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什么是生成式人工智能?? 它和我们知道的人工智能有什么不同?
Let’s start with traditional AI, which has the ability to perform specific tasks more intelligently. 如何? 它擅长于吸收大量的数据集, 识别显著模式, 然后根据这些数据做出决定或预测. These include 应用程序 like suggesting what movie to watch next on a streaming service, 客服聊天机器人和信用卡欺诈预测/保护.
在21世纪20年代初, progress in transformer-driven deep neural networks paved the way for generative AI platforms, 包括ChatGPT™, Bing聊天™, 吟游诗人™, 骆驼™, 和DALL-E™. These technologies are unique — they also learn patterns from the input training data but have the additional capability to generate new data with similar characteristics as the training set. (他们很好——最后一句话是巴德写的.)
这“一代”是它与众不同的地方. 最近 《沙巴体育结算平台》文章 described it, “It's like an imaginative friend who can come up with original, creative content.”
生成式人工智能的输出可以有多种形式, 包括文本, 图片, 音乐，甚至电脑代码. 生成式人工智能已经被广泛应用于各种行业, 包括艺术, 写作, 软件开发, 沙巴体育结算平台设计, 医疗保健, 金融, 游戏, 市场营销与时尚.
麦肯锡预测 生成式人工智能”可以增加相当于2美元的收入.6万亿到4万亿美元.在我们分析的63个用例中，每年4万亿美元. 相比之下，英国2021年的GDP总额为3美元.1万亿年. This estimate would roughly double if we include the impact of embedding generative AI into software that is currently used for other tasks beyond those use cases.”
应用几乎是无限的. 事实上, many big businesses have recognized these 应用程序 and are already putting generative AI to use.
智能制造
根据德勤, 86 percent of manufacturers believe that smart factories will be the main driver of competition within the next two years. 已经, there are over 15 billion connected IoT devices — and you can expect twice as many — over 29 billion — by 2030. 使用大数据的大机器正在改变工业市场, relying on complex generative AI workloads to manage the rapidly growing sensor data.
在微米, 我们不仅提供关键的生成式人工智能内存和存储解决方案, 我们也在自己的制造过程中利用人工智能. Silicon manufacturing is an extremely complex process, taking months and involving some 1,500 steps. 美光在这一过程的每一步都采用了复杂的人工智能, 显著提高准确性和生产力. 好处很多, 包括更高的产量, 收益率, 质量, 更安全的工作环境, 提高效率和可持续发展的业务.
汽车
Generative AI is transforming the 汽车 industry with accelerated prototyping, 设计师在哪里创作简单的草图, 系统生成详细的3D模型. 这些模型是迭代地改进的, 结合外部市场趋势, 气动效率数据, 碰撞和人体工程学模拟, 新兴风格.
Generative AI also has the potential to pave the way for the safe rollout of autonomous vehicles, 在技术成熟的同时，不会让公众处于危险之中. Since generative AI can generate 图片 and videos to build real-world scenarios, autonomous vehicles can learn and adapt to different environments within a controlled setting. That means less expensive field testing and more intuitive algorithms to train autonomous vehicle decision-making models.
在生产方面, 生成式人工智能优化物料分配, reduced waste and assembly processes and component designs that are easier and more cost-effective to manufacture.
科学
生成式人工智能对科学发现产生了重大影响, 从创意内容转变一切, 合成数据, 生成工程和设计.
事实上, Gartner预测 到2025年, more than 30% of new drugs and materials will be systematically discovered using generative AI techniques, 从今天的零开始. 生成式人工智能在制药行业看起来很有前景, 有机会减少药物研发的成本和时间.”
麦肯锡的分析 63 use case and predicts that customer operations, marketing and sales, software engineering, and R&所有垂直领域的D将受到生成式人工智能的影响最大.
接下来是什么?
While there are justifiable concerns about the potential misuse of generative AI, 包括侵犯知识产权, 网络犯罪和深度造假, 好的可能性是巨大的.
微米’s own Eric Booth — a cloud senior business development manager — is in a doctoral program at Boise State University re搜索ing ways that the technology can help children with speech disabilities.
在语言治疗中, we used to think that the therapist would give the student content to read and then a tool would score how well they did in pronunciation and enunciation,埃里克解释道。. “但有了生成式人工智能，这个工具实际上可以处理整个过程. 它擅长识别模式, 所以它可以判断一个学生是否, 例如, 总是发错o的音.”
直到最近, 语音识别意味着你需要一个拥有大量内存的大型服务器, 所有东西都要放到云端. 现在，你的手机内置了语音识别功能. 计算变得更快了, 内存变快了, and a former data center process is now on your phone or other endpoint device.
很快，生成式人工智能程序将出现在你的手机上. Because the training process for AI models is not just about making more complex models, 还可以简化它们，以便在手机或PC等终端设备上工作. 随着这些大型语言模型的增长, 在云环境之外进行培训是不可能的. But, once you have it trained, and then simplified, it can move to the endpoint device.
然后生成式人工智能的力量就在你的手中了, 作为一种工具, 在日常生活中陪伴你. The future virtual assistant is likely to become your personal AI companion that can grow and adapt with you, learning from your experience and the data that you generate to better predict and understand your personal preferences.
想象一下这个伴侣从一开始就和你在一起. 一个与你一起成长的AI伙伴, 随着你旅程的每一步而进化, 在每个阶段丰富你的生活.
作为一个婴儿, 你的人工智能伴侣可以帮助培养你好奇的头脑, 我可以给你讲故事, 玩益智游戏, 激发你的想象力, 随着你的成长, 它可以跟随你从一个设备到另一个设备, 每时每刻都变得更聪明, 就像你一样. It can guide you through your educational journey, adapting to your unique learning style. 它可以帮助你学习如何最好地吸收信息, 并调整其方法, 以与你产生共鸣的方式呈现概念, 让你的教育更有效、更愉快. 作为教练, your companion leverages instructional improvements to help you make informed decisions to forge your path through life.
即使作为一个成年人, 你的人工智能伴侣将优化你的日程安排和日常任务, 简化工作流程，提高工作效率. The data that you generate every day is used by your AI devices to continually refine and hone its skills. This type of technology and experience will be driven by generative AI or some not-yet-invented derivative AI methodology.
无论是制造业, 汽车, 科学或其他应用, generative AI and its derivatives will shape the future in ways we can’t imagine — and 微米 is at the heart of the data driving the devices on your wrist, 在你的手中, 在云端.
Generative AI needs to access and absorb enormous amounts of data all at once and draw from vast stores of memory to determine proper responses. 这需要美光的技术，比如 HBM3E，高密度 DDR5 DRAM，以及多tb 固态硬盘存储设备, all of which enable the speed and capacity required for generative AI training and inference in the cloud. 对于终端设备，比如移动电话, striking a balance of power efficiency and performance is key for AI-driven user experiences. 微米 LPDDR5X offers the speed and bandwidth needed to have powerful generative AI at hand.
The capabilities of generative AI have advanced rapidly and the use cases for good are still in development, 但很容易看出，它有可能改变我们的日常生活. 美光的愿景是，这项技术将真正丰富所有人的生活.