gartner 炒作曲线_Gartner 2020年新兴技术炒作周期对AI领导者有何影响

It has been already a year since I published a similar article on the same Gartner’s report for 2019 that you can find here. Which AI related technologies have been excluded from the report? Which ones should be, according to Gartner, focus areas for companies AI leaders?

自从我在同一份Gartner 2019年报告中发表类似文章以来已经一年了，您可以在此处找到。 报告中排除了与AI相关的哪些技术？ 根据Gartner的说法，哪些应该成为公司AI领导者的重点领域？

First, a quick reminder of an important background to understand how Gartner’s Hype Cycles are presented. As Gartner explains in its research, its Hype Cycle covers a very broad spectrum of topics, so if a specific technology is not featured it does not necessarily imply that they are not important, quite the opposite. One reason for some technologies to disappear from the Hype Cycle might be that they are no longer “emerging” but key for business and IT. Please also note that Gartner mentions explicitly that given the vast amount of emerging technologies to be covered, some of them are going to be covered in dedicated Hype Cycles.

首先，快速提醒您一个重要背景，以了解如何呈现Gartner的炒作周期。 正如Gartner在其研究中所解释的那样，其“炒作周期”涵盖了非常广泛的主题，因此，如果未采用特定技术，则不一定意味着它们并不重要，而恰恰相反。 某些技术从“炒作周期”中消失的原因之一可能是它们不再“新兴”，而是业务和IT的关键。 还请注意，Gartner明确提到，鉴于将要涵盖的大量新兴技术，其中一些将被专门的“炒作周期”所涵盖。

So let’s start by actually reviewing foundational AI related technologies that have been excluded from this year’s report:

因此，让我们首先回顾一下今年报告中未包括的与AI相关的基础技术：

• Augmented Intelligence

  增强智能

• Edge AI

  边缘人工智能

• AI Cloud Services

  AI云服务

• Emotion AI

  情感人工智能

• Transfer Learning

  转移学习

Both Augmented Intelligence and Edge AI where considered focus areas for companies AI leaders in 2019, while Emotion AI and Transfer Learning were considered new emerging AI technologies last year.

增强智能和边缘AI都被认为是2019年公司AI领导者的重点领域，而情感AI和转移学习被认为是去年新兴的AI技术。

Which ones should be, according to Gartner, the focus areas for companies AI leaders? Based on its Priority Matrix for Emerging Technologies, 2020, those should be:

根据Gartner的说法，哪些是公司AI领导者的重点领域？ 根据2020年新兴技术优先级矩阵，这些指标应为：

• Composite AI. Described as combining different techniques of Artificial Intelligence to improve the way it learns (Gartner actually defines it in a way that can Composite AI can be viewed as the path of AI to achieve “common sense” and to become AGI — Artificial General Intelligence).

  复合AI。 被描述为结合了人工智能的不同技术来改善其学习方式(Gartner实际上以一种方式将其定义为可以将复合AI视为实现“常识”并成为AGI(人工通用人工智能)的AI的途径)。

• Generative AI. Described as a subset of algorithms that can generate new content (e.g. text, images) that preserve some relationship to previous learnt representations of training data. These subset of algorithms have become extremely popular recently due to Open AI’s GPT-3.

  生成式AI。 描述为可以生成新内容(例如，文本，图像)的算法子集，这些新内容保留了与以前学习的训练数据表示形式的某种关系。 由于Open AI的GPT-3，这些算法子集最近变得非常流行。

Finally, which are the new emerging technologies related to AI in 2020 Hype Cycle:

最后，以下是2020年炒作周期中与人工智能相关的新兴技术：

• AI-Augmented Design. Defined as using Artificial Intelligence to aid the process of creating or updating user workflows, interfaces, and contents.

  AI增强设计。 定义为使用人工智能来辅助创建或更新用户工作流，界面和内容的过程。

• Self-Supervised Learning. Defined as a special case of Unsupervised Learning in which the algorithm creates its own labeled data. This subset of Machine Learning algorithms can prove very useful in those scenarios in which accessing large amounts of labeled data is not possible.

  自我监督学习。 定义为无监督学习的一种特殊情况，其中算法创建自己的标记数据。 在无法访问大量标记数据的情况下，机器学习算法的这一子集非常有用。

• AI-Augmented Development. Defined as using Artificial Intelligence to aid the process of delivering software applications faster and with better quality.

