大数据中国

搜索
大数据中国 首页 热点综合 热点科技 查看内容
展望2019:五大未来技术趋势
2018-12-14 02:06 |原作者: 王婕(译)|来自: 数据观| 查看: 1739| 评论: 0

Technology futures in 2019 and beyond

【编者按】岁末已至,2019年即将到来,你和你所处的行业是否已准确把握了未来技术变革的趋势?是否已做好迎接行业升级换代的心理准备?

身份管理将成为区块链的一大杀手锏、商业模式将因数据价值而被重塑、健康大数据平台将会进一步衍生......本文中,美国达科公司首席技术官Ettienne Reinecke从五个方面给出了他的判断。

Ettienne Reinecke

Ettienne Reinecke

△Trend 1: Easier access will accelerate adoption of game-changing technologies

趋势一:便捷访问将加速颠覆性技术落地

Until now, our industry has spoken about innovative technologies somewhat theoretically, without providing a clear picture of how these powerful new innovations will be used. This has left people without a solid understanding of how they will ultimately manifest in our work and personal lives. Think analytics, machine learning, artificial intelligence, blockchain, and containers, just to name a few.

截至目前,我们业内在某种程度上谈论的都是理论上的创新技术,没有提供如何利用这些强大创新的清晰蓝图,人们对于这些技术终将如何体现在工作和个人生活中缺乏透彻的了解。就这一点,你只要想想分析学、机器学习、人工智能、区块链和容器就知道了,而这只是其中的几个例子。

That’s starting to change. The application of game-changing technologies is becoming more pervasive and their adoption is growing steadily. I believe that they’ll be firmly embedded in many of the core processes and technologies we use, within the next 3-5 years.

这种情况正在开始改变。颠覆性技术的应用越来越普遍,它们被采用的频率也在稳步增长。我相信,在未来3-5年内,这些技术将被深植到多数核心流程和科技中。

Last year, I predicted that artificial intelligence (AI), machine learning, robotics, and virtual and augmented reality would start to converge to deliver compelling outcomes. Over the last year, we’ve seen this trend coming to fruition and I expect it to accelerate.

去年,我预测人工智能(AI)、机器学习、机器人技术、虚拟现实(VR)和增强现实(AR)技术的汇聚将产生令人瞩目的成果。在过去一年里,我们已经看到了这一趋势的实现,我预期它还会加速。

One reason that adoption is increasing, is an improved understanding of how and where to use such technologies. And of course, we’re also seeing growth in the number of skilled people who know how to leverage them.

这些技术被广泛采用的原因之一,就是大众对于何时何式使用这种技术有了更好的理解。当然,我们还看到,越来越多的技术人才懂得了如何利用这些技术。

Easier access is already accelerating adoption of key technologies

便捷访问助推关键技术的运用

Another important contributing factor for more rapid adoption is improved access to such technologies, both from a platform and cost perspective. The hyperscale cloud providers at an infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a service (SaaS) level, such as Google, Microsoft, Amazon, and Salesforce are starting to embed these capabilities into their offerings, or making them available as a platform to be used by third parties.

另一个促使新技术迅速被采用的重要因素是此类技术的获取途径在平台和成本方面得到了改进。基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS)级别(如Google、Microsoft、Amazon和Salesforce)的超大规模云服务提供商开始将这些功能嵌入到它们的产品中,或者将它们作为可供第三方使用的平台。

This is helping businesses overcome the hurdles they’ve faced in the past. Now they can get access to game-changing technologies without having to invest in building their own algorithms and platforms. Instead they can focus on how to exploit these technologies and speed up the rate at which they get business value.

这有助于企业克服过去面临的障碍。现在,他们无需投资构建自己的算法和平台,就可以使用这些颠覆性技术。同时有别于此,他们还可以专注于如何开发这些技术,并加快其获取商业价值的速度。

Bots and robotic process automation are already becoming part of our everyday working and personal lives. It’s relatively simple to create a bot that will access all a company’s sales support systems, and provide a consolidated dashboard. These dashboards can be unique to each customer service employee – paving the way for more informed decisions. This can now be taken to the next level, for example, by leveraging an AI application like Salesforce’s Einstein. This tool can make recommendations and predictions on next actions and outcomes based on unique business processes and customer data. Individuals simply can’t access these kinds of insights without this level of assistance. It’s changing the way we work, the service levels we can provide, and our effectiveness.

