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    2020年十大科技趋向展望
    公布>###53:21   泉源:本站原创   点击量:
    Trend No 1. Hyperautomation
    Automation uses technology to automate tasks that once required humans.
    Hyperautomation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyperautomation extends across a range of tools that can be automated, but also refers to the sophistication of the automation (i.e., discover, analyze, design, automate, measure, monitor, reassess.)
    Hyperautomation often results in the creation of a digital twin of the organization
    As no single tool can replace humans, hyperautomation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making. 
    Although not the main goal, hyperautomation often results in the creation of a  of the organization (DTO), allowing organizations to visualize how functions, processes and key performance indicators interact to drive value. The DTO then becomes an integral part of the hyperautomation process, providing real-time, continuous intelligence about the organization and driving significant business opportunities. 
    趋向1、超主动化
    主动化利用技能使已经必要人的义务主动化。
    超主动化触及到******技能的使用,包罗人工智能(AI)和呆板学习(ML),以越来越主动化的历程和增长人类。超主动化扩展了一系列可以主动化的东西,但也指主动化的庞大性(即发明、剖析、设计、主动化、丈量、监控、重新评价)
    由于没有一种东西可以代替人类,现在的超主动化触及多种东西的组合,包罗呆板人流程主动化(RPA)、智能商业办理软件(iBPMS)和人工智能,其目的是越来越多的人工智能驱动决议计划。
    只管超主动化不是次要目的,但它通常会招致构造的数字孪生兄弟(DTO)的创立,使构造可以可视化功效、流程和要害功能目标怎样互相作用以驱动代价。然后,DTO成为超主动化历程的一个构成局部,提供有关构造的及时、继续的谍报,并推进严重的贸易时机。
    Trend No. 2: Multiexperience
    Multiexperience replaces technology-literate people with people-literate technology. In this trend, the traditional idea of a computer evolves from a single point of interaction to include multisensory and multitouchpoint interfaces like wearables and advanced computer sensors. 
    For example, Domino’s Pizza created an experience beyond app-based ordering that includes autonomous vehicles, a pizza tracker and smart speaker communications. 
    In the future, this trend will become what’s called an ambient experience, but currently multiexperience focuses on immersive experiences that use augmented reality (AR), virtual (VR), mixed reality, multichannel human-machine interfaces and sensing technologies. The combination of these technologies can be used for a simple AR overlay or a fully immersive VR experience. 
     
    趋向2:多重体验
    多重体验用人们熟习的技能代替了懂技能的人。在这种趋向下,传统的盘算机观点从单一的交互点开展到包罗多传感器和多点接口,如可穿着设置装备摆设和******的盘算机传感器。
    比方,Domino的Pizza发明了一种逾越基于使用步伐的订购的体验,包罗自主车辆、Pizza跟踪器和智能扬声器通讯。
    在将来,这种趋向将成为所谓的情况体验,但现在的多体验偏重于利用加强实际(AR)、假造(VR)、混淆实际、多通道人机界面和传感技能的沉溺式体验。这些技能的联合可以用于一个复杂的AR掩盖或一个******沉溺式的假造实际体验。
     
    Trend No. 3: Democratization
    Democratization of technology means providing people with easy access to technical or business expertise without extensive (and costly) training. It focuses on four key areas — application development, data and analytics, design and knowledge — and is often referred to as “citizen access,” which has led to the rise of citizen data scientists, citizen programmers and more. 
    For example, democratization would enable developers to generate data models without having the skills of a data scientist. They would instead rely on AI-driven development to generate code and automate testing. 
    趋向三:遍及化
    技能的遍及化意味着为人们提供容易取得技能或贸易专业知识的时机,而无需举行普遍(且昂贵)的培训。它专注于四个要害范畴——使用步伐开辟、数据和剖析、设计和知识——通常被称为“百姓拜访”,这招致了百姓数据迷信家、百姓步伐员等的崛起。
    比方,遍及化可以使开辟职员在不具有数据迷信家技艺的状况下天生数据模子。相反,他们将依赖人工智能驱动的开辟来天生代码和主动化测试。
     