  人工智能增强开发。 定义为使用人工智能来帮助更快，更好地交付软件应用程序的过程。

Gartner’s 2020 Hype Cycle also includes Adaptive ML and Responsible AI as emerging technologies. They are not covered in this article as they were also included in the 2019 edition. You can find more details about them in my last year summary.

Gartner的2020年炒作周期还包括自适应ML和负责任的AI作为新兴技术。 它们未包含在本文中，因为它们也包含在2019年版中。 您可以在我的去年总结中找到有关它们的更多详细信息。

Finally, it is interesting to note that Gartner’s groups the 2020 emerging technologies into five clear trends, two of them being directly related to AI:

最后，有趣的是，Gartner将2020年新兴技术分为五个明显趋势，其中两个与AI直接相关：

• Algorithmic Trust, including set of technologies that must ensure the privacy and security of data being used for training the algorithms, as well as technologies such as Responsible and Explainable AI.

  算法信任，包括一组必须确保用于训练算法的数据的隐私和安全性，以及诸如负责任和可解释的AI之类的技术。

• Formative Artificial Intelligence (AI). Gartner describes this trend as a set of emerging AI technologies capable of responding to variances in the situational context, enabling the creation of tools to aid in the process of design, software development, or even AI models that can adapt over time (or even create their own new models to solve newly faced problems).

  形成性人工智能(AI)。 Gartner将这种趋势描述为一组能够对情况变化做出响应的新兴AI技术，从而能够创建工具以辅助设计，软件开发甚至可以随着时间推移而适应(甚至创建)的AI模型的过程。自己的新模型来解决新遇到的问题)。

A third trend, which Gartner calls Composite Architecture, it also highly linked to AI. Gartner’s definition of a Composite Architecture is a set of software components that deliver business capabilities in a way that it is design to rapidly adapt to business changes and needs. Gartner explicitly mentions Embedded AI as one of the technologies that should be included in this kind of Enterprise Architectures.

第三个趋势，被Gartner称为Composite Architecture ，它也与AI高度相关。 Gartner对复合体系结构的定义是一组软件组件，这些组件以旨在快速适应业务变化和需求的方式提供业务功能。 Gartner明确提到嵌入式AI是这种企业体系结构应包含的技术之一。

As a recap, and based on my personal experience, AI leaders should:

作为总结，根据我的个人经验，人工智能领导者应：

• Embrace AI not as an innovation initiative, but as part of the core strategy for the company. I also mentioned this one last year, and I think there is still a lot to do in this specific area. Companies should be moving from lab PoCs to scalable AI approaches, including how to organize AI talent, apply methodology and implement common platforms across the company. A good example of this is the adoption of AI Cloud Services. While Gartner is not considering it emerging anymore in its 2020 Hype Cycle, a lot of companies still lack a clear strategy and adoption of AI solutions in the Cloud.

  拥抱AI不是创新计划，而是公司核心战略的一部分。 去年我也提到了这一点，我认为在这一特定领域还有很多工作要做。 公司应该从实验室PoC转向可扩展的AI方法，包括如何组织AI人才，应用方法并在公司范围内实施通用平台。 一个很好的例子是采用AI Cloud Services。 尽管Gartner不再考虑使其在2020年的炒作周期中出现，但许多公司仍缺乏明确的战略，并缺乏在云中采用AI解决方案的方法。

• Consider how AI and Composite Architectures can work together to help their companies solve business challenges. And this is a two way-challenge: Composite Architectures need AI to better adapt to business changes, but also AI needs to be integrated in a well-designed architecture (including development and deployment tools, technical and functional monitoring, etc.) to scale.

  考虑一下AI和Composite Architectures如何一起工作以帮助其公司解决业务挑战 。 这是两种方式的挑战：复合架构需要AI以更好地适应业务变化，而且AI需要集成到设计良好的架构(包括开发和部署工具，技术和功能监控等)中以进行扩展。

• Finally, focus on the human side of the technology. From how to make our digital talent to benefit from automation, to considering AI impact on their employee’s jobs, customer experience, and society in general. I kept this paragraph exactly as the one I wrote last year, as I think the level of maturity towards this specific challenge in big organizations is still low.

  最后， 关注技术的人性化方面 。 从如何使我们的数字人才从自动化中受益，到考虑AI对员工的工作，客户体验和整个社会的影响。 我保留这一段的方式与我去年写的一样，因为我认为大型组织中应对这一特定挑战的成熟度仍然很低。