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What exactly is generative AI (artificial intelligence)? And how is it different than the AI we know?
让我们从传统的人工智能开始，它有能力更智能地执行特定的任务. How? It excels at ingesting vast data sets, identifying salient patterns, then making decisions or predictions based on that data. 这些应用程序包括在流媒体服务上建议接下来看什么电影, customer service chatbots and credit card fraud prediction/protection.
In the early 2020s, 变压器驱动的深度神经网络的进步为生成式人工智能平台铺平了道路, including ChatGPT™, Bing Chat™, Bard™, LLaMA™, and DALL-E™. 这些技术是独一无二的——它们也从输入的训练数据中学习模式，但具有生成与训练集具有相似特征的新数据的额外能力. (And they are good — that last sentence was written with Bard.)
This “generation” is what sets it apart. As a recent Forbes article “这就像一个富有想象力的朋友，可以想出原创的、有创意的内容.”
Generative AI’s outputs can take a variety of forms, including text, images, music and even computer code. Generative AI is already being used across a wide variety of industries, including art, writing, software development, product design, healthcare, finance, gaming, marketing and fashion.
McKinsey predicts that generative AI “could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases we analyzed. By comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. 如果我们将生成式人工智能嵌入到当前用于这些用例之外的其他任务的软件中的影响包括在内，这一估计将大约翻倍.”
The applications are almost limitless. In fact, 许多大企业已经认识到这些应用，并已经开始使用生成式人工智能.
Smart manufacturing
According to DeLoitte, 86%的制造商认为，智能工厂将成为未来两年内竞争的主要推动力. Already, 有超过150亿台连接的物联网设备，预计到2030年将超过290亿台，是这个数字的两倍. Big machines using big data are transforming the industrial market, 依靠复杂的生成式人工智能工作负载来管理快速增长的传感器数据.
At Micron, we not only supply critical generative AI memory and storage solutions, we also leverage AI in our own manufacturing processes. 硅制造是一个极其复杂的过程，耗时数月，涉及约1500个步骤. Micron employs sophisticated AI in every step of this process, dramatically improving accuracy and productivity. The benefits are many, including higher output, yield, quality, a safer working environment, improved efficiencies and a sustainable business.
Automotive
生成式人工智能正在通过加速原型设计改变汽车行业, where designers create simple sketches, and the system generates detailed 3D models. These models are refined iteratively, incorporating external market trends, aerodynamic efficiency data, crash and ergonomic simulations, and emerging styles.
生成式人工智能也有可能为自动驾驶汽车的安全推出铺平道路, without putting the public at risk while the technology matures. 因为生成式人工智能可以生成图像和视频来构建现实世界的场景, 自动驾驶汽车可以在可控的环境中学习和适应不同的环境. 这意味着更便宜的现场测试和更直观的算法来训练自动驾驶汽车的决策模型.
On the production side, generative AI optimizes for material distribution, 减少浪费和组装过程和组件设计，更容易和更具成本效益的制造.
Science
Generative AI is heavily impacting scientific discovery, transforming everything from creative content, to synthetic data, to generative engineering and design.
In fact, Gartner predicts that “by 2025, 超过30%的新药物和新材料将通过生成式人工智能技术系统地发现, up from zero today. Generative AI looks promising for the pharmaceutical industry, given the opportunity to reduce costs and time in drug discovery.”
McKinsey analyzed 63用例和预测客户操作，市场营销和销售，软件工程，和R&D across all verticals will be the most heavily affected by generative AI.
What’s Next?
虽然有理由担心生成人工智能可能被滥用, including intellectual property infringement, cybercrime and deepfakes, the possibilities for good are overwhelming.
美光公司的Eric Booth是一名云计算高级业务开发经理，他正在博伊西州立大学攻读博士学位，研究该技术如何帮助有语言障碍的儿童.
“In speech therapy, 我们过去认为，治疗师会给学生提供阅读内容，然后用一个工具来评分他们在发音和发音方面的表现,” explains Eric. “But with generative AI, the tool can actually handle the whole process. It excels in identifying patterns, so it can tell if a student is, for instance, consistently mispronouncing their Os.”
Until recently, speech recognition meant you needed a big server with lots of memory, and everything had to go to the cloud. Now, speech recognition is built into your phone. The compute has gotten faster, the memory has gotten faster, 以前的数据中心进程现在在您的手机或其他端点设备上.
Soon generative AI processes will be on your phone. 因为人工智能模型的训练过程不仅仅是制作更复杂的模型, but also simplifying them to work in endpoint devices such your phone or PC. As these large language models grow, it’s not possible to do the training outside of a cloud environment. 但是，一旦你对它进行训练，然后进行简化，它就可以移动到终端设备上.
Then the power of generative AI is literally in your hand, as a tool, as a companion to help in day to day life. 未来的虚拟助手很可能成为你的个人人工智能伴侣，可以与你一起成长和适应, 从你的经验和数据中学习，以更好地预测和理解你的个人偏好.
Imagine this companion with you from the very beginning. An AI companion that grows alongside you, evolving with every step of your journey, enriching your life at every stage.
As a baby, your AI companion could help nurture your curious mind, could read you stories, play educational games, and spark your imagination, and as you grow, it can follow you from device to device, becoming more intelligent with every passing moment, just like you. 它可以引导你完成你的教育之旅，适应你独特的学习方式. It can help you excel by learning how you best absorb information, and adjusting its methods, presenting concepts in ways that resonate with you, making your education more effective and enjoyable. As a coach, 你的伴侣利用教学上的改进来帮助你做出明智的决定，来打造你的人生道路.
Even as an adult, your AI companion will optimize your schedule and daily tasks, streamlining your workflow and boosting your productivity. 你每天生成的数据被你的人工智能设备用来不断完善和磨练它的技能. 这种类型的技术和经验将由生成人工智能或一些尚未发明的衍生人工智能方法驱动.
Whether it’s manufacturing, automotive, science or other applications, 生成式人工智能及其衍生沙巴体育结算平台将以我们无法想象的方式塑造未来——而美光是驱动你手腕上设备的数据的核心, in your hand, and in the cloud.
生成式人工智能需要一次访问和吸收大量数据，并从大量存储的内存中提取数据，以确定适当的响应. This requires Micron technologies like HBM3E, high density DDR5 DRAM, and multi-terabyte SSD storage, 所有这些都为云中的生成式人工智能训练和推理提供了所需的速度和容量. For endpoint devices like mobile phones, 在功率效率和性能之间取得平衡是人工智能驱动的用户体验的关键. 美光LPDDR5X提供了强大的生成式人工智能所需的速度和带宽.
生成式人工智能的能力发展迅速，用例仍在开发中, but it is easy to see that it has the potential to change our day-to-day lives. Micron’s vision is that this technology will truly enrich the lives of all.