Integrated hardware-based voice-activated ai system for versatile task execution

Abstract

Described herein are examples of hardware-based voice-activated artificial intelligence (AI) systems for versatile task execution which include an input interface, a processing module, a control circuit, a communication module, and an audio device. The input interface may include a microphone configured to receive spoken language input provided by a user in the form of an audio signal and a converter configured to convert the captured audio signal to a digital signal. The processing module may include a central processing unit (CPU) and memory, configured to process the received spoken language input by executing a machine learning algorithm or a natural language processing routine stored in the memory. The control circuit may generate a response or action based on the spoken language input. The communication module may be communicatively linked with an external system. The audio device may be configured to provide a voice-based response or audio feedback to the user.

Description

INTEGRATED HARDWARE-BASED VOICE-ACTIVATED Al SYSTEM FOR VERSATILE TASK EXECUTIONCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims the benefit of U.S. Non- Provisional Patent Application No. 18 / 492,703 entitled “Integrated Hardware- Based Voice- Activated Ai System For Versatile Task Execution”, filed on October 23, 2023. The entire contents of the above-listed application are hereby incorporated by reference for all purposes. The entire contents of the above-listed application are hereby incorporated by reference for all purposes.BACKGROUND

[0002] In the ever-evolving landscape of technology, the field of artificial intelligence (Al) systems has emerged as a transformative force. At its core, this field revolves around systems designed to understand and respond to commands provided by users. While these Al systems have made significant strides, they predominantly rely on textual or touch-based input methods. This fundamental limitation confines their versatility and usability, leaving a substantial gap in the realm of natural and intuitive human-computer interaction. In particular, conventional systems do not adequately support voice commands, which has led to a growing need for innovative solutions in this specific field.

[0003] The demand for voice-activated Al systems capable of comprehending and executing spoken language commands is more pressing than ever before. As technology continues to infiltrate every aspect of our lives, users are increasingly seeking voice-based interfaces that can provide seamless, efficient, and context-aware interactions. However, the conventional systems in this field, which rely on textual or touch-based inputs, often struggle to meet these expectations. The limitations of these systems have become evident, particularly in scenarios where voice commands offer significant advantages, such as hands-free operation, accessibility for individuals with mobility impairments, and enhanced user engagement. These challenges underscore the critical need for innovative improvements promising to bridge the gap between conventional systems and the growing demand for sophisticated voice-activated Al technology.BRIEF DESCRIPTION OF THE DRAWINGS

[0004] The present description will be understood more fully when viewed in conjunction with the accompanying drawings of various examples of integrated hardware-based voice-activated Al systems for versatile task execution. The description is not meant to limit the integrated hardwarebased voice-activated Al system for versatile task execution to the specific examples. Rather, the specific examples depicted and described are provided for explanation and understanding ofintegrated hardware-based voice-activated Al systems for versatile task execution. Throughout the description the drawings may be referred to as drawings, figures, and / or FIGs.

[0005] FIG. 1 illustrates an integrated hardware-based voice-activated Al system for versatile task execution, according to an embodiment;

[0006] FIG. 2 illustrates a device schematic for various devices used in the integrated hardwarebased voice-activated Al system, according to an embodiment;

[0007] FIG. 3 illustrates a device schematic for various devices used in the integrated hardwarebased voice-activated Al system, according to an embodiment;

[0008] FIGs. 4A to 4F illustrate various aspects of user interaction throughout the registration and login processes, stock and cryptocurrency trading, securities management, and access to technology- related information.

[0009] FIG. 5 is a flow diagram of a method for versatile task execution using an integrated hardware-based voice-activated Al system.DETAILED DESCRIPTION

[0010] An integrated hardware- based voice-activated Al system for versatile task execution as disclosed herein will become better understood through a review of the following detailed description in conjunction with the figures. The detailed description and figures provide merely examples of the various embodiments of voice-activated Al systems for versatile task execution. Many variations are contemplated for different applications and design considerations; however, for the sake of brevity and clarity, all the contemplated variations may not be individually described in the following detailed description. Those skilled in the art will understand how the disclosed examples may be varied, modified, and altered and not depart in substance from the scope of the examples described herein.

