Amazon Technologies, Inc. patent applications on June 20th, 2024
Patent Applications by Amazon Technologies, Inc. on June 20th, 2024
Amazon Technologies, Inc.: 15 patent applications
Amazon Technologies, Inc. has applied for patents in the areas of G06F13/40 (2), G06N5/04 (2), G06F11/14 (2), G06F3/01 (1), H04L67/51 (1) G06F3/011 (1), G06F13/4022 (1), G06F13/4081 (1), G06F16/2358 (1), G06F40/40 (1)
With keywords such as: data, network, server, processing, language, machine, natural, learning, radar, and prompt in patent application abstracts.
Patent Applications by Amazon Technologies, Inc.
Inventor(s): Zheda Li of Mountain View CA (US) for amazon technologies, inc., Morris Yuanhsiang Hsu of Mountain View CA (US) for amazon technologies, inc., Vivek Yenamandra of Santa Clara CA (US) for amazon technologies, inc., Aditya V. Padaki of San Jose CA (US) for amazon technologies, inc., Raghunandan M Rao of Santa Clara CA (US) for amazon technologies, inc., Abhishek Sanaka of San Jose CA (US) for amazon technologies, inc., Rohit Kumar of San Jose CA (US) for amazon technologies, inc., Sai Prashanth Chinnapalli of Dublin CA (US) for amazon technologies, inc.
IPC Code(s): G06F3/01, G01S13/04, H04N7/025
CPC Code(s): G06F3/011
Abstract: techniques for a dynamic radar mode modulation feature are described herein. a computer system associated with a device may implement a first radar configuration for a radar sensor. the first radar configuration may correspond to a first mode and comprise a first frame per second rate and a first difference threshold. the computer system may receive first data from the radar sensor in the first radar configuration. the computer system may determine a presence of an object within a field of view of the radar sensor based on the first data and the first difference threshold. the computer system may instruct the device to turn on based on determining the presence of the user. the radar sensor may be instructed to implement a second radar configuration associated with a second mode.
Inventor(s): Jiandong Huang of San Jose CA (US) for amazon technologies, inc., Frank Paterra of Oakton VA (US) for amazon technologies, inc., Ryan L. Sanders of Pike Road AL (US) for amazon technologies, inc.
IPC Code(s): G06F13/40, G06F13/38
CPC Code(s): G06F13/4022
Abstract: attachment of a pluggable module to an externally-accessible slot of a base unit of a server is detected. the module is configured to execute a first network function of a radio-based communication network. in response to a determination that the module satisfies a security criterion, a second network function is launched. the second network function performs one or more computations on output of the first network function. the output of the first network function is generated at the module in response to a message from a user equipment device of a radio-based communication network.
Inventor(s): Frank Paterra of Oakton VA (US) for amazon technologies, inc., Timothy Robert Hamilton of Arlington VA (US) for amazon technologies, inc., Justin Knowles of Arlington VA (US) for amazon technologies, inc., Aaron Michael Brown of Washington DC (US) for amazon technologies, inc.
IPC Code(s): G06F13/40, G06F9/455, H04L9/32
CPC Code(s): G06F13/4081
Abstract: the attachment of a pluggable hardware module to a server via a slot on an enclosure of the server is detected. in response to determining, using metadata stored at the server, that the module is in a group of approved modules, a first security artifact is obtained from the module. in response to validating the first security artifact using a second security artifact which is part of the metadata, a program running within a virtual machine launched at the server is enabled to access application data of an application from the module.
Inventor(s): James Christopher Sorenson, III of Madison WI (US) for amazon technologies, inc., Hao He of Bellevue WA (US) for amazon technologies, inc., Nicholas Gordon of Seattle WA (US) for amazon technologies, inc., Mrithyunjaya Kumar Annapragada of Concord MA (US) for amazon technologies, inc.
IPC Code(s): G06F16/23, G06F11/14, G06F16/11, G06F16/21, G06F21/60
CPC Code(s): G06F16/2358
Abstract: time and value ordering may be applied for items stored in data backups. a change log that persists changes to a data set may be updated with changes and used to update an in-memory table for the data set, which describes changes to items up to a current time. an event may be detected to seal the in-memory table from subsequent updates and a persistent data object that orders the items in the in-memory according to both keys of the respective items and the respective time values of the items, as stored in the change log, may be generated and stored as part of a backup for the data set.
