Context-aware information on always-on displays

Abstract

A computing device may determine a current location, obtain user-context, and generate location-specific insights by applying an artificial intelligence model to the current location and user-context associated with the computing device. For instance, the computing device may, while operating in a locked mode, output a graphical indication of a location-specific insight to an always-on-display device and detect a user input at a location of the always-on-display device associated with the graphical indication. In response to detecting the user input, the computing device may execute an application associated with the at least one location-specific insight and output to a display device while operating in the unlocked mode, additional information to a graphical user interface of the application associated with the at least one location-specific insight.

Description

Docket No.: 1333-871WO01 CONTEXT-AWARE INFORMATION ON ALWAYS-ON DISPLAYS CLAIM OF PRIORITY

[0001] This application is a PCT with provisional priority to US Provisional Patent Application No.63 / 653,100, filed 29 May 2024, the entire contents of which is incorporated herein by reference. BACKGROUND

[0002] The widespread usage of mobile devices, such as smartphones, enables users’ access to information at any place and at any time. Such ready access to information may result in information overload due to the volume of data available, lessening the value of such information to users. When irrelevant information or too much information is provided to mobile device users, such users may ignore the information entirely. Potentially worse, users may consider the delivery of irrelevant or excessive information to be intrusive, thus degrading the overall user experience.

[0003] While technological solutions have been developed to tailor the relevance of data and control the volume of data, these solutions often rely on user interaction with the content that is presented in response to user input rather than being anticipatory, which limits the ability of the device to provide information that is both timely and contextually relevant. SUMMARY

[0004] In general, the techniques of this disclosure are directed to displaying context-aware information to the Always-On-Display (AOD) feature of a user’s computing device and connected peripherals, such as a smartwatch, glasses with a display interface, and other connected display components, including while the computing device is in a locked state. In some implementations, these connected display components may include wearable computing devices, such as smartwatches, smart glasses, or smart rings, which may include integrated display elements configured to present glanceable information when the device is locked or inactive. Artificial intelligence (AI) models analyze current location and contextual data, such as user activity, surrounding environment, and historical or crowd-sourced information. Based on this analysis, a computing device may generate and display various anticipatory insights directly to the AOD. These insights are consumable at a glance, with optional user interaction triggering a seamless transition to a more detailed application interface upon device unlock. Displaying such context-aware information on the AODDocket No.: 1333-871WO01 enables proactive delivery of relevant and actionable content without requiring constant user input, extending AI assistance beyond traditional on-screen interactions.

[0005] In one example, this disclosure describes a method that includes determining, by one or more processors of a computing device, a current location of the computing device. In such an example, the one or more processors may obtain user-context associated with the computing device and generate a plurality of location-specific insights while the computing device is operating in a locked mode by at least applying an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device. According to such an example, the computing device may output, by an always-on-display device while the computing device is operating in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location- specific insights. The computing device may detect, by the one or more processors, a user input at a location of the always-on-display device associated with the graphical indication. In response to detecting the user input, the computing device may output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of the application associated with the at least one location-specific insight.

[0006] In another example, this disclosure describes a computing device that includes a memory and one or more processors implemented in circuitry in communication with the memory. The one or more processors may be configured to determine a current location of the computing device. In such an example, the computing device may obtain user-context associated with the computing device and generate a plurality of location-specific insights while the computing device is operating in a locked mode by at least applying an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device. According to such an example, the computing device may output, by an always-on-display device while the computing device is operating in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights. The computing device may detect, by the one or more processors, a user input at a location of the always-on-display device associated with the graphical indication. In response to detecting the user input, the computing device may output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of the application associated with the at least one location-specific insight. For instance, the computing device may output the additional information to a connected display such as aDocket No.: 1333-871WO01 smartwatch, eyeglasses, a presence-sensitive display integrated with the computing device, or a remote display component communicably linked with the computing device.

[0007] In another example, this disclosure describes a non-transitory computer-readable storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to determine a current location of the computing device. In such an example, the instructions may cause the one or more processors to obtain user- context associated with the computing device and generate a plurality of location-specific insights while the computing device is operating in a locked mode by at least applying an artificial intelligence model to the current location of the computing device and the user- context associated with the computing device. According to such an example, the instructions may cause the one or more processors to output, by an always-on-display device while the computing device is operating in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights. The instructions may cause the one or more processors to detect a user input at a location of the always-on-display device associated with the graphical indication. In response to detecting the user input, the instructions may output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of the application associated with the at least one location-specific insight.

[0008] The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF DRAWINGS

[0009] FIG.1 is a process diagram illustrating an example always-on-display framework depicting AI-based insight generation and delivery to a locked device display, in accordance with one or more aspects of the present disclosure.

[0010] FIG.2 is a block diagram illustrating further details of an example computing device, in accordance with one or more aspects of the present disclosure.

[0011] FIGS.3A-3D are conceptual diagrams illustrating example graphical user interfaces, in accordance with aspects of this disclosure.

[0012] FIGS.4A-4D are conceptual diagrams illustrating example graphical user interfaces, in accordance with aspects of this disclosure.Docket No.: 1333-871WO01

[0013] FIG.5 is a conceptual diagram illustrating example graphical user interfaces, in accordance with aspects of this disclosure.

[0014] FIG.6 is a flowchart illustrating example operations performed by an example computing device that is configured in accordance with one or more aspects of the present disclosure. DETAILED DESCRIPTION

[0015] In general, the techniques of this disclosure are directed to displaying context-aware information to the Always-On-Display (AOD) feature of a user’s computing device and connected peripherals, such as a smartwatch, glasses with a display interface, and other connected display components, including while the computing device is in a locked state. In some implementations, these connected display components may include wearable computing devices, such as smartwatches, smart glasses, or smart rings, which may include integrated display elements configured to present glanceable information when the device is locked or inactive. Artificial intelligence (AI) models analyze current location and contextual data, such as user activity, surrounding environment, and historical or crowd-sourced information. Based on this analysis, a computing device may generate and display various anticipatory insights directly to the AOD. These insights are consumable at a glance, with optional user interaction triggering a seamless transition to a more detailed application interface upon device unlock. Displaying such context-aware information on the AOD enables proactive delivery of relevant and actionable content without requiring constant user input, extending AI assistance beyond traditional on-screen interactions.

[0016] FIG.1 is a process diagram illustrating an example always-on-display framework depicting AI-based insight generation and delivery to a locked device display, in accordance with one or more aspects of the present disclosure. More particularly, as shown in FIG.1, always-on-display framework 100 includes various interactions by computing device 102 (e.g., a mobile computing device) with artificial intelligence model 190 and various user interactions. Always-On-Display (AOD) is a feature available on modern mobile computing devices enabling the mobile device to output for display information such as time of day, date, weather information, user configurable notifications, missed calls, etc., while computing device 102 is inactive due to a lack of user interactions, while the mobile computing device is operating in a locked mode, or both. Always-on-display 105 of computing device 102 may provide a limited scope graphical user interface (GUI) for computing device 102 while concurrently restricting access to expanded functionality of applications and featuresDocket No.: 1333-871WO01 provided by the mobile computing device, until a user successfully completes an authentication challenge, such as by actions including entering a password or passcode, swiping a finger across the screen in a pre-defined authentication pattern, submitting biometric information responsive to a biometric challenge, and so forth.

[0017] As shown in FIG.1, computing device 102, using processing circuitry 199, obtains user-context data 114 (101). User-context data 114 may include, for example, historical user interaction data, behavioral patterns, calendar entries, or environmental signals such as time of day and location proximity indicators. User-context refers to dynamically collected data reflecting the user’s current situational state, including temporal information (e.g., date, time), geographic location, activity status (e.g., walking, driving), recent user interactions, historical behavior patterns, and device sensor readings, used to inform the generation of location-specific insights. Computing device 102 determines current location 115, resulting in location data 116 as depicted. Computing device 102 sends user-context data 114 and location data 116 to artificial intelligence model 190 (120) as AI model input data 121. In response, computing device 102 obtains location-specific insights 122 (125), generated by artificial intelligence model 190 based on the received AI model input data 121 analyzed by artificial intelligence model 190. Location-specific insights 122 may include predictive outputs relevant to the user’s current context and location, such as recommendations, navigational aids, or other contextually relevant content. Location-specific insight(s) refers to content generated by processing device-determined location data with user context to produce predictive or situationally relevant informational output concerning venues, routes, environmental factors, or events associated with the user’s current or proximate geographic location, beyond static location labels.

