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    'Adjustable Parameters For Autonomous Cleaning Robots' in Patent Application App roval Process (USPTO 20240225400)

    140-145页
    查看更多>>摘要:The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Cleaning robots include mobile robots that auto nomously perform cleaning tasks within anenvironment, e.g., a home. Many kinds of cleaning robots are autonomous to some degree and in differentways. The clea ning robots include a controller that is configured to autonomously navigate the cleaningrobot about the environment such that the cleaning robot can ingest de bris as it moves.”

    Patent Issued for System and method for order processing (USPTO 12033113)

    145-149页
    查看更多>>摘要:From the background information supplied by the inventors, news correspondents o btained the followingquote: “Contemporary storage facilities handle a large num ber of inventory items on a daily basis. Theinventory items may be moved out of the storage facility for fulfilment of an order or brought inside thestorage f acility for replenishment of inventory items. Examples of such inventory items m ay includegroceries, apparels, cosmetics, electronic appliances, or the like. T hroughputs of such storage facilitiesmay have a direct bearing on various busin ess metrics such as time taken to complete orders, total numberof orders comple ted within a time duration, customer satisfaction, or the like. Hence, it is nec essary tooptimize the operations performed at these storage facilities to reali ze a maximum throughput.

    Patent Issued for Enabling secure auto-filling of information (USPTO 12032901)

    149-152页
    查看更多>>摘要:News editors obtained the following quote from the background information suppli ed by the inventors:“A user device may rely on a network to communicate informa tion and/or to communicate messages withanother user device. Such information a nd/or messages may include private information and/or sensitivedata associated with the user device. The communication over the network may be vulnerable as be ingsusceptible to a cybercrime, through which a malicious entity may attempt to steal, alter, disable, expose,or destroy the information through unauthorized access to the communicating user devices. A cybercrimemay include, for example, a malware attack, a phishing attack, a ransomware attack, a virus attack, etc.As a result, cyber security measures may be used to prevent occurrence of the cy bercrime and/or tomitigate risks associated with the cybercrime.”

    Patent Issued for System and method for a machine learning service (USPTO 120332 16)

    152-155页
    查看更多>>摘要:“In service industries, including financial services, it is important to obtain, store and manage knowledgerelated to prospective clients, which are referred t o as “leads”. One objective of the lead managementprocess is to match a prospec tive lead with the most appropriate recipient (advisor, salesperson, etc.)in an organization. Traditionally, lead management is handled by the individuals resp onsible for clientprospecting. These individuals typically obtain information c oncerning leads by buying clients lists, receivingreferrals, and creating web p ages that collect information. In the case of large organizations, leadscan als o be assigned to sales personnel by assignment from a central process. While the se processes havesome effectiveness, the matching between the lead and advisor is based on fairly generalized rules and/orhuman-biased decisions that often re sult in sub-optimal or unsuccessful lead matching.

    Patent Issued for Automated processing of multiple prediction generation includi ng model tuning (USPTO 12033041)

    155-159页
    查看更多>>摘要:The assignee for this patent, patent number 12033041, is Databricks Inc. (San Fr ancisco, California,United States).Reporters obtained the following quote from the background information supplied by the inventors:“A system for big data processing comprises a system for deplo yments of applications, configurations,one or more datasets, and model(s) used in connection with analyzing the data. Models are generallydeployed in services and applications, such as web-based services, in connection with providing esti matedoutcomes, etc. A model is generated or trained based on relationships amon g different input data. Atscale, numerous models are used to provide prediction s with different aspects of a same dataset, andeach model uses numerous relatio nships among data, and the development of such relationships is veryresource in tensive. This creates a problem for training the numerous models corresponding t o a datasetin an efficient manner and tuning the models to ensure that the mode ls continue to provide effectivepredictions.”

    Patent Issued for Robotic vacuum cleaner with dirt enclosing member and method o f using the same (USPTO 12029379)

    159-161页
    查看更多>>摘要:The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Various types of robotic or autonomous surface cleaning apparatus are known. A roboticvacuum cleaner may have a docking statio n that charges the robotic vacuum cleaner when the roboticvacuum cleaner is con nected or docked to the docking station. Also, a docking station may have a suction motor to draw dirt from a dirt storage chamber in a robotic vacuum cleaner a nd an air treatmentmember to remove entrained dirt from the air drawn into the docking station for the dirt storage chamberof a robotic vacuum cleaner.”

    Patent Issued for Methods and system for passive authentication through user att ributes (USPTO 12033127)

    161-163页
    查看更多>>摘要:Reporters obtained the following quote from the background information supplied by the inventors:“Electronic authentication is commonplace in today’s highly-co nnected society, especially in view of thefact that more and more individuals a re conducting financial and personal transaction electronically.“Authentication can come in a variety of forms, such as single-factor authentica tion and multifactorauthentication. Authentication can be done with different d egrees of perceived strength. For example,biometric authentication is typically believed to be a stronger form of authentication than an identifier andpasswor d combination.

    'Dynamic Tuning Of Larger Pages During Runtime' in Patent Application Approval P rocess (USPTO 20240232098)

    163-167页
    查看更多>>摘要:The following quote was obtained by the news editors from the background informa tion supplied by theinventors: “Aspects of the present invention relate general ly to heap memory management during runtimeof applications and, more particular ly, to dynamic use of larger pages during runtime of applications.

    'Method for Training Large Language Models to Perform Query Intent Classificatio n' in Patent Application Approval Process (USPTO 20240232637)

    167-171页
    查看更多>>摘要:The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Machine learning is a field of computer science that includes the building and training (e.g.,via application of one or more l earning algorithms) of analytical models that are capable of making usefulpredi ctions or inferences on the basis of input data. Machine learning is based on th e idea that systemscan learn from data, identify patterns, and make decisions w ith minimal human intervention.

    Researchers Submit Patent Application, 'Detecting and Correcting Anomalies in Co mputer-Based Reasoning Systems', for Approval (USPTO 20240232660)

    171-174页
    查看更多>>摘要:News editors obtained the following quote from the background information suppli ed by the inventors:“Many systems are controlled by machine learning systems. A common issue with such systems, however,is that when there is an anomalous out come, such as a system failure, unexpected action, etc., there isno way to know why the system acted in the manner in which it did. For example, in a machine l earningsystem to detect letters or numbers in images, tens or hundreds of thous ands of training data (e.g.,pictures along with coded letters or numbers) might be used to train the system. The system can then beused to act on incoming ima ges to find letters and numbers in those images. At times, those outcomesmight be anomalous. For example, the system may “find” letters or numbers that are not actually in theimages, find incorrect letters or numbers, or fail to find lett ers or numbers in the images.