Inventor(s): Sheng Zha of New York NY (US) for amazon technologies, inc., Miguel Ballesteros Martinez of New York NY (US) for amazon technologies, inc., Yassine Benajiba of Briarcliff Manor NY (US) for amazon technologies, inc., Cole Hawkins of New York NY (US) for amazon technologies, inc., Aditya Rawal of Mountain View CA (US) for amazon technologies, inc., Dhananjay Ram of Kirkland WA (US) for amazon technologies, inc., Min Rong Samson Tan of Mountain View CA (US) for amazon technologies, inc., Abhinav Goyal of Snohomish WA (US) for amazon technologies, inc., Brant Swidler of Kauneonga Lake NY (US) for amazon technologies, inc.
IPC Code(s): G06F40/40, G06F40/279
CPC Code(s): G06F40/40
Abstract: prompt discovery is performed for identifying prompts to natural language processing machine learning models. a request to determine a prompt for a natural language processing task performed by a pre-trained natural language processing machine learning model may be received. a task classification for the natural language processing task may be determined and candidate prompts for the natural language processing prompt task collection selected. respective prompt results for the candidate prompts are evaluated to generate a prompt recommendation for the natural language processing task.
Inventor(s): Sheng Zha of New York NY (US) for amazon technologies, inc., Miguel Ballesteros Martinez of New York NY (US) for amazon technologies, inc., Yassine Benajiba of Briarcliff Manor NY (US) for amazon technologies, inc., Cole Hawkins of New York NY (US) for amazon technologies, inc., Aditya Rawal of Mountain View CA (US) for amazon technologies, inc., Dhananjay Ram of Kirkland WA (US) for amazon technologies, inc., Min Rong Samson Tan of Mountain View CA (US) for amazon technologies, inc., Vittorio Castelli of Croton-on-Hudson NY (US) for amazon technologies, inc.
IPC Code(s): G06F40/56, G06N5/04
CPC Code(s): G06F40/56
Abstract: prompt development techniques are implemented for tuning natural language processing machine learning models using selected prompts from a prompt task collection. a prompt development system may support requests to further adapt a pre-trained natural language processing machine learning model to tune the pre-trained natural language processing machine learning model for use with a selected prompt. evaluation of the tuned natural language processing machine learning model may be performed and provided as a result.
Inventor(s): Kevin LOTZ of Kiel (DE) for amazon technologies, inc., Bruno DUTERTRE of Mountain View CA (US) for amazon technologies, inc., John Byron COOK of Brooklyn NY (US) for amazon technologies, inc., Amit GOEL of Portland OR (US) for amazon technologies, inc., Robert JONES of Beaverton OR (US) for amazon technologies, inc., Benjamin KIESL-REITER of Munich (DE) for amazon technologies, inc., Soon Ho KONG of Cupertino CA (US) for amazon technologies, inc., Rupak MAJUMDAR of Krickenbach (DE) for amazon technologies, inc.
IPC Code(s): G06N5/01, G06N5/04
CPC Code(s): G06N5/013
Abstract: techniques are described for providing a sat-based solver for a quantifier-free theory of strings and bit vectors. the solver can be used by an automated reasoning service of a cloud provider network to analyze policies and the consequences of policies. the solver reduces an input formula to a boolean satisfiability problem by encoding the input formula into an equisatisfiable propositional formula, where the satisfiability of the equisatisfiable propositional formula is determined by a sat solver. rather than using a traditional dpll(t) style algorithm, the solver described herein bounds the length of variables in an input formula and reduces the problem to a single formula, which can then be solved using incremental sat solving. the solver can be used independently or as part of a portfolio of solvers used to determine the satisfiability or unsatisfiability of certain formula corresponding, e.g., to questions about users' policies within a cloud provider network.
Inventor(s): Vinayshekhar Bannihatti Kumar of Santa Clara CA (US) for amazon technologies, inc., Rashmi Gangadharaiah of San Jose CA (US) for amazon technologies, inc., Dan Roth of Philadelphia PA (US) for amazon technologies, inc.