[0011] A conventional voice-activated Al system may include a combination of hardware and software components primarily designed to execute specific tasks or commands triggered by voice inputs. However, these conventional systems are not typically equipped to engage in meaningful spoken language interactions with users. Instead, they often rely on predetermined commands or keywords to trigger predefined actions. This limited functionality restricts their ability to understand and respond to the diverse and natural language inputs that users may provide.

[0012] The limitations of these conventional systems give rise to various challenges and missed opportunities. One significant issue is their inability to handle complex, context- rich spoken language inputs effectively. Users may struggle to interact naturally with such systems, leading to frustration and reduced user engagement. Additionally, these systems often lack the capability toauthenticate users securely through voice or other biometric data, which can compromise user privacy and system security.

[0013] Implementations of the disclosed hardware-based voice-activated Al system may address some or all of the problems described above. This system may be configured to receive and process spoken language input from users and enable more natural and context-aware interactions. By incorporating advanced machine learning algorithms and natural language processing routines, the system can identify user intents, extract relevant entities, and determine context, thereby offering a more comprehensive understanding of user commands. Furthermore, the system may include a user authentication module that utilizes biometric data for security purposes.

[0014] The disclosed embodiment fundamentally transforms voice-activated Al systems by enabling them to engage in meaningful spoken language interactions. By utilizing machine learning and natural language processing, the system may accurately interpret complex voice inputs and thus facilitate smoother and more intuitive interactions. Additionally, the incorporation of user authentication and: data security features may provide a secure user experience.

[0015] FIG. 1 illustrates a voice-activated Al system 100, according to an embodiment. The voice- activated Al system 100 includes internal and external data resources for versatile task execution. The voice-activated Al system 100 may result in reduced memory allocation at client devices and may conserve memory resources for application servers.

[0016] The voice-activated Al system 100 may include a cloud-based data management system 102 and a user device 104. The cloud-based data management system 102 may include an application server 106, a database 108, and a data server 110, The user device 104 may include one or more devices associated with user profiles of the voice-activated Al system 100, such as a smartphone 112 and / or a personal computer 114. The voice-activated Al system 100 may include external resources such as an external application server 116 and / or an external database 118. The various elements of the voice-activated Al system 100 may communicate via various communication links 120. An external resource may generally be considered a data resource owned and / or operated by an entity other than an entity that utilizes the cloud-based data management system 102 and / or the user device 104.

[0017] The voice-activated Al system 100 may be web-based. The user device 104 may access the cloud-based data management system 102 via an online portal set up and / or managed by the application server 106. The voice-activated Al system 100 may be implemented using a public internet. The voice-activated Al system 100 may be implemented using a private intranet. Elements of the voice-activated Al system 100, such as the database 108 and / or the data server 110, may bephysically housed at a location remote from an entity that owns and / or operates the voice-activated Al system 100. For example, various elements of the voice-activated Al system 100 may be physically housed at a public service provider such as a web services provider. Elements of the voice-activated Al system 100 may be physically housed at a private location, such as at a location occupied by the entity that owns and / or operates the voice-activated Al system 100.

[0018] The communication links 120 may be direct or indirect. A direct link may include a link between two devices where information is communicated from one device to the other without passing through an intermediary. For example, the direct link may include a Bluetooth™ connection, a ZigbeeRconnection, a Wifi Direct™ connection, a near-field communications (NFC) connection, an infrared connection, a wired universal serial bus (USB) connection, an ethernet cable connection, a fiber-optic connection, a firewire connection, a microwire connection, and so forth. In another example, the direct link may include a cable on a bus network. '‘Direct,'’ when used regarding the communication links 120, may refer to any of the aforementioned direct communication links.

[0019] An indirect link may include a link between two or more devices where data may pass through an intermediary, such as a router, before being received by an intended recipient of the data. For example, the indirect link may include a wireless fidelity (WiFi) connection where data is passed through a WiFi router, a cellular network connection where data is passed through a cellular network router, a wired network connection where devices are interconnected through hubs and / or routers, and so forth. The cellular network connection may be implemented according to one or more cellular network standards, including the global system for mobile communications (GSM) standard, a code division multiple access (CDMA) standard such as the universal mobile telecommunications standard, an orthogonal frequency division multiple access (OFDMA) standard such as the long term evolution ( LTE) standard, and so forth. “Indirect,” when used regarding the communication links 120, may refer to any of the aforementioned indirect communication links.