自动程序和机器人过程自动化已经成为我们日常工作和个人生活的一部分。创建一个可以访问公司所有销售支持系统,并提供统一控制面板的自动程序相对简单。这些控制面板对于每个客户服务人员都是独一无二的——为他们做出更为明智的决策铺平了道路。现在可以将这一工具提升到下一个层次,例如利用Salesforce的Einstein这样的人工智能应用程序。该工具可以基于独有的业务流程和客户数据,对下一步操作和结果提出建议和预测。没有这种程度的帮助,个人根本无法获得这类深刻洞见。它正在改变我们的工作方式、服务水平,以及效率。

Bots have been used in omnichannel customer service centres for some years now, but even this world is being re-engineered by the introduction of AI algorithms that can assess the emotive state of a customer interaction. This is achieved by assessing words, phrases, tone, or pitch across multiple channels, either spoken or written, to assess the emotional state of the customer, in real time. The moment a negative emotive interaction is identified, appropriate action can be taken, either by changing the channel or method of interaction.

自动程序已经在全渠道的客户服务中心使用了好几年,但即便是我们所处的这个世界,也因为引入了能够评估客户交互情绪状态的人工智能算法而正在被重塑。这是通过评估单词、短语、音调或音高、通过口头或书面的多种渠道,实时评估客户的情绪状态来实现的。一旦消极情绪主导下的互动被确认, 就可以通过改变相互交流的渠道或方法来采取适当的行动。

3D printing has also been around for some time, mainly based on resin or epoxy-based materials, but we’ve seen this move quickly to metal-based 3D printing, which is opening up a multitude of new use cases. General Electric is one of the trailblazers of 3D metal printing. They’re already using it to print fuel nozzles for jet engines. Nike are using it to adapt the spikes on their running shoes to ensure the most appropriate strength, fit, and flexibility required by the customer, depending on what surface they plan to wear them.

3D打印也已经出现了一段时间了,它主要基于树脂或环氧材料而实现,但我们已经看到,3D打印很快便转向了基于金属的3D打印,并已有许多新案例出现。通用电气(General Electric )是3D金属打印的先驱之一,他们已经在用它打印喷气发动机的燃料喷嘴。Nike也正在依据不同的鞋面料来使用3D金属打印调整他们跑鞋上的鞋钉,以确保达到最合适的强度、合适度以及客户所需的灵活性。

△Trend 2: Identity will emerge as the killer app for blockchain

趋势2:身份将成为区块链的杀手级应用

There’s been a massive amount of investment in blockchain in the last 12 months. In the financial and capital markets, blockchain-based platforms are rapidly starting to dominate. We’re now starting to see this extend to additional settlement areas such as equity trading. There’s also been a proliferation of blockchain-based smart contract platforms across multiple vertical segments, both in the private and public sectors.

在过去的12个月里,区块链行业涌入了大量的投资。在金融和资本市场,区块链平台正迅速开始占据主导地位。如今我们可以看到这一趋势正延伸到股票交易等其他结算领域,基于区块链的智能合同平台也在私营和公共部门的多个垂直领域迅速发展。

The market is starting to see ecosystems of value emerging around the blockchain platform vendors, such as R3/Corda, Ripple, and Ethereum. Platform providers are beginning to align to verticals or specialised applications, and it’s interesting to observe the emergence of ecosystem incubators developing additional applications for a specific vertical, on a particular platform.

区块链平台供应商周围的价值生态系统开始崭露头角,如R3/Corda、Ripple和Ethereum(以太坊)。平台提供商开始向垂直或专门的应用程序靠拢,观察生态系统孵化器在特定平台上为垂直领域开发额外应用程序不失为一件趣事。

I believe identity management will emerge as one of the killer apps for blockchain in the next 3-5 years. It’s a topic that’s never quite been resolved in our industry. Most of the major cybersecurity incidents that have occurred in the last few years have involved breaches of people’s personal identity information.