[0018] Computing device 102 uses locked state application 130 to manage the generation of graphical indication 131 based on location-specific insights 122. Graphical indication(s) refers to a visual element, including icons, text, symbols, or animations, rendered on an always-on display to convey the existence of a context-aware, location-specific insight, distinguishable from generic status information such as time or battery level. Computing device 102 outputs graphical indication 131 to always-on-display 105 using output component 135, as shown in FIG.1. Computing device 102 detects user interaction with graphical indication 131 (140), for example, by sensing a tap or other gesture on always-on- display 105. Computing device 102 determines whether computing device 102 remains in a locked state (145). If computing device 102 remains locked, computing device 102 may maintain or update graphical indication 131 on always-on-display 105. If the userDocket No.: 1333-871WO01 successfully authenticates (150), computing device 102 transitions to an unlocked state and launches expanded functionality application 155. Expanded functionality application 155 generates and outputs additional information 156, which may include detailed content, interactive elements, or extended features related to the previously displayed location-specific insights 122, completing the transition from glanceable insights to expanded user engagement.

[0019] Always-on-display 105 of computing device 102 may continue to output limited information even while computing device 102 is asleep. Depending on the configuration of always-on-display 105, computing device 102 may keep at least a portion of always-on- display 105 (e.g., a display screen) on at all times or may activate portions of always-on- display 105 on an as-needed basis to display notifications and to output graphical insights.

[0020] Computing device 102 may implement an artificial intelligence model 190 to generate context-aware information for output to always-on-display 105 providing location-specific insights. AI model 190 may include machine learning (ML) models, chatbots, generative pre- trained transformer (GPT) models such as Gemini, large language models (LLMs), natural language processing (NLP) models, computer vision models for object recognition and classification, graphics based search models, and image generation models for outputting computer generated visual information responsive to written prompts.

[0021] When computing device 102 interacts with AI model 190, computing device 102 may provide input to AI model 190 (e.g., send user-context 114 and determined location data 116 information) to AI model 190 installed locally and executing locally at computing device 102. In other examples, computing device 102 may send current location 116 information for computing device 102 and user-context 114 information associated with computing device 102 to artificial intelligence model 190 executing at a third-party cloud platform communicably interfaced with computing device 102 over a public Internet. In such a way, computing device 102 may utilize a locally installed AI model 190, a remote AI model 190, or both, as needed.

[0022] By combining the predictive capabilities of AI model 190 with the passive visibility of always-on-display 105, computing device 102 enables proactive delivery of timely, location-specific insights 122 to assist users in engaging with the physical world. Unlike traditional AI models that respond to user-initiated input, AI model 190 generates predictive output based on user-context 114 and location 116, presenting information that appears anticipatory from the user's perspective, even though computing device 102 operates based on data-driven predictions rather than human-like foresight or any true cognitive awareness.Docket No.: 1333-871WO01 Context-aware refers to the capability of a system to adjust information presentation based on dynamically determined user state, including but not limited to location, time, detected activity, environmental conditions, or historical interaction patterns, processed through algorithmic or machine learning methods rather than static rules alone. User-context 114 may include data such as prior search history, calendar entries, behavioral patterns, or environmental signals like time of day and proximity to map elements (e.g., restaurants or venues). These insights 122 are surfaced to always-on-display 105 without requiring the user to unlock computing device 102 or provide active input.

[0023] For example, computing device 102 may detect that the user is near a location of interest, such as a previously searched restaurant. Based on this situational context, the artificial intelligence model may generate location-specific insights such as walking directions, parking suggestions, or real-time wait time information. These insights are displayed directly on the always-on-display, allowing the user to view contextually relevant information without unlocking computing device 102 or opening an application. This proactive delivery of information helps the user engage with nearby physical environments more effectively, providing actionable suggestions at a glance.

[0024] In another scenario, computing device 102 may recognize that the user has arrived at a venue, such as a restaurant, store, or entertainment location. Based on this recognition, the artificial intelligence model may generate venue-specific insights, such as current wait times, available reservations, or personalized menu recommendations. These insights may appear on the always-on-display as graphical prompts, enabling the user to view helpful venue-specific information without unlocking computing device 102. If the user interacts with one of these prompts, computing device 102 may transition to an unlocked state and present expanded details, such as a full menu or booking interface, through an appropriate application.

[0025] In some implementations, graphical indication 131 may present a plurality of location-specific insights 122 simultaneously. For example, when computing device 102 determines that the user is near a recognized venue, AI model 190 may generate and output to always-on-display 105, a combination of insights 122, such as estimated wait times for seating, available reservation times, parking availability near the venue, and current weather conditions relevant to the user’s location. In another example, computing device 102 may surface multiple transit-related insights 122, including the nearest transit stop, estimated arrival times for multiple transportation services (e.g., bus, train, rideshare), and walking directions to the selected service. These plural insights 122 may be displayed as separate, glanceable elements within graphical indication 131 on always-on-display 105, providing theDocket No.: 1333-871WO01 user with multiple pieces of contextual information concurrently, without requiring the user to unlock computing device 102 or provide additional input. More particularly, locked state application 130 may generate graphical indication 131 based on location-specific insights 122 obtained from AI model 190. In this manner, locked state application 130 converts predictive output generated by AI model 190 into graphical content suitable for output on always-on- display 105. Display and interaction flow for the glanceable insights are managed by always- on-display framework 100 of computing device 102 while computing device 102 remains locked, as described below.

[0026] Continuing with the process illustrated in FIG.1, always-on-display framework 100 may include a locked state application 130 that manages the delivery of graphical indications 131 on always-on-display 105 while computing device 102 is operating in a locked mode. The locked state application 130 may cause graphical indications 131 to be output to always- on-display 105 through output component 135. Output component 135 may represent a display controller, rendering engine, or other graphical output pipeline implemented by processing circuitry 199 to manage delivery of graphical indications 131 to always-on- display 105. In a similar manner, graphical output of additional information 156 may be delivered (e.g., output for display) after computing device 102 transitions to the unlocked state. Additional information 156 may represent a graphical rendering beyond graphical indications 131 generated by expanded functionality application 155, ensuring a seamless transition from glanceable insights to full application engagement. In some implementations, expanded functionality application 155 may also present additional information, indicated in FIG.1 as additional information 156, such as contextual data, third-party content, or real-time updates associated with the user’s interaction. Additional information 156 may provide deeper insight, user actions, or multimedia content, extending the utility of the expanded functionality interface.

[0027] In response to detecting user interaction with graphical indication 131, computing device 102 may launch an expanded functionality application 155 (e.g., a full functionality variant of the application accessible while the phone is in an unlocked state or a view of the application which is only accessible while the phone is in the unlocked state) via which to present additional information or interactive content, allowing the user to move from glanceable insights to fully interactive engagement. Expanded functionality application(s) refers to a software module or process that, when executed in an unlocked state of the computing device, provides a broader set of interactive features and data related to the location-specific insight, compared to the limited or glanceable information presented on theDocket No.: 1333-871WO01 always-on display while the device is in a locked state. In some implementations, the techniques described herein may also be applied to other devices with display capabilities, such as smartwatches, glasses with integrated displays, or other wearable computing devices configured to present glanceable insights in a locked or inactive state. For instance, in response to detecting user interaction with graphical indication 131, computing device 102 may launch an expanded functionality application 155 via which to present additional information or interactive content to the display component of a smartwatch, smart glasses using the integrated display of the smart glasses, or to a display component of a wearable smart ring, which enables the user to access rich, interactive content beyond what is available in glanceable form. In some implementations, locked state application 130 may be an optional software module executed by processing circuitry 199, configured to manage graphical indications 131 while computing device 102 operates in a locked state. Other implementations may perform similar functions without requiring a distinct software module 130.

[0028] The architecture of computing device 102 supporting these features may include various hardware components integrated into computing device 102. For example, computing device 102 may include one or more processors, memory, presence-sensitive display components, user interface elements (such as touchscreens or buttons), graphical processing units (GPUs), sensors (such as GPS, accelerometers, or biometric sensors), and communication interfaces to support connectivity with remote services or artificial intelligence models. Processing circuitry 199 may include or represent one or more hardware- based processing components, such as application-specific integrated circuits (ASICs), digital signal processors (DSPs), microcontrollers, or general-purpose processors. Computing device 102 may also include or be communicably connected to always-on-display 105, which operates to display selected information while restricting user access to full device functionality until authentication is completed.

[0029] To conserve power and manage memory resources, computing device 102 may implement runtime constraints while operating in a locked mode. For example, processing circuitry 199 may utilize low-power cores to execute AI model inference or throttle background processes to reduce energy consumption. Additionally, always-on-display 105 may operate with reduced refresh rates, limited color depth, or dimmed brightness to further minimize battery drain. Cached user-context and location data may be stored in volatile memory with expiry timers to prevent memory exhaustion, ensuring that insights 122 are generated only when relevant and reducing unnecessary processing cycles.Docket No.: 1333-871WO01

[0030] In various implementations, computing device 102 may offer user-configurable options to control how graphical indications 131 are presented on always-on-display 105. These options may include enabling or disabling audible chimes, activating or suppressing haptic feedback, selecting visual-only display modes (such as dimmed or low-contrast graphics), and defining time-based or context-based notification profiles (e.g., "Do Not Disturb" schedules or location-specific modes). The configuration settings may allow users to tailor how and when they receive graphical indications 131, balancing informational delivery with privacy, battery consumption, and user attention preferences.