[0020] FIG. 2 illustrates a device schematic 200 for various devices used in the voice-activated Al system 100, according to an embodiment. A server device 200a may moderate data communicated to a client device 200b based on data permissions to mimimize memory resource allocation at the client device 200b.

[0021] The server device 200a may include a communication device 202, a memory device 204, and a processing device 206. The processing device 206 may include a data processing module 206a and a data permissions module 206b, where module refers to specific programming that governs how data is handled by the processing device 206. The client device 200b may include a communication device 208, a memory device 210, a processing device 212, and a user interface 214. Varioushardware elements within the server device 200a and / or the client device 200b may be interconnected via a system bus 216. The system bus 216 may be and / or include a control bus, a data bus, and address bus, and so forth. The communication device 202 of the server device 200a may communicate with the communication device 208 of the client device 200b.

[0022] The data processing module 206a may handle inputs from the client device 200a. The data processing module 206a may cause data to be written and stored in the memory device 204 based on the inputs from the client device 200b. The data processing module 206a may rectrieve data stored in the memory device 204 and ouput the data to the client device 200a via the communication device 202. The data permissions module 206b may determine, based on permissions data stored in the memory device, what data to output to the client device 200b and what format to output the data in (e.g. as a static variable, as a dynamic variable, and so forth). For example, a variable that is disabled for a particular" user profile may be output as static. When the variable is enabled for the particular user profile, the variable may be output as dynamic.

[0023] The server device 200a may be representative of the cloud-based data management system 102. The server device 200a may be representative of the application server 106. The server device 200a may be representative of the data server 110. The server device 200a may be representative of the external application server 116. The memory device 204 may be representative of the database 108 and: the processing device 206 may be representative of the data server 110. The memory device 204 may be representative of the external database 118 and the processing device 206 may be representative of the external application server 116. For example, the database 108 and / or the external database 118 may be implemented as a block of memory in the memory device 204. The memory device 204 may further store instructions that, when executed by the processing device 206, perform various functions with the data stored in the database 108 and / or the external database 118.

[0024] Similarly, the client device 200b may be representative of the user device 104. The client device 200b may be representative of the smartphone 112. The client device 200b may be representative of the personal computer 114. The memory device 210 may store application instructions that, when executed by the processing device 212, cause the client device 200b to perform various functions associated with the instructions, such as retrieving data, processing data, receiving input, processing input, transmitting data, and so forth.

[0025] As stated above, the server device 200a and the client device 200b may be representative of various devices of the voice-activated Al system 100. Various of the elements of the voice-activated Al system 100 may include data storage and / or processing capabilities. Such capabilities may be rendered by various electronics for processing and / or storing electronic signals. One or more of thedevices in the voice-activated Al system 100 may include a processing device. For example, the cloud-based data management system 102, the user device 104, the smartphone 112, the personal computer 114, the external application server 116, and / or the external database 118 may include a processing device. One or more of the devices in the voice-activated Al system 100 may include a memory device. For example, the cloud-based data management system 102, the user device 104, the smartphone 112, the personal computer 114, the external application server 116, and / or the external database 118 may include the memory device.

[0026] The processing device may have volatile and / or persistent memory. The memory device may have volatile and / or persistent memory. The processing device may have volatile memory and the memory device may have persistent memory. Memory in the processing device may be allocated dynamically according to variables, variable states, static objects, and permissions associated with objects and variables in the voice-activated Al system 100. Such memory allocation may be based on instructions stored in the memory device. Memory resources at a specific device may be conserved relative to other systems that do not associate variables and other object with permission data for the specific device.

[0027] The processing device may generate an output based on an input. For example, the processing device may receive an electronic and / or digital signal. The processing device may read the signal and perform one or more tasks with the signal, such as performing various functions with data in response to input received by the processing device. The processing device may read from the memory device information needed to perform the functions. For example, the processing device may update a variable from static to dynamic based on a received input and a rule stored as data on the memory device. The processing device may send an output signal to the memory device, and the memory device may store data according to the signal output by the processing device.

[0028] The processing device may be and / or include a processor, a microprocessor, a computer processing unit (CPU), a graphics processing unit (GPU), a neural processing unit, a physics processing unit, a digital signal processor, an image signal processor, a synergistic processing element, a field-programmable gate array (FPGA), a sound chip, a multi-core processor, and so forth. As used herein, “processor,” “processing component,” “processing device,” and / or “processing unit” may be used generically to refer to any or all of the aforementioned specific devices, elements, and / or features of the processing device.

