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Adaptive Screen Layouts Based On Viewer Proximity From Home Devices, Daniele Midi, William Schilit
Adaptive Screen Layouts Based On Viewer Proximity From Home Devices, Daniele Midi, William Schilit
Defensive Publications Series
Smart devices in the form of personal assistants are becoming more common and more dynamic. In addition to audibly exchanging information with a user via a mechanism such as a smart speaker, a personal assistant may now include a display to present useful ambient information to a user, such as time, weather, calendar information, or upcoming events. Techniques are described for adapting a screen layout of such a display based on proximity of a viewer relative to the display, allowing an effective and efficient presentation of the useful, ambient information.
Dynamic Slider Scaling, Michael Alger
Dynamic Slider Scaling, Michael Alger
Defensive Publications Series
Techniques are described that enable dynamic slider scaling. In a VR user interface with dynamic slider scaling, the slider control expands when the user selects the control. The expanded control offers better control to adjust the slider and may include additional information that is not available with conventional slider controls. When the user has completed the adjustment and releases the slider control, it reverts to its original size and shape to conserve space in the VR user interface.
Smart-Voice Invocation Of Scenes In Home-Automation Systems, Daniele Midi, William Schilit, Tianchun Yang
Smart-Voice Invocation Of Scenes In Home-Automation Systems, Daniele Midi, William Schilit, Tianchun Yang
Defensive Publications Series
Home environments are rapidly becoming more and more automated via the use of voice-recognizing personal assistants. Home-automation systems using a voice-recognizing personal assistant are capable of configuring smart devices of a home, such as lighting, security systems, or environmental controls, to particular operational settings which, when aggregated across multiple smart devices, constitute a particular scene. Techniques for a home-automation system to configure, or “set”, a scene using smart-voice invocation are described.
Domain Restricted Secure Podcasts, Dustin Beutin
Domain Restricted Secure Podcasts, Dustin Beutin
Defensive Publications Series
This disclosure describes techniques to securely provide access to audio files across desktop and mobile devices. The audio files, e.g., audio recordings that are part of a podcast, are converted to multimedia files of similar filesize. The converted files, which can optionally include a graphic related to the audio, are uploaded to secure, view-only cloud storage and configured for access by selected users, e.g., users within a particular domain. Access to the files is provided by a widget that can enable users to play the audio via any desktop or mobile device that can access the cloud storage service.
Proximity-Based Single-Tap Meeting Room Selection, Xavier Lepaul, Josefin Karlsson, Carolina Sartorius, Megan Boundey, Alex Usbergo
Proximity-Based Single-Tap Meeting Room Selection, Xavier Lepaul, Josefin Karlsson, Carolina Sartorius, Megan Boundey, Alex Usbergo
Defensive Publications Series
A meeting participant can join a scheduled or ad-hoc meeting from a conference room by manual entry of a meeting code into meeting room audio or video conferencing equipment. This is a tiresome and error-prone process that requires multiple steps. This disclosure describes techniques that enables users to join a meeting at a nearby conference room using a simple user interface. With user permission, a mobile device of the user determines user proximity to a conference rooms based on signals transmitted by conference rooms. The identity of the available conference room(s) is used to generate and present a user interface …
Machine Learning For Hardware Simulation, N/A
Machine Learning For Hardware Simulation, N/A
Defensive Publications Series
Generally, the present disclosure is directed to improving hardware simulation through machine learning. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict hardware test results based on data extracted from hardware.
Injection Molding Eyepieces For Head Mounted Display, Hongqin Shi, Yeh-Jiun Tung
Injection Molding Eyepieces For Head Mounted Display, Hongqin Shi, Yeh-Jiun Tung
Defensive Publications Series
A technique is provided for manufacturing eyepieces for a head mounted display by forming the eyepiece in two parts: a coated, smaller insert part with a first coating (e.g. chiolite), and a second, larger supporting part with an opening or gap for the coated smaller part. The inset and supporting parts are formed from an eyepiece material via injection molding, and the inset part is then coated with the first coating. The inset is inserted into the gap of the supporting part, and the two parts are cast with an index matching material. The casting forms a front and back …
Contextual Advertising Based On Content Recognition In A Video, Jason Mayes
Contextual Advertising Based On Content Recognition In A Video, Jason Mayes
Defensive Publications Series
Generally, the present disclosure is directed to providing relevant advertisements based on the visual content of a video. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to determine a relevant advertisement and/or a relevant time for the relevant advertisement based on image data taken from a video.
