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    2020年十大科技趨勢預測
    發布時間:2020-01-03 13:53:21   來源:本站原創   點擊量:
    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. 
    趨勢1、超自動化
    自動化使用技術使曾經需要人的任務自動化。
    超自動化涉及到先進技術的應用,包括人工智能(AI)和機器學習(ML),以越來越自動化的過程和增加人類。超自動化擴展了一系列可以自動化的工具,但也指自動化的復雜性(即發現、分析、設計、自動化、測量、監控、重新評估)
    由于沒有一種工具可以取代人類,如今的超自動化涉及多種工具的組合,包括機器人流程自動化(RPA)、智能業務管理軟件(iBPMS)和人工智能,其目標是越來越多的人工智能驅動決策。
    盡管超自動化不是主要目標,但它通常會導致組織的數字孿生兄弟(DTO)的創建,使組織能夠可視化功能、流程和關鍵性能指標如何相互作用以驅動價值。然后,DTO成為超自動化過程的一個組成部分,提供有關組織的實時、持續的情報,并推動重大的商業機會。
    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. 
     
    趨勢2:多重體驗
    多重體驗用人們熟悉的技術取代了懂技術的人。在這種趨勢下,傳統的計算機概念從單一的交互點發展到包括多傳感器和多點接口,如可穿戴設備和先進的計算機傳感器。
    例如,Domino的Pizza創造了一種超越基于應用程序的訂購的體驗,包括自主車輛、Pizza跟蹤器和智能揚聲器通信。
    在未來,這種趨勢將成為所謂的環境體驗,但目前的多體驗側重于使用增強現實(AR)、虛擬(VR)、混合現實、多通道人機界面和傳感技術的沉浸式體驗。這些技術的結合可以用于一個簡單的AR覆蓋或一個完全沉浸式的虛擬現實體驗。
     
    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. 
    趨勢三:普及化
    技術的普及化意味著為人們提供容易獲得技術或商業專業知識的機會,而無需進行廣泛(且昂貴)的培訓。它專注于四個關鍵領域——應用程序開發、數據和分析、設計和知識——通常被稱為“公民訪問”,這導致了公民數據科學家、公民程序員等的崛起。
    例如,普及化可以使開發人員在不具備數據科學家技能的情況下生成數據模型。相反,他們將依賴人工智能驅動的開發來生成代碼和自動化測試。
     
    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. 
    趨勢4:人體增強
    人類增強是利用技術來增強一個人的認知和身體體驗。
    物理增強通過在身體內或身體上植入或托管技術來改變固有的物理能力。例如,汽車或采礦業使用可穿戴設備來提高工人的安全。在其他行業,如零售業和旅游業,可穿戴設備被用來提高工人的生產力。
    物理增強分為四大類:感覺增強(聽覺、視覺、知覺)、附屬物和生物功能增強(外骨骼、假肢)、大腦增強(治療癲癇的植入物)和基因增強(體細胞基因和細胞治療)。
    認知增強提高了人類思考和作出更好決定的能力,例如,利用信息和應用程序來增強學習或新體驗。認知增強還包括大腦增強類的一些技術,因為它們是處理認知推理的物理植入物。
    人類的增長具有一系列的文化和倫理含義。例如,使用CRISPR技術擴增基因具有重大的倫理意義。
     
    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. 
    趨勢5:透明與追溯性
    科技的發展正在制造一場信任危機。隨著消費者越來越意識到他們的數據是如何被收集和使用的,組織也認識到存儲和收集數據的責任越來越大。
    此外,人工智能和人工智能越來越多地被用來代替人類做出決策,演變出信任危機,并推動對可解釋人工智能和人工智能治理等想法的需求。
    這一趨勢要求把重點放在信任的六個關鍵要素上:道德、正直、開放、問責、能力和一致性。
    立法,像歐盟的一般數據保護條例(GDPR),正在世界各地頒布,推動演變,并為組織制定基本規則。
     