[0029] The memory device may be and / or include a computer processing unit register, a cache memory, a magnetic disk, an optical disk, a solid-state drive, and so forth. The memory device may be configured with random access memory (RAM), read-only memory (ROM), static RAM,dynamic RAM, masked ROM, programmable ROM, erasable and programmable ROM, electrically erasable and programmable ROM, and so forth. As used herein, “memory,” “memory component,” “memory device / ’ and / or “memory unit” may be used generically to refer to any or all of the aforementioned specific devices, elements, and / or features of the memory device.

[0030] Various of the devices in the voice-activated Al system 100 may include data communication capabilities. Such capabilities may be rendered by various electronics for transmitting and / or receiving electronic and / or electromagnetic signals. One or more of the devices in the voice- activated Al system 100 may include a communication device, e.g., the communication device 202 and / or the communication device 208. For example, the cloud-based data management system 102, the user device 104, the smartphone 112, the personal computer 114, the application server 116, and / or the external database 118 may include a communication device.

[0031] The communication device may include, for example, a networking chip, one or more antennas, and / or one or more communication ports. The communication device may generate radio frequency (RF) signals and transmit the RF signals via one or more of the antennas. The communication device may receive and / or translate the RF signals. The communication device may transceive the RF signals. The RF signals may be broadcast and / or received by the antennas.

[0032] The communication device may generate electronic signals and transmit the RF signals via one or more of the communication ports. The communication device may receive the RF signals from one or more of the communication ports. The electronic signals may be transmitted to and / or from a communication hardline by the communication ports. The communication device may generate optical signals and transmit the optical signals to one or more of the communication ports. The communication device may receive the optical signals and / or may generate one or more digital signals based on the optical signals. The optical signals may be transmitted to and / or received from a communication hardline by the communication port, and / or the optical signals may be transmitted and / or received across open space by the networking device.

[0033] The communication device may include hardware and / or software for generating and communicating signals over a direct and / or indirect network communication link. For example, the communication component may include a USB port and a USB wire, and / or an RF antenna with Bluetooth™ programming installed on a processor, such as the processing component, coupled to the antenna. In another example, the communication component may include an RF antenna and programming installed on a processor, such as the processing device, for communicating over a Wifi and / or cellular network. As used herein, “communication device” “communication component,”and / or “communication unit” may be used generically herein to refer to any or all of the aforementioned elements and / or features of the communication component.

[0034] Various of the elements in the voice-activated Al system 100 may be referred to as a “server.”' Such elements may include a sen er device. The server device may include a physical server and / or a virtual server. For example, the sewer device may include one or more bare-metal servers. The bare-metal servers may be single-tenant servers or multiple tenant servers. In another example, the server device may include a bare metal server partitioned into two or more virtual sewers. The virtual servers may include separate operating systems and / or applications from each other. In yet another example, the server device may include a virtual server distributed on a cluster of networked physical servers. The virtual servers may include an operating system and / or one or more applications installed on the virtual server and distributed across the cluster of networked physical servers. In yet another example, the server device may include more than one virtual server distributed across a cluster of networked physical servers.

[0035] The term server may refer to functionality of a device and / or an application operating on a device. For example, an application server may be programming instantiated in an operating system installed on a memory device and run by a processing device. The application server may include instructions for receiving, retrieving, storing, outputting, and / or processing data. A processing server may be programming instantiated in an operating system that receives data, applies rules to data, makes inferences about the data, and so forth. Servers referred to separately herein, such as an application server, a processing server, a collaboration server, a scheduling server, and so forth may be instantiated in the same operating system and / or on the same server device. Separate servers may be instantiated in the same application or in different applications.

[0036] Various aspects of the systems described herein may be referred to as “data.” Data may be used to refer generically to modes of storing and / or conveying information. Accordingly, data may refer to textual entries in a table of a database. Data may refer to alphanumeric characters stored in a database. Data may refer to machine- readable code. Data may refer to images. Data may refer to audio. Data may refer to, more broadly, a sequence of one or more symbols. The symbols may be binary. Data may refer to a machine state that is computer-readable. Data may refer to human- readable text.

