苹果公司近日在其研究领域取得了重大突破，推出了全新的自回归视觉模型（AIM），这一创新技术有望重塑计算机视觉领域。在一篇名为《Scalable Pre-training of Large Autoregressive Image Models》的论文中，苹果的研究团队深入探讨了如何利用自回归目标训练视觉Transformer（ViT）模型，以实现与大型语言模型（LLMs）类似的扩展能力。
据机器之心报道，苹果的研究者发现，AIM模型能够轻松应对数十亿级别的参数量扩展，这一发现打破了以往对视觉模型规模的限制。更为重要的是，AIM模型在处理大量未经整理的图像数据时展现出高效能，这为从海量无标签图像中学习深层次的表征提供了可能。
这一创新技术的推出，标志着苹果在人工智能和计算机视觉领域的持续探索和领先地位。AIM模型的应用前景广阔，未来可能在图像识别、自动驾驶、医疗影像分析等领域产生深远影响。通过将自回归模型应用于视觉任务，苹果不仅推动了模型规模的扩展，也为解决实际问题提供了更加强大的工具。
苹果的这一研究成果不仅为学术界提供了新的研究方向，也为业界提供了可能改变游戏规则的技术。随着AIM模型的不断发展和完善，我们有望见证计算机视觉技术在各行业的广泛应用，从而进一步推动人工智能的进步。
英语如下：
**News Title:** “Apple Researchers Breakthrough: Autoregressive Visual Model AIM ushers in a new era of Large-Scale Image Learning”
**Keywords:** Apple AI research, autoregressive model, large-scale pre-training
**News Content:**
Title: Apple Researchers Unveil Autoregressive Visual Model AIM, Paving the Way for a New Chapter in Large-Scale Image Learning
Apple has recently made a significant breakthrough in its research domain with the introduction of the innovative Autoregressive Visual Model (AIM). This development has the potential to reshape the computer vision landscape. In a paper titled “Scalable Pre-training of Large Autoregressive Image Models,” Apple’s research team delves into how to leverage autoregressive objectives for training visual Transformers (ViT) to achieve similar scalability to Large Language Models (LLMs).
As reported by Machine之心, Apple researchers have discovered that the AIM model can seamlessly handle parameter expansions in the billions, breaking previous limitations on the scale of visual models. More importantly, AIM demonstrates high efficiency when processing vast amounts of uncurated image data, enabling the learning of deeper representations from unlabeled images.
This pioneering technology underscores Apple’s ongoing exploration and leadership in the realms of AI and computer vision. The AIM model holds broad application prospects, with potential far-reaching impacts on areas such as image recognition, autonomous driving, and medical image analysis. By applying autoregressive models to visual tasks, Apple not only pushes the boundaries of model scale but also equips problem-solving with more powerful tools.
Apple’s research outcome not only offers new avenues for academic exploration but also presents a game-changing technology for the industry. As the AIM model evolves and matures, we can anticipate the widespread adoption of computer vision technology across various sectors, further propelling the advancement of artificial intelligence.
【来源】https://www.jiqizhixin.com/articles/2024-01-18-7
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