在工业中.0, great minds will literally think alike

The first four revolutions

回顾:

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1. 机械化——1780年. The first industrial revolution, occurring over about 100 years from the mid-18th to mid-19th centuries, began with the use of water and steam power to mechanize manufacturing processes.
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2. Electrification — 1870. In the late 19th and early 20th centuries, electric power came to factories, enabling the assembly line and mass production.
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3. 自动化——1970年. 数字技术, 包括机器人技术, came to the manufacturing process starting around 1970, automating many tasks that humans had previously performed and, 有了互联网, enabling globalization.
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4. Connection and digitization — 2011. Everything — from cars to computers to 机器人 to toasters — is becoming virtually linked in the Connected Age, communicating with and even controlling one another with minimal human intervention. Factories are on their way to running themselves. “Cyber-physical systems” take charge of not only manufacturing but also procurement, maintenance and repairs. The internet of things, robotics and AI are the technologies enabling all this autonomy, 哪一个, 比如人类的大脑, 是由数据驱动的, 分析和记忆.
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As we know, digital technology has sped up time. Everything happens faster now, 哪一个 explains why the fourth revolution — the Connected Age — followed so closely on the heels of the third, the Age of Automation. It comes as no surprise that we are already entering 行业5.0, the Collaborative Age.

行业5.0: the human-machine convergence

The Fifth Industrial Revolution is seeing the beginnings of the convergence of humans and machines. Smartphones and applications are giving way to technologies that live on our bodies, with virtual assistants murmuring directions in our ear, suggesting restaurants for dinner, making reservations on our behalf, 还有更多. But the most paradigm-shattering changes will occur in the workplace.

行业5.0 is about transforming Industry 4.0’s “cyber-physical” manufacturing plants — those using digital technologies to operate factories with minimal human involvement – into “human-cyber-physical” systems.

在这个新范例中, people work alongside collaborative 机器人, 或“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. 例如, a person could now focus on designing products and processes with a “digital twin,” a virtual copy of the factory where a product gets made or the environment where the process is used. 一路走来, in certain 行业, a factory’s ability to communicate directly with customers will enable it to customize and personalize every product. Imagine being able to go to a car manufacturer’s website, choose the car you’d like, and select thousands of features that personalize the car for your use!

当然, smart factories don’t run themselves; they rely on a human force to program, 指导, guide and troubleshoot. The speed at 哪一个 a factory’s 机器人 can process, analyze and respond to data coming from varied sources — sensors, 在线订单, computing devices and wearables — depends on how fast their processors are and how much memory they have. (What’s true for human intelligence is also true for artificial intelligence.)

记忆让它起作用

AI relies on memory and processing speed to generate the right response at the right time. Self-driving cars sort through streams of data coming from multiple sources to make snap decisions — all with a failure tolerance of zero. Manufacturing plants scale production up or down, 订单供应, ship out finished products, and repair and replace equipment autonomously.

行业5.0, like the fourth revolution, relies on data, devices and generative AI. None of these components works without memory. 内存, 事实上, puts the “intelligence” in AI, providing it with the data to run its algorithms and the context for its actions and reactions.

Everything we do happens as a result of sensory input: going to lunch, 因笑话而大笑, saying “I love you” or buying a car. To perform each of these actions, we take in information coming from our senses — of sight, 气味, 味道, hearing and touch — as well as our memories, 情绪, 信仰, 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. Our brains break up incoming information and assign each part to its corresponding area of specialty — one area for visual data, 另一个代表声音, another for emotion and so on.

同样的, instead of using CPUs to process data, most AI systems use graphic processing units (GPUs), a different kind of computing chip that needs a different kind of memory to maximize performance. While a CPU may have eight, 16 or 32 processing cores on a chip or chiplet, GPUs have thousands. This lets them process thousands of data inputs at once, 哪一个 is what data-hungry AI workloads require.

微米’s high-bandwidth memory (HBM) — specifically our latest HBM3E, 世界上最快的, most power-efficient high-bandwidth memory — feeds these hungry GPU cores with enough data to satiate these powerful cognitive computing chips. Our industry-leading 232-layer NAND supports vast quantities of data storage for AI, including the top-of-the-line 美光9400 NVMe™固态硬盘，结果是 25% higher performance and 23% lower response time for graphic direct storage (GDS) 人工智能工作负载.¹ The result is AI — equipped with vast and expansive memory and storage solutions — that reacts in near real time.

在微米, 我们看到了生成式人工智能, 机器人, 无人驾驶飞机, 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 行业5.0. 本质上, we’re building something that is completely differentiated, with great promise for the future.

Bringing human cognition and artificial intelligence (AI) together is the hallmark of the Fifth Industrial Revolution, 一个时代, 现在开始, when people and 机器人 work collaboratively to the benefit of society. 行业5.0 is pushing compute beyond the edge to a world in 哪一个 humans thrive as never before — all because of AI.

A 清晰的 example of this evolution is OpenAI的ChatGPT™. 直到现在, AI models excelled in ingesting lots of data, identifying patterns and pinpointing root causes from a diagnostic perspective. Today, most AI re搜索ers are focused on the next phase, generative AI. And that’s not just because of ChatGPT buzz — it’s also because of the profound potential benefits to enterprises.