[0037] Various of the devices in the voice-activated Al system 100, including the server device 200a and / or the client device 200b, may include a user interface for outputting information in a format perceptible by a user and receiving input from the user, e.g., the user interface 214, The user interface may include a display screen such as a light-emitting diode (LED) display, an organic LED(OLED) display, an active-matrix OLED (AMOLED) display, a liquid crystal display (LCD), a thin- film transistor (TFT) LCD, a plasma display, a quantum dot (QLED) display, and so forth. The user interface may include an acoustic element such as a speaker, a microphone, and so forth. The user interface may include a button, a switch, a keyboard, a touch-sensitive surface, a touchscreen, a camera, a fingerprint scanner, and so forth. The touchscreen may include a resistive touchscreen, a capacitive touchscreen, and so forth.

[0038] Various methods are described below. The methods may be implemented by the data analysis system 100 and / or various elements of the data analysis system described above. For example, inputs indicated as being received in a method may be input at the client device 200b and / or received at the server device 200a. Determinations made in the methods may be outputs generated by the processing device 206 based on inputs stored in the memory device 204. Correlations performed in the methods may be executed by the correlation module 206a. Inference outputs may be generated by the inference module 206b. Key data and / or actionable data may be stored in the knowledge database 204b. Correlations between key data and actionable data may be stored in the knowledge database 204b. Outputs generated in the methods may be output to the output database 204c and / or the client device 200b. In general, data described in the methods may be stored and / or processed by various elements of the data analysis system 100.

[0039] FIG. 3 illustrates an integrated hardware-based voice-activated Al system 300 for versatile task execution, according to an embodiment. The Al system 300 may be capable of comprehending and executing spoken language commands and performing a wide array of tasks for a user.According to various embodiments, the voice-activated Al system 300 may comprise a voice-input interface 305, a processing module 320, a graphics processing unit (GPU) 355, a control circuit 360, a communication module 365, and a user interface 370.

[0040] The voice-input interface 305 may comprise a microphone 310 and an analog-to-digital converter 315. The microphone 310 may be a high-quality condenser microphone capable of capturing an audio signal with precision. In various embodiments, alternatives such as dynamic microphones or even array microphones may be used to capture audio from different angles or filter background noise. The analog-to-digital converter 315 may be configured to convert the captured analog audio signal into a digital signal. The process may involve various quantization and sampling techniques. Variations in the process of converting the captured audio signal into the digital signal may include different converter resolutions or sampling rates to adapt to various environmental conditions or user preferences.

[0041] The processing module 320 may comprise a processing unit (CPU) 325 and memory 330. The processing unit 325 may execute instructions from the memory 330, which may store machine learning algorithms and natural language processing routines. In some embodiments, multiple CPUs may be integrated, and the memory 330 may comprise volatile RAM for real-time data processing and non-volatile storage like SSDs or Flash memory for storing models, datasets, and system configurations. The clock speed, core count, and memory capacity of the processing unit 325 may vary across different configurations to meet performance demands.

[0042] The processing module 320, integrated into the voice-activated Al system 300, may establish communication links with various components to enhance its functionality. Notably, the processing module 320 may connect with an integration module for Whisper ASR 335, which incorporates a software interface and a set of APIs. Whisper ASR along with its software interface and APIs may be configured to enable the processing module 320 to efficiently transmit the audio signal representing the user’s voice input for transcription and subsequently process the transmitted digital signal, converting it into a text signal. Simultaneously, the processing module 320 may verify the user input by sending a confirmation request to the user after processing their spoken language input but before converting the digital signal to the text signal. The purpose of the request may be to solicit the user’s validation or modification of the generated response or action before execution. The processing module 320 may utilize optical character recognition (OCR) or natural language processing (NLP) to analyze the user input to confirm the accuracy and relevance within the given context. The verification process may aid in reducing errors and identify inconsistencies, inaccuracies, or missing information in user inputs and prompt users for clarification or correction if needed. It will be appreciated that the specifics of the confirmation process may vary across different embodiments to accommodate diverse user interfaces or interaction preferences.

