\n
Gartner predicts that by 2022, 80 percent of smartphones<\/a> shipped will have on-device AI capabilities, up from 10 percent in 2017. On-device AI is currently limited to premium devices<\/a> and provides better data protection and power management than full cloud-based AI, since data is processed and stored locally.
\n
\n10 Uses for AI-Powered Smartphones<\/strong>
\n
\nGartner has identified 10 high-impact uses for AI-powered smartphones to enable vendors to provide more value to their customers.
\n
\n1) \"Digital Me\" Sitting on the Device<\/strong>
\n
\nSmartphones will be an extension of the user, capable of recognizing them and predicting their next move. They will understand who you are, what you want, when you want it, how you want it done and execute tasks upon your authority.
\n
\n2) User Authentication<\/strong>
\n
Password-based, simple authentication is becoming too complex and less effective, resulting in weak security<\/a>, poor user experience, and a high cost of ownership. Security technology combined with machine learning, biometrics and user behavior will improve usability and self-service capabilities. For example, smartphones can capture and learn a user's behavior, such as patterns when they walk, swipe, apply pressure to the phone, scroll and type, without the need for passwords or active authentications.
\n
\n3) Emotion Recognition<\/strong>
\n
\nEmotion sensing systems and affective computing allow smartphones to detect, analyze, process and respond to people's emotional states and moods. The proliferation of virtual personal assistants and other AI-based technology for conversational systems is driving the need to add emotional intelligence for better context and an enhanced service experience. Car manufacturers, for example, can use a smartphone's front camera to understand a driver's physical condition or gauge fatigue levels to increase safety.
\n
\n4) Natural-Language Understanding<\/strong>
\n
Continuous training and deep learning<\/a> on smartphones will improve the accuracy of speech recognition, while better understanding the user's specific intentions. For instance, when a user says \"the weather is cold,\" depending on the context, his or her real intention could be \"please order a jacket online\" or \"please turn up the heat.\" As an example, natural-language understanding could be used as a near real-time voice translator on smartphones when traveling abroad.
\n
\n5) Augmented Reality (AR<\/a>) and AI Vision<\/strong>
\n
\nWith the release of iOS 11, Apple included an ARKit feature that provides new tools to developers to make adding AR to apps easier. Similarly, Google announced its ARCore AR developer tool for Android and plans to enable AR on about 100 million Android devices by the end of next year. Google expects almost every new Android phone will be AR-ready out of the box next year. One example of how AR can be used is in apps that help to collect user data and detect illnesses such as skin cancer or pancreatic cancer.
\n
\n6) Device Management<\/strong>
\n
\nMachine learning will improve device performance and standby time. For example, with many sensors, smartphones can better understand and learn user's behavior, such as when to use which app. The smartphone will be able to keep frequently used apps running in the background for quick re-launch, or to shut down unused apps to save memory and battery.
\n
\n7) Personal Profiling<\/strong>
\n
\nSmartphones are able to collect data for behavioral and personal profiling. Users can receive protection and assistance dynamically, depending on the activity that is being carried out and the environments they are in (e.g., home, vehicle, office, or leisure activities). Service providers such as insurance companies can now focus on users, rather than the assets. For example, they will be able to adjust the car insurance rate based on driving behavior.
\n
\n8) Content Censorship\/Detection<\/strong>
\n
\nRestricted content can be automatically detected. Objectionable images, videos or text can be flagged and various notification alarms can be enabled. Computer recognition software can detect any content that violates any laws or policies. For example, taking photos in high security facilities or storing highly classified data on company-paid smartphones will notify IT.
\n
\n9) Personal Photographing<\/strong>
\n
\nPersonal photographing includes smartphones that are able to automatically produce beautified photos based on a user's individual aesthetic preferences. For example, there are different aesthetic preferences between the East and West — most Chinese people prefer a pale complexion, whereas consumers in the West tend to prefer tan skin tones.