[0031] To maintain functionality when network connectivity is limited or unavailable, computing device 102 may employ fallback techniques that utilize locally cached insights or previously generated predictions. For example, the computing device may store static or recently retrieved location-specific information, such as operating hours, transit schedules, or past user interactions. This cached information allows the always-on-display to continue providing useful insights, even in offline conditions. When network access is restored, computing device 102 may update or refresh these insights to ensure that the information presented remains current and relevant to the user’s context.

[0032] Various types of artificial intelligence models may be used to generate the insights described above. These models may include natural language processing (NLP) models designed to extract relevant entities, analyze sentiment, or engage in conversational interactions. Large language models (LLMs), such as transformer-based architectures, may be trained to understand and generate language-based content. Computing device 102 may also utilize contextual ranking models that prioritize information based on user behavior, environmental factors, or historical data. Additional models may include classifiers trained to recognize patterns in user activity, predictive models for forecasting future user needs, and computer vision models capable of identifying objects, faces, or scenes. Some implementations may also incorporate generative models to produce graphical or visual content, recommendation engines for providing personalized suggestions, or safety and risk detection models to identify potentially unsafe situations. These models may operate individually or in combination to generate meaningful, context-aware insights for delivery to always-on-display 105 or other output interfaces of computing device 102.

[0033] Context-aware insights 122 may also include proactive safety and social tools. For instance, based on situational context and location 116 of a user, graphical indication 131 may present selectable prompts such as “Create a safety check” or “Remind my friend to call me in 1 hour.” If the user selects one of these prompts, AI model 190 may generate additionalDocket No.: 1333-871WO01 output, such as pre-populating a text message or scheduling a reminder, further extending the anticipatory capabilities of computing device 102.

[0034] Insights presented on always-on-display 105 may be consumed passively by the user or, in many cases, may go entirely unnoticed. Because computing device 102 typically operates in a locked or inactive state when presenting these insights, users may choose to ignore the displayed information or may not observe it at all. Computing device 102 may deliver graphical indications silently, without audio cues or haptic feedback, based on user- configured preferences. In some implementations, the graphical elements may appear as small, dimly lit icons or text, reducing visual disruption while maintaining glanceable availability of contextual insights. In some implementations, computing device 102 may display graphical indication 131 using different presentation modes depending on device state or user configuration. For example, computing device 102 may output graphical indication 131 using a high-contrast or high-brightness mode when the user is actively interacting with computing device 102, and may switch to a low-brightness, low-contrast, or monochrome mode when computing device 102 is idle or operating in a locked state. These alternative display modes may help reduce power consumption or minimize distractions when computing device 102 is not in active use. Additionally, computing device 102 may suppress or delay graphical indication 131 based on other device conditions, such as a low battery state, silent mode activation, or scheduled "Do Not Disturb" timeframes configured by the user.

[0035] Notwithstanding that graphical indication 131 may be ignored entirely, in some examples, a user may interact with graphical indication 131 displayed as output using always- on-display 105 of computing device 102. This interaction may involve tapping or otherwise engaging with the displayed insight, prompting computing device 102 to initiate a transition from a locked state toward expanded functionality.

[0036] In many implementations, computing device 102 will present graphical indications 131 while operating in a locked state to preserve user security. If the user interacts with a displayed insight, computing device 102 may prompt for authentication using methods such as a passcode, biometric input, or gesture-based unlocking. Once the user successfully authenticates, computing device 102 transitions to an unlocked state, allowing expanded interaction with the displayed insight or launching a related application for additional functionality. This user interaction triggers output component 135 to transition graphical indication 131 from always-on-display 105 to an expanded functionality interface, such as expanded functionality application 155. This transition completes the flow from glanceableDocket No.: 1333-871WO01 presentation to full application engagement as managed by always-on-display framework 100. If the user cancels or simply fails the authentication process, always-on-display framework 100 may suppress the transition to expanded functionality and loop back to maintain graphical indication 131 on always-on-display 105 in the locked state. This loopback ensures that computing device 102 continues operating under locked-state restrictions while preserving glanceable information without proceeding to expanded functionality. In this way, always-on-display framework 100 manages both forward transitions to expanded functionality and fallback scenarios where user interaction does not result in successful authentication.

[0037] Upon successful authentication, computing device 102 may automatically transition to an unlocked state and present expanded content related to the previously displayed insight. For example, computing device 102 may launch a relevant application to display additional details such as a reservation booking interface, navigation directions, or a complete venue menu. This transition allows the user to move seamlessly from passive observation of glanceable insights on always-on-display 105 to active engagement with expanded content.

[0038] Through the combination of glanceable insights and transitions to expanded functionality, computing device 102 provides contextually relevant information without requiring active user interaction, supporting user engagement with nearby information or services. The glanceable insights are ephemeral and non-persistent, allowing the user to consume, ignore, or miss the information without penalty, without notification backlogs, and without generating follow-up tasks or intrusive alerts that demand user attention. For instance, if the user misses insights about a nearby restaurant, they are not obligated later to sift through them and clear out a list of stale and now irrelevant notifications. By applying artificial intelligence-driven predictions to content presented via low-power always-on- display 105, computing device 102 presents contextually relevant information in a non- intrusive manner, supporting user awareness of nearby opportunities and services. Collectively, these features and interactions define the operational flow of always-on-display framework 100, as illustrated in FIG.1. Always-on-display framework 100 coordinates AI- driven insight generation, locked-state graphical indication output, user interaction detection, authentication transitions, and delivery of expanded functionality through output component 156. The framework manages state transitions both forward—from locked glanceable insights to unlocked expanded functionality—and backward, by maintaining or re-presenting graphical indications 131 if authentication is not completed. By managing these transitionsDocket No.: 1333-871WO01 cohesively, always-on-display framework 100 ensures a continuous and responsive user experience that spans both locked and unlocked operating modes.

[0039] FIG.2 is a block diagram illustrating further details of an example computing device, in accordance with one or more aspects of the present disclosure. Computing device 202 of FIG.2 is described below as an example of computing device 102 as illustrated in FIG.1.

[0040] Computing device 202 of FIG.2 may be an example of a mobile phone, a tablet computer, a laptop computer, a desktop computer, a server, a mainframe, a set-top box, a television, a wearable device (including watches, glasses, rings, etc.), a home automation device or system, a gaming system, a media player, an e-book reader, a mobile television platform, an automobile navigation or infotainment system, or any other type of mobile, non- mobile, wearable, and non-wearable computing device configured to communicate with a network, such as a local network or a public Internet.

[0041] FIG.2 illustrates only one particular example of computing device 202, and many other examples of computing device 202 may be used in other instances and may include a subset of the components included in example computing device 202 or may include additional components not shown in FIG.2.

[0042] As shown in the example of FIG.2, computing device 202 includes user interface component (UIC) 204, one or more processors 299, one or more input components 242, one or more communication units 244, one or more output components 246, always-on-display 205 (e.g., an ambient display), and one or more storage components 248. Storage components 248 of computing device 202 also include user interface (UI) module 206, artificial intelligence (AI) model 290 enabled to provide insight(s) 222, user-context 252, expanded functionality application 253 enabled to provide application graphical user interface (GUI) 254, and reduced functionality application 255 enabled to provide graphical indication 231.

[0043] One or more processors 299 are one example of processing circuitry 199 of FIG.1. UI module 206, as shown in the example of FIG.2, may be operable by computing device 202 to perform one or more functions, such as receive input and send indications of such input to other components associated with computing device 202, such as AI model 290 and / or available application modules including expanded functionality application 253 and reduced functionality application 255. UI module 206 may also receive data from components associated with computing device 202 such as AI model 290 and / or available application modules including expanded functionality application 253 and reduced functionality application 255. Using the data received, UI module 206 may cause other components associated with computing device 202, such as UI component 204, to provide output based onDocket No.: 1333-871WO01 the data. For instance, UI module 206 may receive data from AI model 290, expanded functionality application 253, and / or reduced functionality application 255 to display a graphical user interface (GUI).

[0044] Always-on-display 205 is an example of always-on-display 105 of FIG.1. AI model 290 is an example of AI model 190 of FIG.1. Insights 222 is an example of location-specific insights 122 of FIG.1. Graphical indication 231 is an example of graphical indication 131 of FIG 1. Application GUI 254 may provide additional information 156 of FIG.1.