[0043] The processing module 320 may also establish a communication link with an integration module for ChatGPT 337. The integration module for ChatGPT 337 may enable the voice-activated Al system 300 to generate a contextually aware response. The integration module for ChatGPT 337 may be configured to process the text signal to understand user intent and generate an output signal comprising embedded instructions and transaction specific data for communication with a DeFi platform’s API. Within the integration module for ChatGPT 337, advanced algorithms and processes may be used to process the text signal derived from Whisper ASR to enable a comprehensive understanding of user intent. The output signal may comprise embedded instructions and transaction-specific data which may set the stage for communication with an API of a decentralized finance platform (DeFi) 340. The DeFi platform’s API may be configured to receive the outputsignal and initiate the requested transaction according to the embedded instructions. The instructions may be shaped by the user's voice command. The requested transaction may include cryptocurrency swapping or smart contact execution.

[0044] In addition, the processing module 320 may establish a communication link with a hardwarebased feedback and learning system for processing and storing historical user interactions and transaction data in memory. The feedback and learning system may allow the voice-activated Al system 300 to continuously enhance its performance, adapt to evolving user preferences, and refine its natural language understanding. For example, in one embodiment, the processing module 320 may establish communication links with an education content integration module 345 and a Langchain module or platform 350. The educational content integration module 345 may be integrated with ChatGPT and may be configured to continuously transmit updated and relevant educational content to ChatGPT, where ChatGPT may assimilate the updated and relevant educational content into its responses in the form of the output signal. The Langchain platform 350 may be configured to process the ChatGPT -generated output signal and extract valuable insights into preferences and behaviors of the user and utilize the extracted insights to tailor the ChatGPT- generated output signal to the user according to the user’s preferences. Different embodiments may employ varying machine learning models, data storage strategies, or update frequencies to accommodate diverse user needs and learning objectives.

[0045] The graphics processing unit (GPU) 355 and a control circuit 360 may be interconnected with the processing module 320 to execute one or more algorithms and software to perform a wide spectrum of tasks and functionalities. The algorithms and routines, which may be stored in the memory 330, may be utilized for processing data, while the control circuit 360 may be utilized for processing tailored to specific functions, such as cryptocurrency trading or cryptographic operations. For example, the GPU 355 may be used for dissecting and comprehending the digital data representing spoken language input, including operations like identifying user intents, extracting entities, and determining context from the voice data. The GPU 355 may also be utilized for image recognition, language translation, financial transactions, and cryptocurrency trading. In alternative embodiments, multiple GPUs or custom-designed control circuits may be employed to enhance the system's capacity and efficiency.

[0046] The GPU 355 may comprise numerous cores designed for parallel processing, allowing it to handle intricate mathematical computations and large volumes of data simultaneously. This parallelism may prove particularly valuable for tasks like image recognition and deep learning. Additionally, the GPU 355 may be integrated with tensor cores and specialized units optimized formatrix operations essential in neural networks, which significantly expedite Al-related workloads. Furthermore, the GPU 155 may support a variety of programming frameworks like CUDA and OpenCL.

[0047] In one embodiment, the control circuit 360 may comprise an application-specific integrated circuit (ASIC), particularly in areas that require high-performance, low-latency processing, such as cryptocurrency trading and financial transactions. The ASIC circuit may be able to execute tasks with minimal power consumption making them ideal for applications where energy efficiency is a critical concern. In this regard, the Al system may remain power-efficient while performing computationally intensive operations. The ASIC circuit may feature custom algorithms, optimized for cryptographic operations, which are crucial for securing transactions within the system. The ASIC may comprise various key elements, including custom-designed logic gates, memory elements, and specialized processing units tailored for the system’s specific functions.

[0048] The communication module 365 may be utilized to connect the system 300 with an external system. The external system may comprise a trading platform, an online voting system, or an online form. For example, the communication module 365 may enable a user to trade stocks and cryptocurrencies, manage securities, and access technology-related information. By enabling voice commands, the communication module 365 may simplify trading processes and cater to users of varying experience levels. Moreover, the communication module 365 may serve as an educational hub, consistently delivering up-to-date content and answering user queries. The capabilities of the communication, however, are not limited solely to trading platforms, online voting systems, or online forms. Instead, the communication module 365 may adapt to communicate effectively with a wide range of external systems, accommodating diverse applications and use cases.

