将人类认知和人工智能(AI)结合在一起是第五次工业革命的标志, an era, beginning now, 当人类和机器人协同工作，造福社会. Industry 5.正将计算推向一个人类前所未有地繁荣的世界——这一切都是因为人工智能.
A clear example of this evolution is OpenAI’s ChatGPT™. Until now, AI models excelled in ingesting lots of data, 从诊断的角度识别模式并确定根本原因. 今天，大多数人工智能研究人员都专注于下一个阶段，即生成式人工智能. 这不仅仅是因为ChatGPT的热议，还因为它对企业有深远的潜在好处.
“At Micron, a big application of generative AI is in our smart searches,” notes Koen De Backer, vice president of smart manufacturing and artificial intelligence. “想想互联网搜索结果——你必须点击或梳理才能了解它们的价值. Now think of a ChatGPT inquiry, 哪一个为你做了所有这些评估，并在一个全面的总结中呈现出来. We are applying that level of smart functionality to Micron. The efficiency is staggering.”
Yet generative AI is worrying to many: Will I lose my job to a robot? Will I have to give up driving? Is my personal privacy gone forever? In Industry 5.0, these worries won’t feel so pressing. Enabled by new technologies, machines will naturally perform the tasks they do best, freeing us to focus on other more important tasks.
事实上，这种新技术并没有夺走每个人的工作，而是增强了我们的能力. 在美光，人工智能在我们的制造过程中意味着我们的团队不再专注于平凡的任务. Rather, 我们的员工可以自由地进行创造性思考，并测试有助于提高效率的创新见解和行动, sustainable products.
The first four revolutions
A recap:- Mechanization — 1780. The first industrial revolution, 发生在18世纪中期到19世纪中期的大约100年间, 开始使用水和蒸汽动力来机械化制造过程.
- Electrification — 1870. In the late 19th and early 20th centuries, electric power came to factories, enabling the assembly line and mass production.
- Automation — 1970. Digital technologies, including robotics, came to the manufacturing process starting around 1970, automating many tasks that humans had previously performed and, with the internet, enabling globalization.
- Connection and digitization — 2011. 在互联时代，一切——从汽车到电脑，从机器人到烤面包机——正在变得几乎相互关联, 在最少的人为干预下相互沟通甚至控制. Factories are on their way to running themselves. “信息物理系统”不仅负责制造，还负责采购, maintenance and repairs. The internet of things, robotics and AI are the technologies enabling all this autonomy, which, like the human brain, is driven by data, analytics and memory.
As we know, digital technology has sped up time. Everything happens faster now, 这就解释了为什么第四次革命——互联时代—— 紧随第三次革命之后, the Age of Automation. It comes as no surprise that we are already entering Industry 5.0, the Collaborative Age.
Industry 5.0: the human-machine convergence
第五次工业革命见证了人类和机器融合的开始. 智能手机和应用程序正在让位于生活在我们身体上的技术, with virtual assistants murmuring directions in our ear, suggesting restaurants for dinner, making reservations on our behalf, and much more. But the most paradigm-shattering changes will occur in the workplace.
Industry 5.0 is about transforming Industry 4.美国的“网络-物理”制造工厂——那些使用数字技术在最少的人力参与下运营工厂的工厂——进入了“人-网络-物理”系统.
In this new paradigm, people work alongside collaborative robots, or “cobots,” teaching them to do jobs and correcting them when they err. While machines perform the most menial, repetitive and dangerous tasks, people use their intricate, flexible brains to make high-level decisions. For example, 一个人现在可以专注于设计沙巴体育结算平台和流程的“数字双胞胎”,“制造沙巴体育结算平台的工厂或使用工艺的环境的虚拟副本. Along the way, in certain industries, 工厂与客户直接沟通的能力将使其能够定制和个性化每件沙巴体育结算平台. Imagine being able to go to a car manufacturer’s website, choose the car you’d like, 并选择数以千计的功能，个性化的汽车为您的使用!
Of course, smart factories don’t run themselves; they rely on a human force to program, instruct, guide and troubleshoot. The speed at which a factory’s robots can process, analyze and respond to data coming from varied sources — sensors, online orders, 计算设备和可穿戴设备——取决于它们的处理器有多快和内存有多大. (适用于人类智能的道理同样适用于人工智能.)
Memory makes it work
人工智能依靠内存和处理速度在正确的时间产生正确的反应. 自动驾驶汽车对来自多个来源的数据流进行分类，以快速做出决定——所有这些都是零容错. Manufacturing plants scale production up or down, order supplies, ship out finished products, and repair and replace equipment autonomously.
Industry 5.就像第四次革命一样，它依赖于数据、设备和生成式人工智能. None of these components works without memory. Memory, in fact, puts the “intelligence” in AI, 为它提供运行算法的数据，以及它的行动和反应的上下文.
Everything we do happens as a result of sensory input: going to lunch, laughing at a joke, saying “I love you” or buying a car. To perform each of these actions, we take in information coming from our senses — of sight, smell, taste, hearing and touch — as well as our memories, emotions, beliefs, thoughts and intuition. Then we process it all at once. Unlike central processing units (CPUs), our brains don’t have a discrete number of “cores” where data goes in, is analyzed and sorted, and gets sent out for an action or result. 我们的大脑将传入的信息分解，并将每个部分分配到相应的专业区域——一个区域负责视觉数据, another for sound, another for emotion and so on.
Likewise, instead of using CPUs to process data, most AI systems use graphic processing units (GPUs), 一种不同的计算芯片需要不同的内存来最大化性能. CPU在一个芯片或小芯片上可能有8个、16个或32个处理核心，而gpu有数千个. This lets them process thousands of data inputs at once, which is what data-hungry AI workloads require.
Micron’s high-bandwidth memory (HBM) — specifically our latest HBM3 Gen2, the world’s fastest, 最节能的高带宽内存——为这些饥渴的GPU内核提供足够的数据，以满足这些强大的认知计算芯片. 我们业界领先的232层NAND支持人工智能的大量数据存储, including the top-of-the-line Micron 9400 NVMe™ SSD, which shows up to 图形直接存储(GDS)的性能提高25%，响应时间降低23% in AI workloads1. 其结果是人工智能——配备了巨大而扩展的内存和存储解决方案——可以近乎实时地做出反应.
At Micron, we see generative AI, robots, drones, self-driving cars and other forms of AI excelling in learning, intelligence and response times. So, we’re using it to foundationally optimize our processes. From manufacturing to business processes, we’re transforming into an AI smart ecosystem across the enterprise, innovating memory and storage to supercharge Industry 5.0. Essentially, we’re building something that is completely differentiated, with great promise for the future.
1 25% higher performance and 23% lower response time 在繁忙的GDS系统中执行4KB传输时，与竞争对手相比.