[0045] Communication channels 250 may interconnect each of components 299, 204, 205, 244, 246, 242, and 248 for inter-component communications (physically, communicatively, and / or operatively). In some examples, communication channels 250 may include a system bus, a network connection, an inter-process communication data structure, or any other method for communicating data.

[0046] One or more input components 242 of computing device 202 may receive input. Examples of input are tactile, audio, and video input. One or more input components 242 of computing device 202, in one example, includes a presence-sensitive display, touch-sensitive screen, mouse, keyboard, voice responsive system, video camera, microphone or any other type of device for detecting input from a human or machine.

[0047] One or more output components 246 of computing device 202 may generate output. Always-on-display 205 is one example of an output component 246. Examples of output are tactile, audio, and video output. One or more output components 246 of computing device 202, in one example, includes a presence-sensitive display, sound card, video graphics adapter card, speaker, liquid crystal display (LCD), light-emitting diode (LED) display, miniLED, microLED, organic light-emitting diode (OLED) display, a light field display, haptic motors, linear actuating devices, or any other type of device for generating output to a human or machine.

[0048] One or more communication units 244 of computing device 202 may communicate with external devices via one or more wired and / or wireless networks by transmitting and / or receiving network signals on the one or more networks. Examples of one or more communication units 244 include a network interface card (e.g., an Ethernet card), an optical transceiver, a radio frequency transceiver, a GPS receiver, or any other type of device that can send and / or receive information. Other examples of one or more communication units 244 may include short wave radios, cellular data radios, wireless network radios, as well as universal serial bus (USB) controllers.Docket No.: 1333-871WO01

[0049] UIC 204 of computing device 202 may be hardware that functions as an input and / or output device for computing device 202. For example, UIC 204 may include a display component, which may be a screen at which information is displayed by UIC 204 and a presence-sensitive input component that may detect an object at and / or near always-on- display 205 (e.g., an ambient display component of computing device 202).

[0050] One or more processors 299 may implement functionality and / or execute instructions within computing device 202. For example, one or more processors 299 on computing device 202 may receive and execute instructions stored by storage components 248 that execute the functionality of always-on-display framework 100 of FIG.1, including executing artificial intelligence model 290, expanded functionality application 253 and reduced functionality application 255. The instructions executed by one or more processors 299 may cause computing device 202 to store information within storage components 248 during program execution. Examples of one or more processors 299 include application processors, display controllers, sensor hubs, and any other hardware configured to function as a processing unit. One or more processors 299 may execute instructions of UI module 206, artificial intelligence model 290, expanded functionality application 253, and reduced functionality application 255 to perform actions or functions. That is, UI module 206, artificial intelligence model 290, expanded functionality application 253, and reduced functionality application 255 may be operable by one or more processors 299 to perform various actions or functions of computing device 202.

[0051] One or more storage components 248 within computing device 202 may store information for processing during operation of computing device 202. That is, computing device 202 may store data accessed by UI module 206, artificial intelligence model 290, expanded functionality application 253, and reduced functionality application 255 during execution at computing device 202. In some examples, storage component 248 is a temporary memory, meaning that a primary purpose of storage component 248 is not long-term storage. Storage components 248 on computing device 202 may be configured for short-term storage of information as volatile memory and therefore not retain stored contents if powered off. Examples of volatile memories include random access memories (RAM), dynamic random- access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories known in the art.

[0052] Storage components 248, in some examples, also include one or more computer- readable storage media. Storage components 248 may be configured to store larger amounts of information than volatile memory. Storage components 248 may further be configured forDocket No.: 1333-871WO01 long-term storage of information as non-volatile memory space and retain information after power on / off cycles. Examples of non-volatile memories include magnetic hard disks, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. Storage components 248 may store program instructions and / or information (e.g., data) associated with UI module 206, artificial intelligence model 290, expanded functionality application 253, and reduced functionality application 255.

[0053] One or more processors 299 are configured to execute UI module 206, artificial intelligence model 290, expanded functionality application 253, and reduced functionality application 255 to perform any combination of the techniques described in this disclosure. For example, one or more processors 299 are configured to execute artificial intelligence model 290 to receive user-context 114 and location 116 (see FIG.1) and generate insights 222 as predictive output. One or more processors 299 are configured to execute reduced functionality application 255 to receive insights 222 and generate as output for display, graphical indication 231 of insight 222. One or more processors 299 are configured to execute expanded functionality application 253 to receive a request or triggering event to automatically launch and navigate to a source of additional information 156 (see FIG.1) on the condition that computing device 202 is in, or has transitioned to, an unlocked operating mode.

[0054] For example, referring to computing device 202 of FIG.2, user interface component 204 may include a presence-sensitive display configured as always-on-display 205. When computing device 202 is in a locked state, one or more processors 299 may execute AI model 290 to generate location-specific insights 222 based on user-context 252. These insights 222 may be surfaced as graphical indication 231 on always-on-display 205 by executing reduced functionality application 255. If the user interacts with graphical indication 231, UI module 206 may detect the interaction through input component 242 (e.g., presence-sensitive display), and one or more processors 299 may initiate an authentication challenge. Upon successful authentication, one or more processors 299 may transition computing device 202 to an unlocked operating mode and launch expanded functionality application 253. Expanded functionality application 253 may generate application GUI 254, presenting additional information 156 based on insights 222. The generated GUI may be rendered on always-on- display 205 through output component 246, completing the transition from glanceable information to interactive engagement.Docket No.: 1333-871WO01

[0055] FIGS.3A-3D are conceptual diagrams illustrating example graphical user interfaces, in accordance with aspects of this disclosure. FIGS.3A, 3B, 3C and 3D are described with respect to computing device 202 of FIG.2.

[0056] With reference to FIG.3A, as described above, when computing device 202 operates in locked mode 345, computing device 202 may continue to output information for display to always-on-display 305. For instance, always-on-display 305 may display a lock screen with additional information such as time-of-day, date, weather, and graphical indication 331 of a context-aware and location-specific insight 222. While in locked mode 345, computing device 202 may utilize a limited functionality variant of an application to output graphical indication 331 to always-on-display 305, until such time that a user successfully unlocks computing device 202. After unlocking computing device 202, an expanded functionality application variant may become available, via which to output additional information 356 (see FIG.3C) to always-on-display 305 while in unlocked mode 346.

[0057] As shown at FIG.3A, always-on-display 305 of computing device 202 may display various graphical elements 332 as part of graphical indication 331 of insight(s) 222. For instance, FIG.3A depicts graphical indication 331 showing that a user’s computing device 202 has a determined location 316 of “downtown restaurant,” as suggested by the user icon and the location flag provided by graphical elements 332. In certain examples, computing device 202 generates as output and for display, graphical indication 331 when AI model 290 satisfies a confidence threshold that computing device 202 is at a specific location for which AI model 202 has generated at least one contextually relevant and location-specific insight.

[0058] With reference to FIG.3B, the user of computing device 202 may ignore graphical indication 331 or may not even see graphical indication 331. However, the user may optionally interact with graphical indication 331 providing user-input 333 to computing device 202. Responsive to detecting user input 333 within always-on-display 305 at a location (e.g., a position or portion of always-on-display 305) associated with graphical indication 331, computing device 202 may prompt for or request user authentication credentials 334 to unlock computing device 202 and transition computing device 202 from operating in locked mode 345 to operating in unlocked mode 346 (see FIG.3C).

[0059] With reference to FIG.3C, computing device 202 is depicted as having successfully received authentication credentials 334 for transitioning transition computing device 202 from operating in locked mode 345 to operating in unlocked mode 346. Always-on-display 305 provides a user interface for computing device 202 while computing device 202 is operating in unlocked mode 346.Docket No.: 1333-871WO01

[0060] As depicted at FIG.3C, application GUI 354 from expanded functionality application 253 may be automatically launched (e.g., executed) at computing device 202 without further user interaction specifying what application to launch and application GUI 354 of expanded functionality application 253 may be automatically navigated to a source providing additional information 356. As depicted, application GUI 354 has automatically performed search 369 requesting from AI model 290 “What is popular here?” Application GUI 354 was launched and navigated, and in this example, performed the search, without further input from the user after user-input 333 providing an interaction with graphical indication 331 (see FIG.3B). Application GUI 354, and specifically AI model 290, is contextually aware of where “here” is, as location 316 was obtained previously. User-context was also obtained by AI model 290 and additional information 356 depicted within application GUI 354 may be customized based on location 316, user-context obtained, date, time, past visitor reviews, past visitor transactions, past visitor behaviors, prior transactions by the user of computing device 202, other relevant factors, or some combination thereof.