“在微米, a big application of generative AI is in our smart 搜索es,” notes Koen De 回来er, vice president of smart manufacturing and artificial intelligence. “Think of internet 搜索 results — the ones you have to click on or comb through to understand their value. Now think of a ChatGPT inquiry, 哪一个 does all this evaluation for you and presents it in a comprehensive summary. We are applying that level of smart functionality to 微米. 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? 工业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.

In fact, far from taking everyone’s jobs, this new technology augments and empowers us. 在微米, AI in our manufacturing process means that our teams no longer focus on mundane tasks. 而, our people are freed up to think creatively and test out innovative insights and actions that could help develop efficient, 可持续发展的沙巴体育结算平台.

The first four revolutions

回顾:

1. 机械化——1780年. The first industrial revolution, occurring over about 100 years from the mid-18th to mid-19th centuries, began with the use of water and steam power to mechanize manufacturing processes.
2. Electrification — 1870. In the late 19th and early 20th centuries, electric power came to factories, enabling the assembly line and mass production.
3. 自动化——1970年. 数字技术, 包括机器人技术, came to the manufacturing process starting around 1970, automating many tasks that humans had previously performed and, 有了互联网, enabling globalization.
4. Connection and digitization — 2011. Everything — from cars to computers to 机器人 to toasters — is becoming virtually linked in the Connected Age, communicating with and even controlling one another with minimal human intervention. Factories are on their way to running themselves. “Cyber-physical systems” take charge of not only manufacturing but also procurement, maintenance and repairs. The internet of things, robotics and AI are the technologies enabling all this autonomy, 哪一个, 比如人类的大脑, 是由数据驱动的, 分析和记忆.

As we know, digital technology has sped up time. Everything happens faster now, 哪一个 explains why the fourth revolution — the Connected Age — followed so closely on the heels of the third, the Age of Automation. It comes as no surprise that we are already entering 行业5.0, the Collaborative Age.

行业5.0: the human-machine convergence

The Fifth Industrial Revolution is seeing the beginnings of the convergence of humans and machines. Smartphones and applications are giving way to technologies that live on our bodies, with virtual assistants murmuring directions in our ear, suggesting restaurants for dinner, making reservations on our behalf, 还有更多. But the most paradigm-shattering changes will occur in the workplace.

行业5.0 is about transforming Industry 4.0’s “cyber-physical” manufacturing plants — those using digital technologies to operate factories with minimal human involvement – into “human-cyber-physical” systems.

在这个新范例中, people work alongside collaborative 机器人, 或“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. 例如, a person could now focus on designing products and processes with a “digital twin,” a virtual copy of the factory where a product gets made or the environment where the process is used. 一路走来, in certain 行业, a factory’s ability to communicate directly with customers will enable it to customize and personalize every product. Imagine being able to go to a car manufacturer’s website, choose the car you’d like, and select thousands of features that personalize the car for your use!

当然, smart factories don’t run themselves; they rely on a human force to program, 指导, guide and troubleshoot. The speed at 哪一个 a factory’s 机器人 can process, analyze and respond to data coming from varied sources — sensors, 在线订单, computing devices and wearables — depends on how fast their processors are and how much memory they have. (What’s true for human intelligence is also true for artificial intelligence.)

记忆让它起作用

AI relies on memory and processing speed to generate the right response at the right time. Self-driving cars sort through streams of data coming from multiple sources to make snap decisions — all with a failure tolerance of zero. Manufacturing plants scale production up or down, 订单供应, ship out finished products, and repair and replace equipment autonomously.

行业5.0, like the fourth revolution, relies on data, devices and generative AI. None of these components works without memory. 内存, 事实上, puts the “intelligence” in AI, providing it with the data to run its algorithms and the context for its actions and reactions.

Everything we do happens as a result of sensory input: going to lunch, 因笑话而大笑, saying “I love you” or buying a car. To perform each of these actions, we take in information coming from our senses — of sight, 气味, 味道, hearing and touch — as well as our memories, 情绪, 信仰, 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. Our brains break up incoming information and assign each part to its corresponding area of specialty — one area for visual data, 另一个代表声音, another for emotion and so on.

同样的, instead of using CPUs to process data, most AI systems use graphic processing units (GPUs), a different kind of computing chip that needs a different kind of memory to maximize performance. While a CPU may have eight, 16 or 32 processing cores on a chip or chiplet, GPUs have thousands. This lets them process thousands of data inputs at once, 哪一个 is what data-hungry AI workloads require.

微米’s high-bandwidth memory (HBM) — specifically our latest HBM3E, 世界上最快的, most power-efficient high-bandwidth memory — feeds these hungry GPU cores with enough data to satiate these powerful cognitive computing chips. Our industry-leading 232-layer NAND supports vast quantities of data storage for AI, including the top-of-the-line 美光9400 NVMe™固态硬盘，结果是 25% higher performance and 23% lower response time for graphic direct storage (GDS) 人工智能工作负载.¹ The result is AI — equipped with vast and expansive memory and storage solutions — that reacts in near real time.

在微米, 我们看到了生成式人工智能, 机器人, 无人驾驶飞机, 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 行业5.0. 本质上, we’re building something that is completely differentiated, with great promise for the future.