[0049] The communication module 365 may comprise a network interface 366 for establishing a secure and efficient connection with the external system over a network protocol. The network interface 366 may be configured to handle various network protocols and standards to ensure compatibility with a wide range of external systems. For example, the protocol-specific components may adapt to different communication standards and may comprise HTTP, WebSocket, or custom APIs, ensuring effective data exchange with the external system. The communication module 365 may also comprise a data form conversion hardware-based component 367. The data form conversion hardware-based component 367 may be configured to translate data and messages between internal data structures of the voice-activated artificial intelligence (Al) system 300 and data structures of the external system. The communication module 165 may further comprise an authentication and: authorization module 369 configured to verify and authorize access to theexternal system. The authentication and authorization module 369 may be configured to utilize encryption and authentication protocols to ensure secure transactions and interactions to access and perform actions on the trading platform.

[0050] The user interface 370 may enable the user to interact with the voice-activatd Al system 300. The user interface 370 may comprise a display 375 for presenting textual or graphical information and an audio device 380 for providing voice-based responses or audio feedback to the user. The audio device 380 may utilize various technologies like OLED, LCD, or E-ink, with varying resolutions and sizes. The audio device 380 may comprise a stereo speaker, a surround sound system, a bone-conduction transducer for an immersive audio experience, and the like. The audio device 380 may be connected to an Eleven Labs' text-to-speech technology hardware-based module 385 that is configured to translate the ChatGPT-generated output signal into an audible response. The audible response may then be delivered to the user via the audio device 380, thereby allowing the user to interact with the system in a conversational manner.

[0051] The user interface 370 may also comprise a user authentication module 385 that may comprise various components such as a biometric sensor, a facial recognition camera, or a fingerprint scanner. The user authentication module 385 may be configured to verify the identity of the user based on voice biometrics or other biometric data. In various embodiments, the voice- activated Al system 300 may utilize alternative authentication methods or a combination of the biometric sensors to cater to diverse security requirements or user preferences. When a user interacts with the voice-activated Al system 300, the user interface 170 may prompt the user for authentication through the authentication module 385. For instance, if a user is required to provide a voice sample or undergo facial recognition for authentication, the user interface 370 can guide the user through this process. Once authentication is successful, the user may gain access to the voice- activated Al system 300, and the user interface 370 may provide a tailored response and / or information based on the identity and preferences of the user.

[0052] One notable feature of the user interface 370 is the voice-activated Al system's ability to assist users in filling out forms. The functionality may significantly streamline the often cumbersome process of form completion. When a user engages with a form, the voice-activated Al system may act as a digital assistant by providing prompts, suggestions, and auto-filling capabilities, The voice- activated Al system 300 does so by utilizing its natural language processing (NLP) capabilities to comprehend the form’s context and the user input. The process may include identifying specific form fields, understanding their purpose, and intelligently populating them with relevant information.Accordingly, the voice-activated Al system 300 may assist users in completing forms quickly and accurately.

[0053] In addition to form filling, the voice-activated Al system 300 may provide a wide array of functionalities designed to enhance the educational experience of users. Using its access to vast databases of educational content, the voice-activated Al system 300 may continuously update and deliver relevant educational materials to users. These materials may cover a spectrum of subjects and topics, catering to individual interests and educational needs. Users can interact with the voice- activated Al system 300 to seek explanations, explore educational content, and engage in learning experiences. The Al system's educational capabilities extend to providing insights and recommendations based on a user's learning history for ensuring that the educational content remains engaging and personalized.

[0054] The voice-activated Al system may also facilitate financial transactions, such as in the realm of cryptocurrency trading. The voice-activated Al system 300 may offer a swapping function designed to enable secure and efficient crypto transactions. To initiate a transaction, users are required to set up specific parameters, including input and output tokens, and the system may require precision in these inputs, requiring that users provide the exact token information for the transaction to be valid.

[0055] The voice-activated Al system 300 may go a step further in enhancing the security and legitimacy of these transactions. For example, the system 300 may have a predefined list of tokens 46 in total from the Polygon blockchain that have been thoroughly vetted for legitimacy and trustworthiness. The tokens may be deemed eligible for trading on the platform. If a user attempts to trade a token that is not on this list, the system will promptly generate an error message. The system’s approach to token validation and tradeability not only safeguards users against potential scams but also maintains the integrity of the platform's financial transactions.