[0061] Additional information 356 is further provided by application GUI 354. For instance, as shown here, three dishes are provided by AI model 290 as additional information 356 along with predictive output generated by AI model 290 providing AI summary 371 indicating that: “Reviewers mention large portion sizes and recommend sharing family-style. Top dishes include: Chilean Sea Bass, Massaman Curry, and Sweet Potato Ice Cream.” Pricing information for the menu items is additionally provided within additional information 356.

[0062] In the lower portion of always-on-display 205 are several selectable prompts 360 which a user of computing device 202 may interact with to “Get a quick answer” as suggested by AI model 290. For instance, a user may interact with selectable prompt 360 to ask a question 361 by a voice to text entry mode, the user may interact with prompt 362 to inquire “What is the best dessert?” Or the user may interact with prompt 363 to ask “What are some vegan options?” When a user interacts with any of selectable prompts 360, an inquiry is passed into AI model 290 responsive to the user interaction, without the user needing to enter or type anything, although the user may optionally do so via the text entry box for search 369 near the top of application GUI 354.

[0063] With reference to FIG.3D, additionally depicted are surface links 372 identified and generated as output by AI model 290. For instance, as shown here, a user may interact with surfaced link 372 to get the full menu for the downtown restaurant. Additionally depicted is in-application content delivery 373 which in the example depicted here, automatically plays aDocket No.: 1333-871WO01 video. For instance, in-application content delivery 373 may play a video shared by another user or social media influencer for a dish at the restaurant corresponding to location 316 of the user’s computing device 202, such as playing a video of the sweet potato ice cream dish offered by the restaurant.

[0064] FIGS.4A-4D are conceptual diagrams illustrating example graphical user interfaces, in accordance with aspects of this disclosure. FIGS.4A-4D are described with respect to computing device 202 of FIG.2.

[0065] With reference to FIG.4A, as described above, when computing device 202 operates in locked mode 445, computing device 202 may continue to output information for display to always-on-display 405. For instance, such information may be output for display via always- on-display 405 to a lock screen of computing device 202.

[0066] As shown at FIG.4A, always-on-display 405 of computing device 202 may display various graphical elements 432 as part of graphical indication 431 of insight(s) 222. For instance, FIG.4A depicts graphical indication 431 showing that a user’s computing device 202 has a determined location 416 of “near downtown restaurant.” Based on user-context information associated with user and location 416 for the user’s computing device 202, AI model 290 may generate graphical indication 431 with GUI elements 432 providing navigational guidance (e.g., a light or reduced functionality navigational mode) from present location 416 associated with the user as determined by computing device 202 to the downtown restaurant indicated by pin 444. In certain examples, computing device 202 generates as output and for display, graphical indication 431 when a distance satisfies a threshold distance between location 416 and a specific location for which AI model 202 has generated at least one contextually relevant and location-specific insight 222. Computing device 202 may receive user input 433 as an interaction with graphical indication 431 output for display to always-on-display 405.

[0067] Consider for example, a user having previously searched for the restaurant or for a store. When AI model 290 satisfies a confidence threshold that the user is both within a threshold distance to the previously searched location and that AI model 290 has one or more contextually relevant and location-specific insights 222 for the location, then AI model 290 may provide as output, graphical indication 431. In some examples, AI model 290 may request a locked state application variant to output graphical indication 431 to always-on- display 405 based on location-specific insight(s) 222 sent to the locked state application variant by AI model 290. In such a way, the user may be guided to the previously searchedDocket No.: 1333-871WO01 location without having to unlock computing device 202 and without having to request or reinitiate the search for the previously searched location.

[0068] In some examples, interacting with graphical indication 431 may trigger computing device 202 to expand the glanceable content displayed on always-on-display 405 without requiring user authentication. For instance, computing device 202 may present additional information such as alternate route options, nearby points of interest, estimated arrival times, or contextual status updates (e.g., “moderate traffic ahead”) directly on always-on-display 405 while maintaining locked mode 445. This expanded glanceable presentation allows the user to receive enhanced contextual information beyond the initial graphical indication 431, while continuing to restrict access to full application functionality until authentication is successfully completed. In such a way, computing device 202 provides a progressive disclosure of information that balances user convenience with device security.

[0069] With reference to FIG.4B, computing device 202 is depicted as having successfully received authentication credentials transitioning transition computing device 202 from operating in locked mode 445 to operating in unlocked mode 446. Always-on-display 405 provides a user interface for computing device 202 while computing device 202 is operating in unlocked mode 446.

[0070] In some implementations, interacting with graphical indication 431 may trigger computing device 202 to provide an expanded glanceable view on always-on-display 405 while maintaining locked mode 445. This expanded glanceable view may include additional contextual details, such as alternative route suggestions, updated arrival estimates, or other status information, beyond what was initially presented in graphical indication 431. This enhanced glanceable content allows the user to review more information without needing to unlock computing device 202. If the user wishes to interact further, computing device 202 may prompt for authentication to access full application functionality, as described below.

[0071] As depicted at FIG.4B, application GUI 454 may be automatically launched and provided from expanded functionality application 253 responsive to user input 433 interacting with always-on-display 405 and specifically upon detection of the user input in association with graphical indication 431. Graphical elements 432 of always-on-display provide light navigation for the user from location 416 near the downtown restaurant to the downtown restaurant. When the user interacted with graphical indication 431, computing device 202 automatically launched expanded functionality application 253 to output for display to application GUI 454, while computing device 202 is operating in unlocked mode 446.Docket No.: 1333-871WO01

[0072] As depicted here, with a user having location 416 near the downtown restaurant, application GUI 454 shows the user’s initial location 461 and destination 462, as well as mode of transportation 463. Computing device 202 may determine, based on data from sensors (e.g., accelerometers, GPS, or other motion-detecting components) or external data sources, that the user is walking, driving, or taking public transportation. Additional information 456 output for display to application GUI 454 showing both a suggested route as well as route information, indicating the distance is 0.7 miles which is mostly flat and anticipated to take approximately 16 minutes.

[0073] With reference to FIG.4C, computing device 202 is again depicted as having successfully received authentication credentials transitioning transition computing device 202 from operating in locked mode 445 to operating in unlocked mode 446. Always-on-display 405 provides a user interface for computing device 202 while computing device 202 is operating in unlocked mode 446.

[0074] Application GUI 454 is updated and now depicts turn-by-turn language to the user in natural language utilizing a natural language processing (NLP) component of AI model 290. For instance, additional information 456 depicted here indicates directions toward a destination specific to the user, but also provides contextually aware references to landmarks, such as “Make a left turn at Jones Avenue, after the coffee shop on the left.” AI model 290 is enabled to reference the coffee shop as AI model 290 has obtained both a current location of computing device 202 as well as contextually relevant and location-specific insights 222 for the user, such as where the user is heading as a destination.

[0075] Again depicted are selectable prompts 460 which are contextually relevant to the user’s present context and experience, providing selectable prompts 460 to ask about anything, with AI model 290 suggesting “How late does the train run today” as prompt 466 and “What food is available near my station” as prompt 464. As before, AI model 290 is enabled to resolve context-specific references such as “today” and “my station” because AI model 290 has access to context data including the current date, time, location of computing device 202, intended destination, detected mode of transportation, and other user-specific contextual signals.

[0076] With reference to FIG.4D, computing device 202 is depicted as providing graphical indication 431 for a contextually aware and location-specific insight 222 to always-on- display 405. Specifically shown here is alert 499 by AI model 290 indicating there is a: “Serious traffic delay on [the user’s] usual route to work.” Computing device 202 may detect user input 433 interacting with graphical indication 431, responsive to which computingDocket No.: 1333-871WO01 device 202 may automatically launch expanded functionality application 253 via which computing device 202 may provide alternative navigational guidance to mitigate the serious traffic delay.

[0077] FIG.5 is a conceptual diagram illustrating example graphical user interfaces, in accordance with aspects of this disclosure. As shown here, always-on-display 505A on the left side of FIG.5 depicts computing device 202 operating in locked mode 545 and providing as output for display to always-on-display 505, graphical indication 531. In particular, graphical indication 531 provides context-aware and location-specific insight 222 that a “25- minute slowdown” is present on highway-101, determined by AI model 290 to be timing and relevant to the user of computing device 202. Computing device 202 may detect a user interaction in the form of user input 533A, causing always-on-display 505A to transition to always-on-display 505B located in the center of FIG.5.

[0078] As depicted by always-on-display 505B, in response to user input 533A, computing device 202 outputs intermediate display 532 to always-on-display 505B with information that is both contextually relevant and location-specific to the user and also contextually relevant to the previously displayed graphical indication 531. In particular, always-on-display 505B depicts notification 561 indicating that an accident is 3-miles away from on the user’s current route. Additionally provided is selectable option 562 generated by AI model 290 providing an alternate route available to the user, indicated as being an estimated 12-minutes faster. Further depicted by always-on-display 505B is selectable option 563 to add a destination via voice to text. Computing device 202 provides intermediate display 532 for output while maintaining locked mode 545, thereby allowing the user to access additional glanceable information without requiring authentication. This enables progressive disclosure of contextual information while continuing to restrict access to sensitive content or expanded application functionality until user authentication is successfully completed.