我相信在未来3-5年,身份管理将成为区块链的杀手级应用之一。在我们这个行业,这是一个从来都没有完全被解决的议题。在过去几年发生的大部分重大网络安全事件中,都涉及到对个人身份信息的侵犯。

I believe that moving identity management into a blockchain environment could offer a solution to many of the current challenges, and in addition, open an entire new value chain, centred on identity. The high levels of encryption and the dispersed nature of data in a distributed ledger, are inherent to a blockchain. This immediately changes the level of cyber safety that can be offered, certainly solving one problem.

我相信,将身份管理迁移到区块链环境中可以解决当前的许多挑战,而且,还可以打开一个以身份为中心的全新价值链。在分布式账本中,高级加密性和数据的分散性是区块链与生俱来的特点,这一特性毫无疑问地改变了可以达到的网络安全级别,也就理所当然地解决了前文所提到的问题。

Consider the other value chains that could emerge … perhaps allowing individuals to truly own and control their identity and its attributes, and selectively allowing the use of such attributes by third parties in transactions or interactions. This could fundamentally change how we conduct financial transactions or even sensitive interactions regarding our health ─ all attributes relating to our identity.

设想一下这条可能出现的其他价值链……这也许将允许个人真正拥有和控制他们的身份及其属性,并且可以选择性地允许第三方在交易或交互中使用这些属性。这将从根本上改变我们进行金融交易的方式,甚至参与有关我们健康方面的敏感交互——所有特质都与我们的身份有关。

These models have the potential to extend into much wider ecosystems, and drive monetisation of data related to identity attributes. Take a simple example: a high school might become an important third-party validator of the educational level that their students achieved ─ an attribute of somebody’s identity. Allowing the school to participate in a transaction, in return for a small payment, will, for the first time, enable the school to monetise data that they collect and own, and open up a revenue stream they never considered before.

这些模式有可能扩展到更为广泛的生态系统,并推动与身份属性相关的数据实现货币化。举一个简单的例子:一所高中可能同时也是一个验证学生受教育水平的重要第三方验证程序─这涉及到了某个个体的身份属性。如果允许学校参与交易来换取一小笔款项,将首次使学校能够将他们收集和拥有的数据货币化,并开辟一条他们从未考虑过的收入来源。

There’s no doubt that blockchain-based innovation will expand and accelerate over the next 3-5 years.

毫无疑问,基于区块链的创新将在未来3-5年内扩张和加速。

△Trend 3: Companies will learn how to extract value from data, while respecting privacy

趋势3:企业将会学习如何在尊重隐私的前提下从数据中提取价值

Data value management is a topic that will dominate our industry in the next 3-5 years.

数据价值管理是未来3-5年将主导我们行业的一个主题。

Today, almost every company has access to large volumes of data. But it’s what they do with that data that will define the business models of the future. This isn’t necessarily a new statement, but the context and impact has escalated dramatically. Current business models will be re-engineered by the value of the data that’s generated by existing activities. The value of the data will supersede the value of traditional revenue activities ─ an interesting concept in its own right.

如今,几乎每家公司都可以访问大量数据,但他们对这些数据的处理方式将决定其未来的商业模式。这未必是一个新的论断,但这一论断提出的背景和影响已急剧升级。当前的商业模式将根据现有活动生成的数据的价值而被重塑,数据的价值将取代传统商业创收活动的价值—— 这本身就是一个有趣的概念。

Let’s take a transport operator as an example. Traditionally they’ve generated their revenue from passengers’ fares. But as they implement more intelligent systems, and connect the data elements to one another, the data becomes the primary source of value, not the transport service. They know who their passengers are, where they’re going and coming from, and when. If they collect and enrich this data they could monetise it by making it available to a host of other businesses for more targeted service delivery–at a premium. The result? An entirely new business model and revenue stream.

让我们以运输运营商为例:一般来说他们的收入大多来自乘客的票费,然而一旦他们运行更为智能的系统并将数据元素彼此连接起来,数据就成为了主要的价值来源,而不是运输服务本身。他们能够知道他们的乘客是谁,他们从哪里来、要往何处去以及何时出发。如果他们能够收集并不断丰富这些数据,他们就可以通过向其它企业提供这些数据来实现数据的货币化,从而提供更有针对性的服务以及收取更高的费用。采取这一模式的结果是什么?毫无疑问,他们将收获全新的商业模式和收入来源。

The concept of data value management will become one of the most important investment areas over the next 3-5 years due to its monetary value potential, but it will also become one of the major driving forces of investment to create more data. Businesses have strived to become more digital in nature, but those that excel in managing the value of their data, re-engineering their business models, and establishing new revenue streams, will become the true digital business heroes of the future.