    Trend No. 4: Human augmentation
    Human augmentation is the use of technology to enhance a person’s cognitive and physical experiences.
    Physical augmentation changes an inherent physical capability by implanting or hosting a technology within or on the body. For example, the automotive or mining industries use wearables to improve worker safety. In other industries, such as retail and travel, wearables are used to increase worker productivity. 
    Physical augmentation falls into four main categories: Sensory augmentation (hearing, vision, perception), appendage and biological function augmentation (exoskeletons, prosthetics), brain augmentation (implants to treat seizures) and genetic augmentation (somatic gene and cell therapy). 
    Cognitive augmentation enhances a human’s ability to think and make better decisions, for example, exploiting information and applications to enhance learning or new experiences. Cognitive augmentation also includes some technology in the brain augmentation category as they are physical implants that deal with cognitive reasoning. 
    Human augmentation carries a range of cultural and ethical implications. For example, using CRISPR technologies to augment genes has significant ethical implications. 
    趋向4:人体加强
    人类加强是使用技能来加强一团体的认知和身材体验。
    物理加强经过在身材内或身材上植入或托管技能来改动固有的物理才能。比方,汽车或采矿业利用可穿着设置装备摆设来进步工人的宁静。在其他行业,如批发业和旅游业,可穿着设置装备摆设被用来进步工人的消费力。
    物理加强分为四大类:觉得加强(听觉、视觉、知觉)、隶属物和生物功效加强(外骨骼、假肢)、大脑加强(医治癫痫的植入物)和基因加强(体细胞基因和细胞医治)。
    认知加强进步了人类思索和作出更好决议的才能,比方,使用信息和使用步伐来加强学习或新体验。认知加强还包罗大脑加强类的一些技能,由于它们是处置认知推理的物理植入物。
    人类的增加具有一系列的文明和伦理寄义。比方,利用CRISPR技能扩增基因具有严重的伦理意义。
     
    Trend No. 5: Transparency and traceability
    The evolution of technology is creating a trust crisis. As consumers become more aware of how  is being collected and used, organizations are also recognizing the increasing liability of storing and gathering the data. 
    Additionally, AI and ML are increasingly used to make decisions in place of humans, evolving the trust crisis and driving the need for ideas like explainable AI and AI governance. 
    This trend requires a focus on six key elements of trust: Ethics, integrity, openness, accountability, competence and consistency. 
    Legislation, like the European Union’s General Data Protection Regulation (GDPR), is being enacted around the world, driving evolution and laying the ground rules for organizations. 
    趋向5:通明与追溯性
    科技的开展正在制造一场信托危急。随着消耗者越来越认识到他们的数据是怎样被搜集和利用的,构造也了解到存储和搜集数据的责任越来越大。
    别的,人工智能和人工智能越来越多地被用来取代人类做出决议计划,演化出信托危急,并推进对可表明人工智能和人工智能管理等想法的需求。
    这一趋向要求把******放在信托的六个要害要素上:品德、端正、开放、问责、才能和分歧性。
    立法,像欧盟的一样平常数据掩护条例(GDPR),正活着界各地公布,推进演化,并为构造订定根本规矩。
     
    Trend No. 6: The empowered edge
     is a topology where information processing and content collection and delivery are placed closer to the sources of the information, with the idea that keeping traffic local and distributed will reduce latency. This includes all the technology on the (IoT). Empowered edge looks at how these devices are increasing and forming the foundations for smart spaces, and moves key applications and services closer to the people and devices that use them.
    By 2023, there could be more than 20 times as many smart devices at the edge of the network as in conventional IT roles. 
    趋向6:边沿盘算
    边沿盘算是一种将信息处置、内容搜集和通报放在接近信息源的地位的拓扑布局,其头脑是坚持通讯量的当地和散布式将增加耽误。这包罗物联网(IoT)上的一切技能。受权边沿着眼于这些设置装备摆设是怎样增长和构成智能空间的底子,并将要害使用步伐和办事更靠近利用的人和设置装备摆设。
    到2023年,网络边沿的智能设置装备摆设数目大概是传统IT脚色的20多倍。
     
    Trend No. 7: The distributed cloud
    Distributed cloud refers to the distribution of public cloud services to locations outside the cloud provider’s physical , but which are still controlled by the provider. In distributed cloud, the cloud provider is responsible for all aspects of cloud service architecture, delivery, operations, governance and updates. The evolution from centralized public cloud to distributed public cloud ushers in a new era of . 
    Distributed cloud allows data centers to be located anywhere. This solves both technical issues like latency and also regulatory challenges like data sovereignty. It also offers the benefits of a public cloud service alongside the benefits of a private, local cloud. 
    趋向7:散布式云
    散布式云是指将大众云办事分发到云提供商物理数据中心以外的地位,但这些地位仍由提供商控制。在散布式云中,云提供商卖力云办事架构、交付、操纵、管理和更新的一切方面。从会合式大众云到散布式大众云的演进,开启了云盘算的新期间。
    散布式云容许数据中心位于任何地方。这既办理了耽误等技能题目,也办理了数据主权等羁系应战。它还提供了大众云办事的利益以及公有当地云的利益。
     
    Trend No. 8: Autonomous things
    Autonomous things, which include drones, , ships and appliances,  to perform tasks usually done by humans. This technology operates on a spectrum of intelligence ranging from semiautonomous to fully autonomous and across a variety of environments including air, sea and land.
    While currently autonomous things mainly exist in controlled environments, like in a mine or warehouse, they will eventually evolve to include open public spaces. Autonomous things will also move from stand-alone to collaborative swarms, such as the drone swarms used during the Winter Olympic Games in 2018.
    However, autonomous things cannot replace the human brain and operate most effectively with a narrowly defined, well-scoped purpose. 
     