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: methods and systems are disclosed for a machine learning (ml) model training system that can remove the influence of specific data points in an efficient way. an ml training system can train multiple instances of a machine learning model on disjoint shards of data. upon receiving a request to remove a specific data point, the ml training system can expunge the data point from its corresponding shard and only retrain the model instance for that specific shard. each shard can be further divided into data slices, with each slice containing a portion of the data from the shard. during the training of each instance of the machine learning model, the ml training system can save model checkpoints after completion of training for each slice. upon receiving a removal request, the related data point is removed from its respective slice, and the relevant model instance can be retrained starting from the last checkpoint before that slice had been previously used for training.
20240202809.OUTFIT SIMULATION USING LAYER MASK_simplified_abstract_(amazon technologies, inc.)
Inventor(s): Benjamin James BIGGS of San Francisco CA (US) for amazon technologies, inc., Philip PINETTE of Seattle WA (US) for amazon technologies, inc., Charu KOTHARI of San Jose CA (US) for amazon technologies, inc., Caitlin Isaac CAGAMPAN of Pasadena CA (US) for amazon technologies, inc., Gerard Guy MEDIONI of Los Angeles CA (US) for amazon technologies, inc., Achal Dushyant DAVE of San Francisco CA (US) for amazon technologies, inc., Scott Chenghui SUN of Milpitas CA (US) for amazon technologies, inc.
IPC Code(s): G06Q30/0601
CPC Code(s): G06Q30/0643
Abstract: a method includes generating a virtual model of a human body based at least in part on a selected image of the human body and generating a segment of an article of clothing based at least in part on a selected image of the article of clothing. the method also includes generating a layer mask indicating whether a plurality of output pixels of an output image should be produced according to the image of the human body, the image of the shirt, or the image of the pair of pants and producing the plurality of output pixels of the output image according to the layer mask. the output image shows the article of clothing on the human body in the selected image of the human body.
Inventor(s): Austin Chang Ming Liu of Burnaby (CA) for amazon technologies, inc., Gonzalo Alvarez Barrio of Seattle WA (US) for amazon technologies, inc., Gregory James Wade of Coquitlam (CA) for amazon technologies, inc., Harsh Agarwal of Seattle WA (US) for amazon technologies, inc., Sam Anthony Sullivan of Lions Bay (CA) for amazon technologies, inc., Chieh Chien of Bellevue WA (US) for amazon technologies, inc., Cameron L Chinn of Seattle WA (US) for amazon technologies, inc.
IPC Code(s): G10L15/22, G10L15/06
CPC Code(s): G10L15/22
Abstract: systems and methods for enterprise type pretrained models for voice interfaces include the generation and validation of enterprise type pretrained models utilizing input associated with the enterprise type at issue. once generated and validated, when a user command is received, the speech processing system may check to determine if a customized model is available, and if not, may query the enterprise type model to provide a response to the user command.
Inventor(s): Piyush Mathur of Sammamish WA (US) for amazon technologies, inc., Oleg Albegov of Sammamish WA (US) for amazon technologies, inc., Ashish Kumar of Seattle WA (US) for amazon technologies, inc., Joseph Elmar Magerramov of Bellevue WA (US) for amazon technologies, inc., Nishant Mehta of Snoqualmie WA (US) for amazon technologies, inc.
IPC Code(s): H04L12/46, H04L9/40
CPC Code(s): H04L12/4675
Abstract: techniques for resource sharing between cloud-hosted virtual networks are described. a first network address of a first virtual network is associated with a resource connected to a second virtual network, the first and second virtual networks within a cloud provider network. a service of the cloud provider network receives a message destined for the first network address. the service translates the first network address to a second network address of the resource in the second virtual private network. the service sends the message to the resource at the second network address in the second virtual network.
Inventor(s): Timothy Andrew Rath of Des Moines WA (US) for amazon technologies, inc., Jakub Kulesza of Bellevue WA (US) for amazon technologies, inc., David Alan Lutz of Renton WA (US) for amazon technologies, inc.