数据价值管理的概念由于其货币价值潜力将成为未来3-5年最重要的投资领域之一,同时它也将成为投资创造更多数据的主要驱动力之一。虽然许多企业已经努力使其在本质上变得更加数字化,但那些擅长管理数据价值、能够重建商业模式和收入来源的企业,将成为未来真正的数字化商业英雄。

Monetisation of data must respect privacy

数据货币化必须尊重隐私

Of course, ensuring that people’s personal particulars aren’t shared illegally is critical for any business considering going down this path. Regulations regarding data privacy continue to grow, both at a country and vertical industry level. Fortunately, the increasing interest in data value management is spurring massive innovation to address the issue of privacy.

当然,确保人们的个人信息不被非法共享对于任何考虑走这条路的企业来说都是至关重要的。在国家和垂直行业级别,有关数据隐私的法规数量在不断增长。幸运的是,人们对数据价值管理越来越感兴趣,这也促使人们进行大规模创新,以解决隐私问题。

Data sources are growing, the granularity of the data itself is improving, and because of this the potential value that can be extracted is growing even faster. The increasing challenge is how to derive insights from disparate and distributed data sources, without infringing regulatory or basic confidentiality guidelines. Anonymised data analytics at scale is an ongoing challenge and finding ways to gain the rich insights without sharing source data or causing breaking the law will become barriers to growth, if not solved.

数据源在增长,数据本身的粒度(指数据仓库中数据的细化和综合程度)也在改进,因此可以挖掘的潜在价值增长得更快。如今人们所面临的越来越大的挑战是如何在不违反法规或基本保密准则的情况下,从不同的分布式数据源获取信息。大规模匿名数据分析是一个持续的挑战,如果不解决这一问题,找到可以在不共享源数据或不导致违法的情况下获取丰富信息的方法,这一挑战将成为数据价值增长的阻碍。

Working with our parent company, NTT, we’re fortunate beneficiaries of deep R&D investment in this area, and have access to a secure computation platform known as San-Shi. It uses secret sharing and secure multi-party computational principles to allow data scientists to aggregate and analyse massive distributed data sets without ever revealing the source data to the analyst. Judging by the interest we’ve received in this solution, we believe this is an area of increasing importance to the wider business community, as they strive to unlock the value of data.

通过与我们的母公司NTT合作,我们有幸成为了这一领域深度投研的受益者,并能够访问一个名为San-Shi的安全计算平台。它使用秘密共享和安全的多方计算原则,允许数据科学家聚合和分析大量分布式数据集,而无需向分析人员透露源数据。根据我们对这一解决方案的兴趣来判断,我们相信对于更广泛的商界来说,这是一个越来越重要的领域,因为他们正在努力解锁数据的价值。

△Trend 4: The Internet of Everything will change our lives for the better

趋势4:物联网将使我们的生活变得更美好

The number of things connected to the Internet in 2008 exceeded the number of people on earth. By 2020, it’s expected that 50 billion things will be connected, and this goes way beyond ‘things’, it becomes ‘everything’ or simply the Internet of Everything (IoE). The IoE ecosystem will connect the online and physical worlds in ways we’ve never imagined and society will become increasingly technology-driven as a result. There’s not a part of our lives that will go untouched. Automation will take on a new meaning, data value management will be accentuated by the richness of data, and AI will ingest the data to drive intelligent insights and outcomes we’ve never seen before.

2008年,连接到互联网上的事物的数量超过了地球上的人数。到2020年,预计将有500亿件事物被连接起来,而这已经远远超过了“事物”的范畴,它将成为“一切”,或者简单来说也就是“物联网”(IoE)。物联网生态系统将以我们从未想象过的方式连接网络和物理世界,也正因为如此,社会的发展将越来越受技术驱动。我们的生活中没有哪一部分是一成不变的,自动化将被赋予新的意义,数据价值管理将因为数据的日益丰富而越显突出,同时,人工智能将吸收这些数据来推动生成我们从未领略过的智能洞察和成果。

The human API will evolve

Human API 平台的演化

The IoE will encompass every area of our lives, transforming the way we provide healthcare, and the way we live, work and learn. It will re-engineer our lives through what we increasingly refer to as the‘human API’enabling us to interface with various connected systems in ways that are hard to anticipate. The scope of biometrics will expand from what we understand today, to include gestures, emotions, expressions, and many more aspects, triggering automated system reactions to complement, ease, or enhance our activities.