\n
\n10) Audio Analytic<\/strong>
\n
\nThe smartphone's microphone is able to continuously listen to real-world sounds. AI capability on device is able to tell those sounds, and instruct users or trigger events. For example, a smartphone hears a user snoring, then triggers the user's wristband to encourage a change in sleeping positions.\n\n<\/body>","next_sibling":[{"msid":62375909,"title":"Lowe Lintas bags creative mandate For Xiaomi","entity_type":"ARTICLE","link":"\/news\/lowe-lintas-bags-creative-mandate-for-xiaomi\/62375909","category_name":null,"category_name_seo":"telecomnews"}],"related_content":[],"msid":62376012,"entity_type":"ARTICLE","title":"80 pct of smartphones shipped in 2022 will have on-device AI capabilities: Gartner","synopsis":"On-device AI is currently limited to premium devices and provides better data protection and power management than full cloud-based AI, since data is processed and stored locally.","titleseo":"telecomnews\/80-pct-of-smartphones-shipped-in-2022-will-have-on-device-ai-capabilities-gartner","status":"ACTIVE","authors":[],"Alttitle":{"minfo":""},"artag":"ETCIO","artdate":"2018-01-05 09:30:23","lastupd":"2018-01-05 09:32:10","breadcrumbTags":["AI","Deep Learning","AR","security","Devices","Smartphones","Gartner","artificial intelligence"],"secinfo":{"seolocation":"telecomnews\/80-pct-of-smartphones-shipped-in-2022-will-have-on-device-ai-capabilities-gartner"}}" data-authors="[" "]" data-category-name="" data-category_id="" data-date="2018-01-05" data-index="article_1">
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80 2022年智能手机出货量将设备内置AI功能:Gartner
设备内置AI目前限于高端设备和提供更好的数据保护和比完整的基于云计算的智能电源管理,数据处理和存储在本地。
班加罗尔:人工智能(人工智能)功能将成为智能手机厂商的关键产品的区别,帮助他们获得新客户,同时保留当前用户,根据Gartner。随着智能手机市场的销售,技术产品提供令人信服的和个性化的体验,人工智能解决方案运行在智能手机将成为必不可少的一部分供应商路线图在未来两年。
Gartner预测,到2022年,80%的智能手机运会AI设备内置功能,从2017年的10%。设备内置AI目前限于溢价设备并提供更好的数据保护和比完整的基于云计算的智能电源管理,数据处理和存储在本地。
10用途AI-Powered智能手机
Gartner确定了10个高影响力用途AI-powered智能手机使供应商能够为顾客提供更多的价值。
1)“数字”我坐在设备
智能手机将是一个扩展的用户,能够识别和预测他们的下一步行动。他们会了解你是谁,你想要什么,当你想它时,你想怎么做你的权威和执行任务。
2)用户身份验证
基于密码、简单身份验证是变得过于复杂和不那么有效,导致弱安全、用户体验差和高成本的所有权。安全技术与机器学习相结合,生物识别技术将提高可用性和用户行为和自助服务功能。例如,智能手机可以捕获和了解用户的行为,如模式行走时,刷卡,施加压力来了电话,滚动和类型,而不需要密码或活跃的认证。
3)情感识别
情感传感系统和情感计算允许智能手机探测、分析、处理和应对人们的情绪和心情。虚拟个人助理和其他基于ai技术的扩散为会话系统驱动的需要添加情商更好的背景和一个增强的服务体验。例如,汽车制造商可以使用智能手机的前置摄像头理解司机的身体状况或衡量疲劳提高安全水平。
4)自然语言理解
持续的培训和深度学习智能手机将提高语音识别的准确性,同时更好的理解用户的特定的意图。例如,当一个用户说,“天气很冷,”根据上下文,他或她的真实意图可能是“请在网上订购一件夹克”或“请把热量。”As an example, natural-language understanding could be used as a near real-time voice translator on smartphones when traveling abroad.