[0079] The user may simply observe the information provided by intermediate display 532 and cease further interactions with computing device 202. However, as depicted by user input 533B, computing device 202 detects a further user interaction and responsively initiates expanded functionality application 553 to provide additional information 556 to the user via always-on-display 505D in an unlocked mode. However, the user must first unlock computing device 202 by providing authentication credentials 534 as depicted by always-on- display 505C while computing device remains locked, enabling computing device 202 to transition from operating in locked mode 545 to operating in an unlocked mode as depicted by always-on-display 505D. Once unlocked, computing device 202 and specifically expandedDocket No.: 1333-871WO01 functionality application 506 may provide full unrestricted functionality which is limited by computing device 202 when operating in locked mode 545.

[0080] In such a way, implementation of context-aware information output to always-on- display 205 enables computing device 202 to communicate timely and contextually relevant information to a user in a glanceable format that minimizes the need for full user interaction. Moreover, context-aware information output to always-on display 205 enables proactive communication of relevant information to a user without requiring the user to perform a search or submit a request, as would be required in reactive systems.

[0081] Technical benefits of computing device 202 are attributable to the ability of computing device 202 to provide contextually relevant and timely information to users through the always-on display (AOD) feature when implemented on mobile computing devices. By leveraging artificial intelligence (AI) to generate location-specific insights based on user-context and current location, aspects of the disclosure enhance the user experience in several ways. Aspects of the disclosure filter and present only the most relevant information, reducing cognitive load and preventing information overload. Unlike traditional systems that rely on user-initiated interactions, aspects of the disclosure anticipate user needs and provide information proactively, enhancing convenience and usability. Aspects of the disclosure enable users to interact with location-specific insights directly from always-on display 205 without requiring the device to be unlocked, encouraging user engagement with minimal friction. Users can choose to interact with displayed insights to seamlessly transition from a locked mode to an unlocked mode, launching relevant applications and navigating to additional information without requiring multiple user inputs. Aspects of the disclosure also protect sensitive information by ensuring that full application functionality is accessible only after successful user authentication, maintaining device security while providing useful glanceable information. Further, always-on display 205 operates in a low-power mode, providing continuous access to important information without significantly draining battery life. AI model 190, 290 can generate insights based on a variety of contextual cues, such as user location, prior searches, and surrounding environmental signals, making the information highly relevant and personalized. Additionally, aspects of the disclosure enable real-time navigation guidance, traffic updates, and personalized recommendations, such as restaurant wait times or menu items, directly on always-on display 205, improving the overall user experience. Overall, implementation and use of the techniques for displaying context-aware information to always-on display 205 of a user’s mobile computing device significantly enhances the functionality and user experience of mobile computing devices by providingDocket No.: 1333-871WO01 timely, relevant, and easily accessible information through always-on display 205, while maintaining security and energy efficiency.

[0082] FIG.6 is a flowchart illustrating example operations performed by an example computing device that is configured in accordance with one or more aspects of the present disclosure. FIG.6 is described below in the context of always-on-display framework 100 of FIG.1 and computing device 202 of FIG.2.

[0083] As shown in FIG.6, one or more processors 299 may determine a current location 116 (602) and obtain user-context 114 (604).

[0084] One or more processors 299 may send input to AI model 290 specifying the current location 116 and user-context 114 (606) and generate location-specific insights 222 as predictive output from AI model 290 based on the input (608). For example, one or more processors 299 of computing device 202 may generate a plurality of location-specific insights 222 while computing device 202 operates in a locked mode by at least applying artificial intelligence model 290 to the current location 116 of computing device 202 and user-context 114 associated with computing device 202.

[0085] One or more processors 299 may output a graphical indication 231 for location- specific insight 222 to always-on-display 205 of computing device 202 while operating in a locked mode (610). For example, while computing device 202 operates in the locked mode, one or more processors 299 of computing device 202 may output, by always-on-display 205 device, graphical indication 231 of at least one location-specific insight 222 from the plurality of location-specific insights 222.

[0086] Computing device 202 may detect user input 121 associated with graphical indication 231 output to always-on-display 205 (612). For example, computing device 202 may detect user input 121 at location 116 of always-on-display device 205 associated with graphical indication 231.

[0087] One or more processors 299 may output additional information associated with the location-specific insight while operating computing device 202 in the unlocked mode (614). For example, further in response to detection of user input 121, one or more processors 299 of computing device 202 may execute an application associated with at least one location- specific insight and while computing device 202 operates in the unlocked mode, output additional information 156 to a graphical user interface of the application associated with the at least one location-specific insight.

[0088] This disclosure includes the following examples.

[0089] Example 1 – A method comprising: determining, by one or more processors of aDocket No.: 1333-871WO01 computing device, a current location of the computing device; obtaining, by the one or more processors, user-context associated with the computing device; generating, by the one or more processors, a plurality of location-specific insights while the computing device is operating in a locked mode by at least applying an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; outputting, by an always-on-display device in communication with the computing device while the computing device is operating in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detecting, by the one or more processors, a user input at a location of the always-on-display device associated with the graphical indication; and in response to detecting the user input, outputting, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of an application associated with the at least one location-specific insight.

[0090] Example 2 – The method of example 1, further comprising: in response to detecting the user input: after transitioning the computing device from operating in the locked mode to operating in the unlocked mode, launching, by the one or more processors of the computing device, the application associated with the at least one location-specific insight without obtaining new user input specifying the application associated with the at least one location- specific insight; navigating the graphical user interface of the application to a source of the additional information without user navigational input specifying the source of the additional information; and responsive to navigating the graphical user interface of the application to the source of the additional information, outputting, by the display device in communication with the computing device, the additional information to the graphical user interface of the application.

[0091] Example 3 – The method of example 1 or 2, further comprising: obtaining, by the one or more processors of the computing device, output from the artificial intelligence model specifying the additional information responsive to providing, as input to the artificial intelligence model, the current location of the computing device and the user-context associated with the computing device; and wherein the artificial intelligence model specifies as output, at least one of: a website providing the additional information; a third-party cloud service providing the additional information; an application programming interface providing access to the additional information; the graphical user interface of the application executing, by the one or more processors of the computing device, with access to the additional information; a mapping service with access to the additional information; and a social mediaDocket No.: 1333-871WO01 platform with access to the additional information.

[0092] Example 4 – The method of any of examples 1-3, further comprising: generating, by the one or more processors, the plurality of location-specific insights by one or more of: providing, as input, the current location of the computing device and the user-context associated with the computing device to a locally installed artificial intelligence model executing, by the one or more processors of the computing device; and sending, by the one or more processors of the computing device, the current location of the computing device and the user-context associated with the computing device to the artificial intelligence model executing at a third-party cloud platform communicably interfaced with the computing device over a public Internet.

[0093] Example 5 – The method of any of examples 1-4, wherein the always-on-display device comprises an ambient display for outputting, by the computing device, information, including the graphical indication of the at least one location-specific insight, while computing device is inactive due to a lack of user interactions.

[0094] Example 6 – The method of any of examples 1-5, wherein the plurality of location- specific insights include one or more of: predictive output by the artificial intelligence model based on previous visitor information for a visitor computing device corresponding to the current location determined for the computing device; the predictive output by the artificial intelligence model based on the previous visitor information for the visitor computing device within a threshold distance to the current location determined for the computing device; one or more prior user queries received by the computing device determined by the artificial intelligence model as being associated with the current location determined for the computing device; one or more prompts to the artificial intelligence model by the computing device; one or more answers provided by the artificial intelligence model responsive to the one or more prompts to the artificial intelligence model by the computing device or one or more prompts to the artificial intelligence model by the visitor computing device corresponding to the current location determined for the computing device.

[0095] Example 7 – The method of any of examples 1-6, wherein the graphical indication of the at least one location-specific insight specifies: navigation instructions; map information; traffic delay information for a route determined by the artificial intelligence model; public transportation information associated with the current location determined for the computing device; user reviews corresponding to the current location determined for the computing device; the user reviews for venues within a threshold distance of the current location determined for the computing device; previous answers generated by the artificialDocket No.: 1333-871WO01 intelligence model responsive to previous visitors to the current location determined for the computing device; or new answers generated by the artificial intelligence model about the current location determined for the computing device responsive to a user inquiry obtained by the computing device.