    趋向8:主动化
    自主的工具,包罗无人机、呆板人、船只和设置装备摆设,使用人工智能实行通常由人类完成的义务。这项技能的智能范畴从半自主到******自主,超过包罗氛围、陆地和海洋在内的种种情况。
    固然现在自治的事物次要存在于受控的情况中,比方在矿山或堆栈中,但它们***终将演化为开放的大众空间。自主的工具也将从独立的蜂群转向协作的蜂群,好比2018年冬奥会时期利用的无人机蜂群。
    但是,自主的事物不克不及代替人脑,也不克不及以广义的、范畴明白的目标***无效地运作。
    Trend No. 9: Practical blockchain
    is a type of distributed ledger, an expanding chronologically ordered list of cryptographically signed, irrevocable transactional records shared by all participants in a network. 
    Blockchain also allows parties to trace assets back to their origin, which is beneficial for traditional assets, but also paves the way for other uses such as tracing food-borne illnesses back to the original supplier. It also allows two or more parties who don’t know each other to safely interact in a digital environment and exchange value without the need for a centralized authority. 
    The complete blockchain model includes five elements: A shared and distributed ledger, immutable and traceable ledger, encryption, tokenization and a distributed public consensus mechanism. However, blockchain remains immature for enterprise deployments due to a range of technical issues including poor scalability and interoperability.
    Enterprise blockchains today take a practical approach and implement only some of the elements of a complete blockchain by making the ledger independent of individual applications and participants and replicating the ledger across a distributed network to create an authoritative record of significant events. Everyone with permissioned access sees the same information, and integration is simplified by having a single shared blockchain. Consensus is handled through more traditional private models.
    In the future, true blockchain or “blockchain complete” will have the potential to transform industries, and eventually the economy, as complementary technologies such as AI and the IoT begin to integrate alongside blockchain. This expands the type of participants to include machines, which will be able to exchange a variety of assets — from money to real estate. For example, a car would be able to negotiate insurance prices directly with the insurance company based on data gathered by its sensors. 
    趋向9:适用区块链
    区块链是一种散布式账本,是一种定时间次序扩展的列表,由网络中一切到场者共享的加密署名、不行打消的买卖记载。
    区块链还容许各方追溯资产的泉源,这对传统资产是无益的,但也为其他用处摊平了路途,如追溯餐饮传达疾病的原始供给商。它还容许不了解对方的两个或多个当事方在数字情况中宁静地交互并互换代价,而不必要会合的******机构。
    区块链还容许各方追溯资产的泉源,这对传统资产是无益的,但也为其他用处摊平了路途,如追溯餐饮传达疾病的原始供给商。它还容许不了解对方的两个或多个当事方在数字情况中宁静地交互并互换代价,而不必要会合的******机构。完备的区块链模子包罗五个要素:共享和散布式账本、不行变和可追踪账本、加密、标志化和散布式大众共鸣机制。但是,由于一系列技能题目,包罗可扩展性和互操纵性差,区块链关于企业摆设来说仍旧不可熟。
    明天的企业区块链接纳了一种适用的办法,经过使分类账独立于单个使用步伐和到场者,并经过散布式网络复制分类账,以创立严重事情的******记载,从而只完成完备区块链的某些元素。每个拥有允许拜访权限的人都能看到相反的信息,而经过拥有一个共享的区块链,集成变得复杂。共鸣是经过更传统的公家形式来处置的
    将来,随着人工智能和物联网等互补技能开端与区块链不相上下[bú xiàng shàng xià],真正的区块链或“区块链完成”将有潜力改动财产,***终改动经济。这扩展了到场者的范例,包罗呆板,它将可以互换种种资产-从钱币到房地产。比方,一辆汽车可以依据传感器搜集的数据间接与保险公司协商保险******。
    Trend No. 10: AI security 
    Evolving technologies such as hyperautomation and autonomous things offer transformational opportunities in the business world. However, they also create  in new potential points of attack. Security teams must address these challenges and be aware of how AI will impact the security space. 
    AI security has three key perspectives:
    1. Protecting AI-powered systems: Securing AI training data, training pipelines and ML models. 
    2. Leveraging AI to enhance security defense: Using ML to understand patterns, uncover attacks and automate parts of the cybersecurity processes. 
    3. Anticipating nefarious use of AI by attackers: Identifying attacks and defending against them. 
     
    趋向10:人工智能宁静
    不停开展的技能,如超主动化和自主的工具提供了贸易天下的厘革时机。但是,它们也会在新的潜伏打击点上形成宁静毛病。宁静团队必需应对这些应战,并认识到人工智能将怎样影响宁静空间。
     
    人工智能宁静有三个要害方面:
    1.掩护人工智能体系:掩护人工智能培训数据、培训管道和ML模子。
    2.使用人工智能加强宁静进攻:利用ML理解形式、发明打击并主动化局部网络宁静历程。
    3.预期打击者歹意利用人工智能:辨认打击并进攻打击。
     
    援用至美國資訊科技研讨與顧問公司Gartner,發佈《2020十大科技趨勢報告》