Identifying And Categorizing Utility Power Anomalies, N/A
Identifying And Categorizing Utility Power Anomalies, N/A
Defensive Publications Series
Generally, the present disclosure is directed to predicting utility power anomalies such as, for example, outage events. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict utility power anomalies based on historical and/or current utility power data.
Recognizing Semantic Formatting Information In A Document, N/A
Recognizing Semantic Formatting Information In A Document, N/A
Defensive Publications Series
Generally, the present disclosure is directed to recognizing semantic intent from formatting information. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the intent of an author for a section (e.g., a word, sentence, line, column and/or paragraph) of a document based on the formatting information of that section of the document.
Suggesting Deletion Of Blurry Photos, Charles Lai, Nicolas Miranda
Suggesting Deletion Of Blurry Photos, Charles Lai, Nicolas Miranda
Defensive Publications Series
Generally, the present disclosure is directed to identifying and suggesting deletion of blurry photos. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a blurriness characteristic of an image based on image data. For example, the blurriness characteristic can describe a percentage of the image that is blurry.
Learning Better Font Slicing Strategies From Data, Quan Wang, Yiran Mao
Learning Better Font Slicing Strategies From Data, Quan Wang, Yiran Mao
Defensive Publications Series
Generally, the present disclosure is directed to serving font files in topical subsets. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict topic labels of characters in a font based on a corpus of characters or glyphs.
Using Imagery Of Vegetation And Rooftops To Predict Solar Roof Candidacy, Charles Armstrong
Using Imagery Of Vegetation And Rooftops To Predict Solar Roof Candidacy, Charles Armstrong
Defensive Publications Series
Generally, the present disclosure is directed to predicting whether a property can be conducive to solar energy system installation with minimal adjustment to peripheral vegetation. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict whether a property can be conducive to solar energy installation with minimal adjustment to peripheral vegetation based on imagery and/or publicly available or user-submitted information about the property or area surrounding the property.
Using Imagery To Identify Abandoned Property In Public Spaces, Charles Armstrong
Using Imagery To Identify Abandoned Property In Public Spaces, Charles Armstrong
Defensive Publications Series
Generally, the present disclosure is directed to identifying private property that has been illegally dumped or stored for a prolonged period without use. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict whether an item has been abandoned in a public right-of-way based on imagery of the item and record of public right-of-way.
System Volume Compensating For Environmental Noise, Nick Felker
System Volume Compensating For Environmental Noise, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to an audio system for compensating for ambient environmental noise. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a comfortable volume level based on an intensity of ambient noise.
Using Music To Affect Mood Based On Sentiment Analysis, Nick Felker
Using Music To Affect Mood Based On Sentiment Analysis, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to influencing the mood of a person listening to music while operating a system or device. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to select music to play to influence a user’s mood based on user input into a system or device.
Planning Group Meals Based On Preferences Of Attendees, Nick Felker
Planning Group Meals Based On Preferences Of Attendees, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to determining an optimal place and time for a meeting based on the preferences of the people attending the meeting. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an optimal restaurant and time for a group meal based on personal preferences and/or time availability of members of the group.
Font Optimization Based On User Reading Habits, Nick Felker
Font Optimization Based On User Reading Habits, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to improving accessibility to electronic documents by adjusting font characteristics based on user behavior. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an optimal font to display an electronic document in based on user interaction with the electronic document.
Detecting Interesting Events In A Home Security Camera System, N/A
Detecting Interesting Events In A Home Security Camera System, N/A
Defensive Publications Series
Generally, the present disclosure is directed to a system for predicting whether the subject of a camera needs to be recorded and/or transmitted. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict whether the view of the camera contains a noteworthy change in semantic meaning based on labels describing the semantic meaning of the view.
