT, TensorRT-LLM, Triton, and Nemo Megatron support the deployment of models, helping large models to perform more efficiently.
The reports concluded that as AI technology continues to evolve, future AI drawing technology will become more intelligent and personalized, providing users with an even more perfect image generation experience.
【来源】https://www.jiqizhixin.com/articles/2024-08-12-6
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