[0096] Example 8 – The method of any of examples 1-7, wherein the graphical indication of the at least one location-specific insight is generated by the artificial intelligence model based at least in part on one or more of the following: the user-context indicating a current mode of transportation; the user-context indicating date and time information for the current location determined for the computing device; the user-context indicating a prior destination search; the user-context indicating a prior destination arrival point and frequency; the user-context indicating prior prompts or inquiries to the artificial intelligence model; and the user-context indicating user profile data with a third-party platform associated with the computing device.

[0097] Example 9 – The method of any of examples 1-8, further comprising: identifying, by the one or more processors as part of the user-context, a business associated with the current location; and obtaining, by the one or more processors, for the business identified in association with the current location, at least one of: menu recommendations for the business identified; wait times for the business identified; available reservation times for the business identified; menu items and menu prices for the business identified; prior user purchases for the business identified; and prior user interactions with the business identified.

[0098] Example 10 – The method of any of examples 1-9, further comprising: outputting, by the always-on-display device in communication with the computing device while the computing device is operating in the locked mode, the graphical indication from a limited functionality version of the application configured to output the at least one location-specific insight utilizing a graphical user interface element associated with the graphical indication; wherein the user input is detected as a user interaction with the graphical user interface element; and wherein the method further comprises: responsive to detecting the user interaction with the graphical user interface element, triggering, by the one or more processors executing the limited functionality version of the application, the application having functionality for outputting the additional information associated with the at least one location-specific insight while the computing device is operating in the unlocked mode.

[0099] Example 11 – The method of any of examples 1-10, further comprising: outputting, by the one or more processors, selectable prompts displayed to the graphical user interface of the application specifying suggested questions for the artificial intelligence model.

[0100] Example 12 – The method of any of examples 1-11, further comprising: outputting,Docket No.: 1333-871WO01 by the one or more processors, the additional information to a connected display selected from the group comprising: a smartwatch; eyeglasses; a presence-sensitive display integrated with the computing device; and a remote display component communicably linked with the computing device.

[0101] Example 13 – The method of any of examples 1-12, further comprising: detecting, by the one or more processors, the user input by one or more of: detecting a user interaction at the location of the always-on-display device associated with the graphical indication; detecting the user interaction at a smartwatch display interface in communication with the computing device; detecting the user interaction at wearable ring interface in communication with the computing device; detecting the user interaction at wearable band interface in communication with the computing device; detecting the user interaction at wearable glasses interface in communication with the computing device; detecting the user interaction based on a physical tap interaction sensed at the wearable glasses interface in communication with the computing device; detecting the user interaction based on a voice interaction sensed at a vehicle infotainment system interface in communication with the computing device; detecting the user interaction based on a tap or touch interaction sensed at the vehicle infotainment system interface in communication with the computing device; and detecting the user interaction based on the voice interaction sensed by a microphone in communication with any the computing device.

[0102] Example 14 – A computing device comprising: an always-on-display device; a display device; one or more processors; and non-transitory computer readable media that stores instructions, wherein the instructions, when executed by the one or more processors, configure the one or more processors to: determine, by the one or more processors, a current location of the computing device; obtain, by the one or more processors, user-context associated with the computing device; generate, by the one or more processors, a plurality of location-specific insights while the computing device operates in a locked mode by at least application of an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; output, by the always-on-display device while the computing device operates in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detect, by the one or more processors, a user input at a location of the always-on-display device associated with the graphical indication; and in response to detection of the user input, output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of anDocket No.: 1333-871WO01 application associated with the at least one location-specific insight.

[0103] Example 15 – The computing device of example 14, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: in response to detection of the user input: after the computing device transitions from operation in the locked mode to operation in the unlocked mode, launch, by the one or more processors, the application associated with the at least one location-specific insight without new user input obtained to specify the application associated with the at least one location-specific insight; navigate the graphical user interface of the application to a source of the additional information without user navigational input to specify the source of the additional information; and responsive to navigation of the graphical user interface of the application to the source of the additional information, output, by the display device in communication with the computing device, the additional information to the graphical user interface of the application.

[0104] Example 16 – The computing device of example 14 or 15, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: generate, by the one or more processors, the plurality of location-specific insights by one of: the current location of the computing device and the user-context associated with the computing device provided to a locally installed artificial intelligence model of the computing device; or the current location of the computing device and the user-context associated with the computing device sent to the artificial intelligence model at a third-party cloud platform communicably interfaced with the computing device over a public Internet.

[0105] Example 17 – The computing device of any of examples 14-16, wherein the graphical indication of the at least one location-specific insight specifies: navigation instructions; map information; traffic delay information for a route determined by the artificial intelligence model; public transportation information associated with the current location determined for the computing device; user reviews corresponding to the current location determined for the computing device; the user reviews for venues within a threshold distance of the current location determined for the computing device; previous answers generated by the artificial intelligence model responsive to previous visitors to the current location determined for the computing device; or new answers generated by the artificial intelligence model about the current location determined for the computing device responsive to a user inquiry obtained by the computing device.

[0106] Example 18 – The computing device of any of examples 14-17, wherein the graphical indication of the at least one location-specific insight is generated by the artificial intelligenceDocket No.: 1333-871WO01 model based at least in part on one or more of the following: the user-context indicating a current mode of transportation; the user-context indicating date and time information for the current location determined for the computing device; the user-context indicating a prior destination search; the user-context indicating a prior destination arrival point and frequency; the user-context indicating prior prompts or inquiries to the artificial intelligence model; and the user-context indicating user profile data with a third-party platform associated with the computing device.

[0107] Example 19 – The computing device of any of examples 14-19, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: identify, by the one or more processors as part of the user-context, a business associated with the current location; and obtain, by the one or more processors, for the business identified in association with the current location, at least one of: menu recommendations for the business identified; wait times for the business identified; available reservation times for the business identified; menu items and menu prices for the business identified; prior user purchases for the business identified; and prior user interactions with the business identified.

[0108] Example 20 – Non-transitory computer-readable storage media comprising instructions that, when executed, configure one or more processors of a computing device to: determine a current location of the computing device; obtain user-context associated with the computing device; generate a plurality of location-specific insights while the computing device operates in a locked mode by at least application of an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; output, by an always-on-display device while the computing device operates in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detect a user input at a location of the always- on-display device associated with the graphical indication; and in response to detection of the user input, output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of an application associated with the at least one location-specific insight.

[0109] Example 21 – A computer program product comprising one or more instructions that, when executed by at least one processor, cause the at least one processor to perform any of the methods of examples 1-13.

[0110] Example 22 – A device comprising means for performing any of the methods of examples 1-13.Docket No.: 1333-871WO01

[0111] By way of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other storage medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer- readable medium. For example, if instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage mediums and media and data storage media do not include connections, carrier waves, signals, or other transient media, but are instead directed to non- transient, tangible storage media. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of a computer-readable medium.

[0112] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structures or any other structures suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and / or software modules. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0113] The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC) or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require realization by different hardware units. Rather, as described above, various units may be combined in a hardware unit or provided by a collection of inter- operative hardware units, including one or more processors as described above, in conjunction with suitable software and / or firmware.Docket No.: 1333-871WO01

[0114] Various embodiments have been described. These and other embodiments are within the scope of the following claims.

Claims

Docket No.: 1333-871WO01 WHAT IS CLAIMED IS:

1. A method comprising: determining, by one or more processors of a computing device, a current location of the computing device; obtaining, by the one or more processors, user-context associated with the computing device; generating, by the one or more processors, a plurality of location-specific insights while the computing device is operating in a locked mode by at least applying an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; outputting, by an always-on-display device in communication with the computing device while the computing device is operating in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detecting, by the one or more processors, a user input at a location of the always-on- display device associated with the graphical indication; and in response to detecting the user input, outputting, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of an application associated with the at least one location-specific insight.

2. The method of claim 1, further comprising: in response to detecting the user input: after transitioning the computing device from operating in the locked mode to operating in the unlocked mode, launching, by the one or more processors of the computing device, the application associated with the at least one location-specific insight without obtaining new user input specifying the application associated with the at least one location- specific insight; navigating the graphical user interface of the application to a source of the additional information without user navigational input specifying the source of the additional information; and responsive to navigating the graphical user interface of the application to the source of the additional information, outputting, by the display device in communication with theDocket No.: 1333-871WO01 computing device, the additional information to the graphical user interface of the application.

3. The method of claim 1 or 2, further comprising: obtaining, by the one or more processors of the computing device, output from the artificial intelligence model specifying the additional information responsive to providing, as input to the artificial intelligence model, the current location of the computing device and the user-context associated with the computing device; and wherein the artificial intelligence model specifies as output, at least one of: a website providing the additional information; a third-party cloud service providing the additional information; an application programming interface providing access to the additional information; the graphical user interface of the application executing, by the one or more processors of the computing device, with access to the additional information; a mapping service with access to the additional information; and a social media platform with access to the additional information.

