**加州大学伯克利分校研究团队利用扩散模型实现程序合成新突破**
近日，加州大学伯克利分校的一个研究团队取得重大突破，他们成功将扩散模型应用于程序合成领域，证明了该模型不仅能生成图像和视频，还能合成新程序。这一创新成果在学术界引起广泛关注。
该团队提出了一种基于神经扩散模型的方法，可以直接操作句法树进行程序合成。只需通过手绘草图作为输入，模型就能够通过不断突变修改程序，最终生成能够输出目标图形的有效代码。这一技术革新标志着人工智能在代码生成方面的又一巨大进步。
论文第一作者Shreyas Kapur及其导师计算机科学教授Stuart Russell在研究中发挥了关键作用。该研究成果不仅展示了扩散模型在程序合成领域的巨大潜力，同时也为人工智能在编程领域的应用开辟了新的道路。随着研究的深入，未来或许能够通过简单的手绘指令，让计算机自动生成更为复杂的程序。
目前，该研究团队已公开论文及相关项目地址，同时代码库也已开放供研究者学习使用。行业专家对此表示高度赞赏，认为这一技术将为编程领域带来革命性变革，尤其是在自动化和人工智能快速发展的今天，该技术的实际应用前景非常广阔。
此成果的诞生将进一步推动扩散模型在人工智能各领域的深入应用，标志着人工智能技术在合成图形、视频及程序生成方面的又一里程碑式的进步。
英语如下：
News Title: “New Breakthrough at Berkeley: Sketching Can Generate Graphic Programs with Diffusion Model, Miracles in Programming!”
Keywords: Diffusion Model Technology, Program Synthesis Iteration Optimization, Berkeley Research Breakthrough
News Content: **UC Berkeley Team Achieves Breakthrough in Program Synthesis with Diffusion Model**
Recently, a research team from the University of California, Berkeley, achieved a significant breakthrough by applying the diffusion model to the field of program synthesis, demonstrating that this model can not only generate images and videos but also synthesize new programs. This innovative achievement has attracted widespread attention in academia.
The team proposed a method based on a neural diffusion model that directly manipulates syntactic trees for program synthesis. With hand-drawn sketches as input, the model is able to continuously mutate and modify programs, ultimately generating effective code that can output target graphics. This technological innovation marks another significant advancement in artificial intelligence for code generation.
The first author of the paper, Shreyas Kapur, and his mentor, Professor of Computer Science Stuart Russell, played a crucial role in this research. The achievements not only demonstrate the enormous potential of diffusion models in program synthesis but also open up new avenues for artificial intelligence in programming. With further research, the future may allow computers to automatically generate more complex programs through simple handwritten instructions.
Currently, the research team has published their paper and provided the project’s website address, and the code library is open for researchers to learn and use. Industry experts have expressed high praise for this technology, believing it will bring revolutionary changes to the programming field, especially with its vast practical application prospects in today’s rapidly developing automation and artificial intelligence.
This achievement will further promote the in-depth application of diffusion models in various fields of artificial intelligence, marking another milestone progress in the generation of synthetic graphics, videos, and program synthesis.
【来源】https://www.jiqizhixin.com/articles/2024-07-01
Views: 3