物联网将涵盖我们生活的每一个领域,改变我们提供医疗保健的方式,以及我们的生活、工作和学习方式。它将通过我们日益频繁提到的“Human API”(美国知名医疗大数据平台)重塑我们的生活,使我们能够以难以预料的方式与各种连接系统进行交互。生物识别技术的范围将从我们今天所了解的内容扩展到包括手势、情绪、表情和许多其他方面,并能够触发自动系统做出反应,以补充、减轻或增强我们的活动。

Leading technology innovators are already finding life-changing use cases for the IoE and human API. Dimension Data recently worked with NTT R&D and Deakin University in Australia on a project that uses virtual reality, biometric sensors, wearables, and data analytics to transform the way that firefighters are trained.

领先的技术创新者已经在为物联网和人类API寻找可以改变生活的可能案例。达科公司(Dimension Data)最近同NTT R&D(日本最大移动运营商NTT研究与开发部门)以及澳大利亚迪肯大学(Deakin University)合作开发了一个项目,该项目使用虚拟现实、生物识别传感器、可穿戴设备和数据分析来改变消防员的培训方式。

This innovation, known as the FLAIM Trainer®, reproduces all the forces and elements that impact a firefighter, connecting the virtual and the physical. It allows firefighters to train for dangerous scenarios that are difficult, expensive, and environmentally harmful to reproduce in reality. It incorporates a patented digital bio-sensing fabric developed by NTT, called Hitoe™, which provides real-time data on firefighters’ vital signs such as heart rate, stress, and fatigue. When aggregated, this data allows instructors to assess a trainee’s fitness and mental state to fight in any given fire scenario.

这种被称为FLAIM Trainer®的创新(澳大利亚迪肯大学智能系统研究所设计的一套VR火灾培训体验),不仅再现了所有作用力和因素对一名消防员的影响,还将虚拟空间和物理空间连接在了一起。它允许消防队员在危险的情况下进行训练,而这些情况通常在现实中很难重现,因其代价昂贵且对环境有害。它集成了一个由NTT自主研发并已成功申请专利的数字生物传感器——Hitoe™,这一产品能够提供消防队员生命体征的实时数据,如心率、压力和疲劳程度。这些数据汇总后,可以帮助教练来评估学员在任何给定火灾场景下的健康状况和心理状态。

△Trend 5: Disruption will drive consolidation among tech vendors

趋势5:变革将推动技术供应商之间的整合

I foresee a period of unprecedented change and disruption for major technology vendors driven by factors largely outside of their control. Not only are technology consumption patterns changing, but how innovation is driven, products are developed, and intellectual property is shared in an opensource and free manner. All of this is driving disruptions that are hard to predict or manage.

我判断,技术供应商们将经历一段主要由不可控因素驱动的前所未有的变革和混乱时期。不仅技术消费模式会改变,创新驱动、产品开发、知识产权共享的方式也会改变。所有这些因素都导致了难以预测或应付的颠覆局面。

The emergence of new technology giants, with very different business models, is driving some of this change – and shifting the landscape at a scale not seen before. The increasing market dominance of the FAANGs – a term coined to describe Facebook, Amazon, Apple, Netflix, and Google – and a resurgent Microsoft, are leading this disruption.

拥有截然不同商业模式的新兴科技巨头的出现,在一定程度上加速了这种变化,并以前所未有的规模改变了格局。市场主导地位日益增长的“FAANG”(脸书、苹果、亚马逊、奈飞和谷歌——五家科技巨头经常“同框”出现被统称为FAANG),外加一个复兴的微软,正在引领这种颠覆。

FAANGs don’t buy their technologies from original equipment manufacturers (OEMs) like HP, Dell, Cisco, or IBM. Instead they source technologies or components from original device manufacturers (ODMs), write their own code and build their own solutions. This diminishes the addressable market for OEMs. To add a further challenge, these companies are making their source code available in opensource communities, such as the Open Networking Foundation and the Open Compute Project, allowing those enterprises that have the resources and funding to follow suit, reducing the total addressable market for OEMs even further. Now add new consumption patterns, such as IaaS and SaaS offered at scale, and the addressable market reduces even further.