4. The method of any of claims 1-3, further comprising: generating, by the one or more processors, the plurality of location-specific insights by one or more of: providing, as input, the current location of the computing device and the user-context associated with the computing device to a locally installed artificial intelligence model executing, by the one or more processors of the computing device; and sending, by the one or more processors of the computing device, the current location of the computing device and the user-context associated with the computing device to the artificial intelligence model executing at a third-party cloud platform communicably interfaced with the computing device over a public Internet.

5. The method of any of claims 1-4, wherein the always-on-display device comprises an ambient display for outputting, by the computing device, information, including the graphical indication of the at least one location-specific insight, while computing device is inactive due to a lack of user interactions.Docket No.: 1333-871WO01 6. The method of any of claims 1-5, wherein the plurality of location-specific insights include one or more of: predictive output by the artificial intelligence model based on previous visitor information for a visitor computing device corresponding to the current location determined for the computing device; the predictive output by the artificial intelligence model based on the previous visitor information for the visitor computing device within a threshold distance to the current location determined for the computing device; one or more prior user queries received by the computing device determined by the artificial intelligence model as being associated with the current location determined for the computing device; one or more prompts to the artificial intelligence model by the computing device; one or more answers provided by the artificial intelligence model responsive to the one or more prompts to the artificial intelligence model by the computing device or one or more prompts to the artificial intelligence model by the visitor computing device corresponding to the current location determined for the computing device.

7. The method of any of claims 1-6, wherein the graphical indication of the at least one location-specific insight specifies: navigation instructions; map information; traffic delay information for a route determined by the artificial intelligence model; public transportation information associated with the current location determined for the computing device; user reviews corresponding to the current location determined for the computing device; the user reviews for venues within a threshold distance of the current location determined for the computing device; previous answers generated by the artificial intelligence model responsive to previous visitors to the current location determined for the computing device; or new answers generated by the artificial intelligence model about the current location determined for the computing device responsive to a user inquiry obtained by the computing device.Docket No.: 1333-871WO01 8. The method of any of claims 1-7, wherein the graphical indication of the at least one location-specific insight is generated by the artificial intelligence model based at least in part on one or more of the following: the user-context indicating a current mode of transportation; the user-context indicating date and time information for the current location determined for the computing device; the user-context indicating a prior destination search; the user-context indicating a prior destination arrival point and frequency; the user-context indicating prior prompts or inquiries to the artificial intelligence model; and the user-context indicating user profile data with a third-party platform associated with the computing device.

9. The method of any of claims 1-8, further comprising: identifying, by the one or more processors as part of the user-context, a business associated with the current location; and obtaining, by the one or more processors, for the business identified in association with the current location, at least one of: menu recommendations for the business identified; wait times for the business identified; available reservation times for the business identified; menu items and menu prices for the business identified; prior user purchases for the business identified; and prior user interactions with the business identified.

10. The method of any of claims 1-9, further comprising: outputting, by the always-on-display device in communication with the computing device while the computing device is operating in the locked mode, the graphical indication from a limited functionality version of the application configured to output the at least one location-specific insight utilizing a graphical user interface element associated with the graphical indication; wherein the user input is detected as a user interaction with the graphical user interface element; and wherein the method further comprises:Docket No.: 1333-871WO01 responsive to detecting the user interaction with the graphical user interface element, triggering, by the one or more processors executing the limited functionality version of the application, the application having functionality for outputting the additional information associated with the at least one location-specific insight while the computing device is operating in the unlocked mode.

11. The method of any of claims 1-10, further comprising: outputting, by the one or more processors, selectable prompts displayed to the graphical user interface of the application specifying suggested questions for the artificial intelligence model.

12. The method of any of claims 1-11, further comprising: outputting, by the one or more processors, the additional information to a connected display selected from the group comprising: a smartwatch; eyeglasses; a presence-sensitive display integrated with the computing device; and a remote display component communicably linked with the computing device.

13. The method of any of claims 1-12, further comprising: detecting, by the one or more processors, the user input by one or more of: detecting a user interaction at the location of the always-on-display device associated with the graphical indication; detecting the user interaction at a smartwatch display interface in communication with the computing device; detecting the user interaction at wearable ring interface in communication with the computing device; detecting the user interaction at wearable band interface in communication with the computing device; detecting the user interaction at wearable glasses interface in communication with the computing device; detecting the user interaction based on a physical tap interaction sensed at the wearable glasses interface in communication with the computing device;Docket No.: 1333-871WO01 detecting the user interaction based on a voice interaction sensed at a vehicle infotainment system interface in communication with the computing device; detecting the user interaction based on a tap or touch interaction sensed at the vehicle infotainment system interface in communication with the computing device; and detecting the user interaction based on the voice interaction sensed by a microphone in communication with any the computing device.

14. A computing device comprising: an always-on-display device; a display device; one or more processors; and non-transitory computer readable media that stores instructions, wherein the instructions, when executed by the one or more processors, configure the one or more processors to: determine, by the one or more processors, a current location of the computing device; obtain, by the one or more processors, user-context associated with the computing device; generate, by the one or more processors, a plurality of location-specific insights while the computing device operates in a locked mode by at least application of an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; output, by the always-on-display device while the computing device operates in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detect, by the one or more processors, a user input at a location of the always-on- display device associated with the graphical indication; and in response to detection of the user input, output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of an application associated with the at least one location-specific insight.

15. The computing device of claim 14, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: in response to detection of the user input:Docket No.: 1333-871WO01 after the computing device transitions from operation in the locked mode to operation in the unlocked mode, launch, by the one or more processors, the application associated with the at least one location-specific insight without new user input obtained to specify the application associated with the at least one location-specific insight; navigate the graphical user interface of the application to a source of the additional information without user navigational input to specify the source of the additional information; and responsive to navigation of the graphical user interface of the application to the source of the additional information, output, by the display device in communication with the computing device, the additional information to the graphical user interface of the application.

16. The computing device of claim 14 or 15, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: generate, by the one or more processors, the plurality of location-specific insights by one of: the current location of the computing device and the user-context associated with the computing device provided to a locally installed artificial intelligence model of the computing device; or the current location of the computing device and the user-context associated with the computing device sent to the artificial intelligence model at a third-party cloud platform communicably interfaced with the computing device over a public Internet.

17. The computing device of any of claims 14-16, wherein the graphical indication of the at least one location-specific insight specifies: navigation instructions; map information; traffic delay information for a route determined by the artificial intelligence model; public transportation information associated with the current location determined for the computing device; user reviews corresponding to the current location determined for the computing device; the user reviews for venues within a threshold distance of the current location determined for the computing device;Docket No.: 1333-871WO01 previous answers generated by the artificial intelligence model responsive to previous visitors to the current location determined for the computing device; or new answers generated by the artificial intelligence model about the current location determined for the computing device responsive to a user inquiry obtained by the computing device.

18. The computing device of any of claims 14-17, wherein the graphical indication of the at least one location-specific insight is generated by the artificial intelligence model based at least in part on one or more of the following: the user-context indicating a current mode of transportation; the user-context indicating date and time information for the current location determined for the computing device; the user-context indicating a prior destination search; the user-context indicating a prior destination arrival point and frequency; the user-context indicating prior prompts or inquiries to the artificial intelligence model; and the user-context indicating user profile data with a third-party platform associated with the computing device.

19. The computing device of any of claims 14-19, wherein the instructions, when executed by the one or more processors, further configure the one or more processors to: identify, by the one or more processors as part of the user-context, a business associated with the current location; and obtain, by the one or more processors, for the business identified in association with the current location, at least one of: menu recommendations for the business identified; wait times for the business identified; available reservation times for the business identified; menu items and menu prices for the business identified; prior user purchases for the business identified; and prior user interactions with the business identified.

20. Non-transitory computer-readable storage media comprising instructions that, when executed, configure one or more processors of a computing device to:Docket No.: 1333-871WO01 determine a current location of the computing device; obtain user-context associated with the computing device; generate a plurality of location-specific insights while the computing device operates in a locked mode by at least application of an artificial intelligence model to the current location of the computing device and the user-context associated with the computing device; output, by an always-on-display device while the computing device operates in the locked mode, a graphical indication of at least one location-specific insight from the plurality of location-specific insights; detect a user input at a location of the always-on-display device associated with the graphical indication; and in response to detection of the user input, output, by a display device in communication with the computing device while the computing device is operating in the unlocked mode, additional information to a graphical user interface of an application associated with the at least one location-specific insight.

21. A computer program product comprising one or more instructions that, when executed by at least one processor, cause the at least one processor to perform any of the methods of examples 1-13.

22. A device comprising means for performing any of the methods of examples 1-13.

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