    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. 
    趨勢6:邊緣計算
    邊緣計算是一種將信息處理、內容收集和傳遞放在靠近信息源的位置的拓撲結構,其思想是保持通信量的本地和分布式將減少延遲。這包括物聯網(IoT)上的所有技術。授權邊緣著眼于這些設備是如何增加和形成智能空間的基礎,并將關鍵應用程序和服務更接近使用的人和設備。
    到2023年,網絡邊緣的智能設備數量可能是傳統IT角色的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. 
    趨勢7:分布式云
    分布式云是指將公共云服務分發到云提供商物理數據中心以外的位置,但這些位置仍由提供商控制。在分布式云中,云提供商負責云服務架構、交付、操作、治理和更新的所有方面。從集中式公共云到分布式公共云的演進,開啟了云計算的新時代。
    分布式云允許數據中心位于任何地方。這既解決了延遲等技術問題,也解決了數據主權等監管挑戰。它還提供了公共云服務的好處以及私有本地云的好處。
     
    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. 
     
    趨勢8:自動化
    自主的東西,包括無人機、機器人、船只和設備,利用人工智能執行通常由人類完成的任務。這項技術的智能范圍從半自主到完全自主,跨越包括空氣、海洋和陸地在內的各種環境。
    雖然目前自治的事物主要存在于受控的環境中,例如在礦山或倉庫中,但它們***終將演化為開放的公共空間。自主的東西也將從獨立的蜂群轉向協作的蜂群,比如2018年冬奧會期間使用的無人機蜂群。
    然而,自主的事物不能取代人腦,也不能以狹義的、范圍明確的目的***有效地運作。
    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. 
    趨勢9:實用區塊鏈
    區塊鏈是一種分布式賬本,是一種按時間順序擴展的列表,由網絡中所有參與者共享的加密簽名、不可撤銷的交易記錄。
    區塊鏈還允許各方追溯資產的來源,這對傳統資產是有益的,但也為其他用途鋪平了道路,如追溯食品傳播疾病的原始供應商。它還允許不認識對方的兩個或多個當事方在數字環境中安全地交互并交換價值,而不需要集中的權威機構。
    區塊鏈還允許各方追溯資產的來源,這對傳統資產是有益的,但也為其他用途鋪平了道路,如追溯食品傳播疾病的原始供應商。它還允許不認識對方的兩個或多個當事方在數字環境中安全地交互并交換價值,而不需要集中的權威機構。完整的區塊鏈模型包括五個要素:共享和分布式賬本、不可變和可追蹤賬本、加密、標記化和分布式公眾共識機制。然而,由于一系列技術問題,包括可擴展性和互操作性差,區塊鏈對于企業部署來說仍然不成熟。
    今天的企業區塊鏈采取了一種實用的方法,通過使分類賬獨立于單個應用程序和參與者,并通過分布式網絡復制分類賬,以創建重大事件的權威記錄,從而只實現完整區塊鏈的某些元素。每個擁有許可訪問權限的人都能看到相同的信息,而通過擁有一個共享的區塊鏈,集成變得簡單。共識是通過更傳統的私人模式來處理的
    未來,隨著人工智能和物聯網等互補技術開始與區塊鏈并駕齊驅,真正的區塊鏈或“區塊鏈完成”將有潛力改變產業,***終改變經濟。這擴大了參與者的類型,包括機器,它將能夠交換各種資產-從貨幣到房地產。例如,一輛汽車可以根據傳感器收集的數據直接與保險公司協商保險價格。
    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. 
     
    趨勢10:人工智能安全
    不斷發展的技術,如超自動化和自主的東西提供了商業世界的變革機會。然而,它們也會在新的潛在攻擊點上造成安全漏洞。安全團隊必須應對這些挑戰,并意識到人工智能將如何影響安全空間。
     
    人工智能安全有三個關鍵方面:
    1.保護人工智能系統:保護人工智能培訓數據、培訓管道和ML模型。
    2.利用人工智能增強安全防御:使用ML了解模式、發現攻擊并自動化部分網絡安全過程。
    3.預期攻擊者惡意使用人工智能:識別攻擊并防御攻擊。
     
    引用至美國資訊科技研究與顧問公司Gartner,發佈《2020十大科技趨勢報告》

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