五大科技巨头不从像惠普、戴尔、思科或IBM这样的原始委托生产制造商(OEM,Original Entrusted Manufacture )购买技术,相反,他们从原始设计制造商(ODM,Original Design Manufacturer)那里获得技术或组件,编写自己的代码并构建自己的解决方案。这削弱了原始委托生产制造商的潜在市场。为了进一步强化挑战,这些公司还在开放网络基金会和开放计算项目等开放源代码社区中提供源代码,从而允许那些拥有资源和资金的企业效仿,进一步减少原始委托生产制造商的总目标市场。现在,如果再添加上像规模化的IaaS和SaaS这样的新的消费模式,其总目标市场将进一步减少。

FAANGs are also simply out-innovating the more established players. Google and Microsoft are embedding advanced innovation into all their products and services, at no additional charge, making it increasingly hard for narrowly-focused technology companies to compete. Applications are enriched with analytics, machine learning, AI, and the application stack itself, to provide additional value, depending on the use case. A good example is the collaboration stack: companies such as Microsoft and Google provide all the collaboration applications, but include additional functionality such as natural speech recognition, speech-to-text, digital recording, streaming, and fully-programmable interfaces to extend the value chain. This is provided in a consumption-based model – at a fraction of the cost of the more traditional approach, making it tough to match.

五大科技巨头的创新度也远远超过了那些更成熟的参与者。谷歌和微软正将先进的创新成果植入其所有的产品和服务中且不收取任何额外费用,这使得专注于特定领域的科技公司越来越难以与之竞争。应用程序通过分析、机器学习、AI和应用程序堆栈使自身得以丰富,并进一步根据使用案例提供了额外的价值。协作栈就是一个很好的例子:像微软和谷歌这样的公司除了提供所有的协作应用程序,还包括了一些额外的功能,例如自然语音识别、语音转文本、数字录音、流媒体和完全可编程的接口,以扩展其价值链。这些都是基于消费模型而提供的,且成本较传统技术只算得上凤毛麟角,因此其他科技公司很难与他们较量。

The rise of the FAANGs will cause a shake down of the OEMs

五大巨头的崛起将对原始委托生产制造商造成威胁

The effect of all this on OEMs will be significant, and in some market areas OEMs are already competing for roughly 40% of the total addressable market. As time goes on we’ll have a lot of big fish competing in a smaller and smaller pond – and I foresee that the big fish will start eating the small fish… I believe that the vendor landscape is going to undergo a metamorphosis over the next 3-5 years and those that emerge, will look very different.

五大巨头的崛起对原始设备制造商产生的影响将是显著的,在相关市场领域,原始设备制造商已经在争夺大约40%的潜在市场。随着时间的推移,我们会看到许多“大鱼”在一个越来越小的“池塘”里竞争——而且我断言“大鱼”会开始吃“小鱼”………我相信在未来的3 - 5年中,整个供应商行业将经历一次蜕变——而蜕变之后,整个行业将焕然一新。

文章精简图文如下:

免责声明: 除非特别声明,文章均为网络转载,仅代表作者观点,与大数据中国网无关。其原创性以及文中陈述文字和内容未经本站证实,对本文以及其中全部或者部分内容、文字的真实性、完整性、及时性本站不作任何保证或承诺,请读者仅作参考,并请自行核实相关内容。如果本文内容有侵犯你的权益,请发送信息至ab12-120@163.com,我们会及时删除
关闭

站长推荐上一条 /1 下一条

 
 
在线客服①
在线客服②
大数据行业交流
大数据行业交流
大数据求职招聘
大数据求职招聘
服务电话:
15010106923
微信联系:
hb-0310
服务邮箱:
ab12-120@163.com
官方微信扫一扫
大数据中国微信

QQ   
冀ICP备14005070号

版权所有: Discuz! © 2001-2013 大数据.

GMT+8, 2019-3-20 16:55 , Processed in 0.029438 second(s), 21 queries .

返回顶部