IPC Code(s): H04L41/0668, G06F3/06, G06F11/14, G06F11/16, G06F11/20, H04L67/1097, H04L67/51
CPC Code(s): H04L41/0668
Abstract: a system that implements a data storage service may store data on behalf of storage service clients. the system may maintain data in multiple replicas of various partitions that are stored on respective computing nodes in the system. the system may employ a single master failover protocol, usable when a replica attempts to become the master replica for a replica group of which it is a member. attempting to become the master replica may include acquiring a lock associated with the replica group, and gathering state information from the other replicas in the group. the state information may indicate whether another replica supports the attempt (in which case it is included in a failover quorum) or stores more recent data or metadata than the replica attempting to become the master (in which case synchronization may be required). if the failover quorum includes enough replicas, the replica may become the master.
Inventor(s): Frank Paterra of Oakton VA (US) for amazon technologies, inc.
IPC Code(s): H04W12/30, H04L41/0803, H04W12/037, H04W12/086
CPC Code(s): H04W12/35
Abstract: during a time period in which a server is in a locked state, such that execution of an application at the server is not permitted, a reception of a radio message at the server is detected. in response to determining that the radio message satisfies an unlocking criterion associated with the server, the server is caused to exit the locked state, and execution of the application is initiated at the server.
Inventor(s): Muhammed Faruk Gencel of Poway CA (US) for amazon technologies, inc., Basak Oyman of Mountain View CA (US) for amazon technologies, inc., Ravi Ichapurapu of Morgan Hill CA (US) for amazon technologies, inc.
IPC Code(s): H04W24/08, H04L1/00, H04L43/0823
CPC Code(s): H04W24/08
Abstract: in various examples, systems and methods of wireless communication link adaptation are described. in some examples, first data may be determined for a first gateway device, the first data representing a plurality of received signal strength (rss) values of a first signal received from a first end node device. second data representing an interference associated with the first signal may be determined. at least one of a first packet error rate or a first packet success rate may be determined based at least in part on the first data and the second data. a first modulation coding scheme (mcs) associated with at least one of the first packet error rate or the first packet success rate may be determined. third data may be sent to the first end node, the third data instructing the first end node device to use the first mcs for communication with the first gateway device.
Inventor(s): Manjari Asawa of Cupertino CA (US) for amazon technologies, inc., Merritt Riggs Goodman of Alpharetta GA (US) for amazon technologies, inc., Ammar Latif of Jupiter FL (US) for amazon technologies, inc.
IPC Code(s): H04W28/20
CPC Code(s): H04W28/20
Abstract: disclosed are various embodiments for dynamic bandwidth allocations for cell site transport links on a radio-based network. in one embodiment, a predicted bandwidth usage at a cell site of a radio-based network is determined. a bandwidth allocation on a data link between the cell site and a data center is dynamically adjusted based at least in part on the predicted bandwidth usage.
Amazon Technologies, Inc. patent applications on June 20th, 2024
- Amazon Technologies, Inc.
- G06F3/01
- G01S13/04
- H04N7/025
- CPC G06F3/011
- Amazon technologies, inc.
- G06F13/40
- G06F13/38
- CPC G06F13/4022
- G06F9/455
- H04L9/32
- CPC G06F13/4081
- G06F16/23
- G06F11/14
- G06F16/11
- G06F16/21
- G06F21/60
- CPC G06F16/2358
- G06F40/40
- G06F40/279
- CPC G06F40/40
- G06F40/56
- G06N5/04
- CPC G06F40/56
- G06N5/01
- CPC G06N5/013
- G06N20/00
- CPC G06N20/00
- G06Q30/0601
- CPC G06Q30/0643
- G10L15/22
- G10L15/06
- CPC G10L15/22
- H04L12/46
- H04L9/40
- CPC H04L12/4675
- H04L41/0668
- G06F3/06
- G06F11/16
- G06F11/20
- H04L67/1097
- H04L67/51
- CPC H04L41/0668
- H04W12/30
- H04L41/0803
- H04W12/037
- H04W12/086
- CPC H04W12/35
- H04W24/08
- H04L1/00
- H04L43/0823
- CPC H04W24/08
- H04W28/20
- CPC H04W28/20