5)增强现实(基于“增大化现实”技术)和人工智能视觉
苹果发布的iOS 11日包括ARKit特性提供了新的工具,开发人员简化添加基于“增大化现实”技术的应用。同样,Google宣布桃色AR Android开发工具,并计划约1亿Android设备上启用基于“增大化现实”技术明年年底。谷歌预计几乎每一个新的Android手机将AR-ready明年开箱即用的。如何使用基于“增大化现实”技术的一个例子是应用程序帮助收集用户数据和检测疾病如皮肤癌或胰腺癌。
6)设备管理
机器学习将提高设备性能和待机时间。例如,许多传感器,智能手机可以更好地理解和学习用户行为,例如当使用应用。智能手机能够经常使用的应用程序在后台运行快速重新启动,或关闭未使用的应用程序来节省内存和电池。
7)个人分析
智能手机能够收集数据的行为和个人分析。用户可以动态地得到保护和援助,根据正在进行的活动和的环境(如家庭、汽车、办公室、或休闲活动)。服务提供者,如保险公司现在可以专注于用户,而不是资产。例如,他们将能够调整基于驾驶行为的汽车保险费率。
8)内容审查/检测
限制内容可以自动检测。令人反感的图片、视频或文本可以标记和各种通知警报可以启用。计算机识别软件可以发现任何违反任何法律或政策的内容。例如,拍照在高安全设施或高度机密数据存储公司智能手机会通知的。
9)个人拍摄
个人拍摄包括智能手机能够自动产生美化照片基于用户的个人审美偏好。例如,东部和西部之间有不同的审美喜好,大多数中国人喜欢一个苍白的肤色,而西方消费者倾向于喜欢晒黑肤色。
10)音频分析
智能手机的麦克风能够不断听真实的声音。AI功能设备能够告诉那些声音,并指导用户或触发事件。例如,一个智能手机听到用户打鼾,然后触发用户的腕带鼓励改变睡眠姿势。
Gartner预测,到2022年,80%的智能手机运会AI设备内置功能,从2017年的10%。设备内置AI目前限于溢价设备并提供更好的数据保护和比完整的基于云计算的智能电源管理,数据处理和存储在本地。
10用途AI-Powered智能手机
Gartner确定了10个高影响力用途AI-powered智能手机使供应商能够为顾客提供更多的价值。
1)“数字”我坐在设备
智能手机将是一个扩展的用户,能够识别和预测他们的下一步行动。他们会了解你是谁,你想要什么,当你想它时,你想怎么做你的权威和执行任务。
2)用户身份验证
基于密码、简单身份验证是变得过于复杂和不那么有效,导致弱安全、用户体验差和高成本的所有权。安全技术与机器学习相结合,生物识别技术将提高可用性和用户行为和自助服务功能。例如,智能手机可以捕获和了解用户的行为,如模式行走时,刷卡,施加压力来了电话,滚动和类型,而不需要密码或活跃的认证。
3)情感识别
情感传感系统和情感计算允许智能手机探测、分析、处理和应对人们的情绪和心情。虚拟个人助理和其他基于ai技术的扩散为会话系统驱动的需要添加情商更好的背景和一个增强的服务体验。例如,汽车制造商可以使用智能手机的前置摄像头理解司机的身体状况或衡量疲劳提高安全水平。
4)自然语言理解
持续的培训和深度学习智能手机将提高语音识别的准确性,同时更好的理解用户的特定的意图。例如,当一个用户说,“天气很冷,”根据上下文,他或她的真实意图可能是“请在网上订购一件夹克”或“请把热量。”As an example, natural-language understanding could be used as a near real-time voice translator on smartphones when traveling abroad.
5)增强现实(基于“增大化现实”技术)和人工智能视觉
苹果发布的iOS 11日包括ARKit特性提供了新的工具,开发人员简化添加基于“增大化现实”技术的应用。同样,Google宣布桃色AR Android开发工具,并计划约1亿Android设备上启用基于“增大化现实”技术明年年底。谷歌预计几乎每一个新的Android手机将AR-ready明年开箱即用的。如何使用基于“增大化现实”技术的一个例子是应用程序帮助收集用户数据和检测疾病如皮肤癌或胰腺癌。
6)设备管理
机器学习将提高设备性能和待机时间。例如,许多传感器,智能手机可以更好地理解和学习用户行为,例如当使用应用。智能手机能够经常使用的应用程序在后台运行快速重新启动,或关闭未使用的应用程序来节省内存和电池。
7)个人分析
智能手机能够收集数据的行为和个人分析。用户可以动态地得到保护和援助,根据正在进行的活动和的环境(如家庭、汽车、办公室、或休闲活动)。服务提供者,如保险公司现在可以专注于用户,而不是资产。例如,他们将能够调整基于驾驶行为的汽车保险费率。
8)内容审查/检测
限制内容可以自动检测。令人反感的图片、视频或文本可以标记和各种通知警报可以启用。计算机识别软件可以发现任何违反任何法律或政策的内容。例如,拍照在高安全设施或高度机密数据存储公司智能手机会通知的。
9)个人拍摄
个人拍摄包括智能手机能够自动产生美化照片基于用户的个人审美偏好。例如,东部和西部之间有不同的审美喜好,大多数中国人喜欢一个苍白的肤色,而西方消费者倾向于喜欢晒黑肤色。
10)音频分析
智能手机的麦克风能够不断听真实的声音。AI功能设备能够告诉那些声音,并指导用户或触发事件。例如,一个智能手机听到用户打鼾,然后触发用户的腕带鼓励改变睡眠姿势。
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