Machine-Learning For Optimization Of Software Parameters, Etienne J. Membrives
Machine-Learning For Optimization Of Software Parameters, Etienne J. Membrives
Defensive Publications Series
Generally, the present disclosure is directed to optimizing tuning parameters in a computing system and/or software application using machine learning. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an optimal value for tuning parameters based on metrics provided by a developer. As examples, such metrics may be related to an amount of user engagement, latency associated with the application, or efficiency of executing the software application.
Providing Relevant Advertisements Based On Item-Specific Purchase History, Nick Felker
Providing Relevant Advertisements Based On Item-Specific Purchase History, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to providing relevant advertisements to a shopper based on purchase history. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict how receptive a shopper will be to advertisements for a similar item to an item recently purchased based on purchase history patterns for the item.
Machine-Learned Caching Of Datasets, Etienne J. Membrives
Machine-Learned Caching Of Datasets, Etienne J. Membrives
Defensive Publications Series
Generally, the present disclosure is directed to creating and/or modifying a pre-cache for a client device connected to a remote server containing a dataset. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the likelihood a particular piece of data will be used (e.g. opened, edited, saved, etc.) within a time frame based on information about the data, the user’s interaction with the data, and/or the user’s schedule.
Identifying Listed Properties Based On Imagery, Charles Armstrong
Identifying Listed Properties Based On Imagery, Charles Armstrong
Defensive Publications Series
Generally, the present disclosure is directed to identifying properties that are listed for sale or similarly available based on imagery of the properties. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict that a property is listed for sale or similarly available and/or characteristics about the listing based on imagery of the property, including imagery containing listing signage.
Human Movement Detection In Wi-Fi Mesh Networks, Zhifeng Cai, Yu Wen
Human Movement Detection In Wi-Fi Mesh Networks, Zhifeng Cai, Yu Wen
Defensive Publications Series
Wireless networks, including mesh networks, can not only transmit information among various network devices but can also monitor changes or variations in the transmission signals used to communicate the information. Monitoring changes or variations in transmission signals can indicate presence, motion, lack of motion, or other characteristics about the physical space in which the wireless network operates without the need for additional equipment or dedicated devices.
Machine-Learning Predicted User Interfaces, David Huffaker
Machine-Learning Predicted User Interfaces, David Huffaker
Defensive Publications Series
Generally, the present disclosure is directed to customizing user interfaces to a particular user. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the likelihood a user will interact with a user interface element and/or the importance of the content of the user interface element based on user data such as, for example, user interaction with the user interface.
Reinforcement Learning For Fuzzing Testing Techniques, Neil Dhillon, Tanmay Wadhwa
Reinforcement Learning For Fuzzing Testing Techniques, Neil Dhillon, Tanmay Wadhwa
Defensive Publications Series
Generally, the present disclosure is directed to using machine learning to manage a trade-off between exploration and exploitation in a fuzzer system. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict inputs that will cause a system being tested to malfunction or crash based on input data provided to the system and output from the system.
Improving Appeal Of An Advertisement Based On Linguistic Trends, Donny Greenberg
Improving Appeal Of An Advertisement Based On Linguistic Trends, Donny Greenberg
Defensive Publications Series
Generally, the present disclosure is directed to improving appeal of an advertisement based on linguistic trends. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to generate fashionable advertisements based on a candidate advertisement and linguistic trends determined from sample material from one or more advertising platforms.
Configuring Alarm System Based On Time To Arrive At Appointment, Nick Felker
Configuring Alarm System Based On Time To Arrive At Appointment, Nick Felker
Defensive Publications Series
Generally, the present disclosure is directed to setting an alarm to alert a user based on an appointment. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a time to alert a user based on a user’s schedule and location.
Predictive Cryptocurrency Mining And Staking, Thomas Price
Predictive Cryptocurrency Mining And Staking, Thomas Price
Defensive Publications Series
Generally, the present disclosure is directed to determining the validity of a chain within a blockchain system. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the likelihood that a block within a blockchain system will be verified based on characteristics of the block.
Predicting Computing Prices Dynamically Using Machine Learning, Thomas Price
Predicting Computing Prices Dynamically Using Machine Learning, Thomas Price
Defensive Publications Series
Generally, the present disclosure is directed to determining the cheapest datacenter for a computing task to be computed in. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the cost of computing at a datacenter over a time interval based on time data, weather data, and/or grid statistics.