根据一堆数字判定下一个数字

Pause for a second. Think about your organisation; mentally visualise your processes and perform a quick inventory of all the data which you collect. It might be a scribble on a form or a record in a database. I bet that you have a lot of that. Now think more in-depth about your operations and at all the data which you are not capturing. It might include the list of people that walk into your shop or maybe the location of your delivery vans. I am pretty sure that you can think of loads of uncaptured data.

暂停一秒钟。考虑一下您的组织；从心理上可视化您的流程，并对所收集的所有数据进行快速清点。它可能是表单上的涂鸦或数据库中的记录。我敢打赌，你有很多。现在，请更深入地考虑您的操作以及所有未捕获的数据。它可能包括走进您商店的人员列表，或者可能是送货车的位置。我很确定您会想到未捕获数据的负载。

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And the worst part of this is that most probably, you are not doing much with your data. You might be generating a report here and there, but that’s pretty much it. Of course, this is a missed opportunity because only by measuring your processes can you manage them efficiently and effectively. In this day and age, data is considered by many as being the new Gold because it is the primary fuel for our intelligent software. It is highly, pervasive; you can collect it from anywhere, and with the proliferation of digital devices, the availability of information is increasing. Just two years ago, 90% of all the data in the world did not even exist! Because of this, the problems we are facing today are various.

最糟糕的是，您可能没有对数据做太多事情。您可能在各处生成报告，但仅此而已。当然，这是一个错失的机会，因为只有通过衡量您的流程，您才能有效地管理它们。在当今时代，数据被许多人视为新的金牌，因为它是我们智能软件的主要推动力。它是高度普遍的。您可以从任何地方收集信息，并且随着数字设备的普及，信息的可用性也在增加。就在两年前，全世界90％的数据甚至都不存在！因此，我们今天面临的问题多种多样。

First of all, we are creating large volumes of data daily. Computers, wearables, mobile devices and all sorts of sensors are producing 2.5 quintillion bytes of data every day. To visualise the scale of this, if we had 2.5 quintillion pennies, we could cover the entire surface of the earth five times! When you generate so much data, the issue shifts on how to manage it, and that is where Artificial Intelligence (AI) comes into play. The only way to process it is by using AI algorithms capable of digesting large volumes of data, identifying patterns and making sense of it.

首先，我们每天创建大量数据。计算机，可穿戴设备，移动设备和各种传感器每天都在生成2.5亿亿字节的数据。为了可视化这种规模，如果我们有2.5亿便士，我们可以覆盖整个地球五次！当您生成大量数据时，问题就转向如何管理它，这就是人工智能(AI)发挥作用的地方。处理它的唯一方法是使用能够消化大量数据，识别模式并加以利用的AI算法。

As an example, take the manufacturing industry, having hundreds of machines operating at the same time. The amount of data which they produce is enormous. Only an AI is capable of analysing it in real-time, propose prescriptive maintenance, predict future faults and optimise the running of the plant autonomously.

例如，以制造业为例，同时有数百台机器在运行。他们产生的数据量巨大。只有AI能够进行实时分析，提出规范性维护，预测未来故障并自主优化工厂运行。

Second, not all data is adequate for computers. Around 80 to 90% of the data found on the internet is unstructured data, thus needing further processing before a computer can use it. Once again, even though AI is far from being perfect, it can manage to process this unstructured data automatically.

其次，并非所有数据都足以容纳计算机。互联网上大约80％到90％的数据都是非结构化数据，因此在计算机可以使用之前，需要进行进一步处理。再一次，即使AI远非完美，它仍可以设法自动处理这些非结构化数据。

Stock traders monitor local and international news to try to predict fluctuations in the market. But there are hundreds of new channels, some of these are official while others are not. All of them use natural languages (like English, Spanish, Mandarine, etc.) which is unstructured and not understandable by machines. Because of this, AI systems can parse the different news feeds in real-time, translate the text, summarise it and extract the polarity of the news item thus giving stock traders a good indication of the market’s reaction to the particular news item.

股票交易员监视本地和国际新闻，以试图预测市场的波动。但是有数百种新渠道，其中一些是官方的，而其他则不是。它们都使用自然语言(例如英语，西班牙语，普通话等)，这些语言是非结构化的，并且机器无法理解。因此，AI系统可以实时解析不同的新闻提要，翻译文本，对其进行汇总并提取新闻的极性，从而为股票交易者提供了市场对特定新闻的React的良好指示。

Third, one of the internet’s most significant malaise is the lack of reliable or trustworthy data. Here too, the only way to check this data is by using automated techniques.

第三，互联网最重大的弊端之一就是缺乏可靠或可信赖的数据。同样在这里，检查此数据的唯一方法是使用自动化技术。

Newspapers need to harvest stories from various news sources, and it is not always easy to distinguish between fake and real news. Automated systems are capable of doing so with a high degree of accuracy. They can quickly identify the source of the news items, compare it to a list of reliable sources, extract snippets from the text and verify its integrity through other online sources.

报纸需要从各种新闻来源中收集故事，而且区分假新闻和真实新闻并不总是那么容易。自动化系统能够做到高度准确。他们可以快速识别新闻来源，将其与可靠来源列表进行比较，从文本中提取摘要，并通过其他在线来源来验证其完整性。

Parker Coffman on 帕克·科夫曼 ( UnsplashUndersplash)摄

Fourth, the production of data happens at the speed of light. Furthermore, you would never have a single source of data, but you would have to deal with several sources of live data simultaneously.

第四，数据的产生以光速发生。此外，您永远不会只有一个数据源，但是您必须同时处理多个实时数据源。

Imagine if you’re operating a network of CCTV cameras. Having a human watching all the feeds is slow, boring, error-prone and tedious. But an AI can analyse the various feeds simultaneously 24/7 and in real-time, thus raising alerts promptly.

想象一下，如果您正在运行CCTV摄像机网络。让人们观看所有提要很慢，无聊，容易出错且乏味。但是，AI可以同时24/7实时分析各种提要，从而Swift发出警报。

Kenan Süleymanoğlu on 凯南苏莱曼诺古上UnsplashUnsplash

Fifth, data on its own has no value. In a world overloaded with sparse data sources, data only becomes valuable once we augment it with other information and use it correctly.

第五，数据本身没有价值。在充满稀疏数据源的世界中，只有在我们使用其他信息对其进行扩充并正确使用之后，数据才变得有价值。

An automated traffic lights system isn’t much of use if it doesn’t have a camera monitoring the state of the traffic and deciding when to switch the lights. But the combination of a camera system together with intelligent traffic lights makes all the difference and saves commuters precious time waiting for nothing.

如果自动交通信号灯系统没有摄像头监视交通状况并决定何时切换灯光的系统，它的使用就很少。但是，将摄像头系统与智能交通信号灯相结合，将带来所有不同，并为通勤者节省了宝贵的时间，无需等待。

As you can see, data is critical in the world of today. We have seen how its use has made processes efficient, reduced errors and brought value to the organisation. So if you are sitting on a pile of digital data, don’t let it gather dust because if you don’t use it, its a missed opportunity for your organisation. Its as if you have vast reservoirs of fuel, but you’re hesitant to buy a car. Don’t lose time, consult with an expert, explore what you can do with that data, take the plunge and start boosting the engine of your organisation.

如您所见，数据在当今世界中至关重要。我们已经看到它的使用如何使流程高效，减少错误并为组织带来价值。因此，如果您坐在一堆数字数据上，请不要让它聚集灰尘，因为如果您不使用它，这对于您的组织来说是一个错失的机会。好像您有大量的燃油库，但是您犹豫要不要买车。不要浪费时间，咨询专家，探索如何使用这些数据，大跌眼镜，并开始增强组织的力量。

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根据一堆数字判定下一个数字_坐在一堆数字黄金

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