[0056] Figures 4A to 4F illustrate various aspects of user interaction and customization during the voice command and recognition procedure and registration process of a voice-activated Al application 400. The voice-activated Al application 400 may enhance the user experience by addressing various aspects of voice command recognition and execution processes. For example, the user can initiate voice commands by clicking, pressing, and / or holding a record button 405. After clicking, pressing, and / or holding the record button 405, the user may provide spoken instructions, which are then processed and executed by the voice-activated Al application 400. The voice command process may serve as the gateway to comprehensive Al-powered task management and may allow an individual to create a personalized profile. During registration, the user may providestandard information, including their full name, email address, and a secure password. The voice- activated Al application 400 may also include optional fields for additional information. During voice command initiation, the user may provide standard instructions, including task requests, questions, and actions to be performed. The voice-activated Al application 400 may also include optional features for additional customization and preferences.

[0057] FIG. 5 is a flow diagram of a method (500) for versatile task execution using an integrated hardware-based voice-activated Al system. The hardware-implemented method (500) for operating a versatile voice-activated artificial intelligence (Al) system may comprise a series of steps. Initially, in step (505), the method may comprise receiving spoken language input from a user through the voice-input interface 305, which comprises the microphone 310 and analog-to-digital converter 315. The microphone 310 may capture an audio signal, and the analog-to-digital converter 315 may digitize the captured audio signal into a digital format, thereby allowing the system to process and analyze the user's spoken commands effectively.

[0058] Moving on to step (510), the method may comprise utilizing a processing module 320, which includes the central processing unit (CPU) 325 and memory 330. Here, the digital signal representing the user's spoken input may be subjected to analysis and interpretation. The processing module 320 may execute a machine learning algorithm and a natural language processing routine stored in the memory 330 to discern various elements of the user’s spoken input, such as user intents, extracted entities, and contextual understanding.

[0059] In step (515), the method may utilize the graphics processing unit (GPU) 355 and the control circuit 360 to generate a response or action based on the previously analyzed spoken language input. The hardware components may execute an algorithm and software suite that enables the voice- activated Al system to perform an extensive array of tasks and functionalities. The functionalities may include data processing, image recognition, language translation, financial transactions, and cryptocurrency trading.

[0060] Lastly, in step (520), the method may comprise delivering the generated response or action to the user through the user interface 370. The user interface 370 may include the display 375 and the audio device 180, such as a speaker. The display 375 may present textual or graphical information associated with the generated response or action, Simultaneously, the speaker may provide audio feedback or a voice-based response to the user.

[0061] The foregoing steps include the core functionalities of the method (500). Furthermore, as detailed in paragraphs

[0041] to

[0043] of this application, the method may also include an integration of additional modules like Whisper ASR, ChatGPT, educational content integration,Eleven Labs' text-to-speech platform, and the Langchain platform. The integrations may enhance the system's capabilities and further cater to user preferences and needs.

[0062] A feature illustrated in one of the figures may be the same as or similar to a feature illustrated in another of the figures. Similarly, a feature described in connection with one of the figures may be the same as or similar to a feature described in connection with another of the figures. The same or similar features may be noted by the same or similar reference characters unless expressly described otherwise. Additionally, the description of a particular figure may refer to a feature not shown in the particular figure. The feature may be illustrated in and / or further described in connection with another figure.

[0063] Elements of processes (i.e. methods) described herein may be executed in one or more ways such as by a human, by a processing device, by mechanisms operating automatically or under human control, and so forth. Additionally, although various elements of a process may be depicted in the figures in a particular order, the elements of the process may be performed in one or more different orders without departing from the substance and spirit of the disclosure herein.

[0064] The foregoing description sets forth numerous specific details such as examples of specific systems, components, methods and so forth, in order to provide a good understanding of several implementations. It will be apparent to one skilled in the art, however, that at least some implementations may be practiced without these specific details. In other instances, well-known components or methods are not described in detail or are presented in simple block diagram format in order to avoid unnecessarily obscuring the present implementations. Thus, the specific details set forth above are merely exemplary. Particular implementations may vary from these exemplary details and still be contemplated to be within the scope of the present implementations.

[0065] Related elements in the examples and / or embodiments described herein may be identical, similar, or dissimilar in different examples. For the sake of brevity and clarity, related elements may not be redundantly explained. Instead, the use of a same, similar, and / or related element names and / or reference characters may cue the reader that an element with a given name and / or associated reference character may be similar to another related element with the same, similar, and / or related element name and / or reference character in an example explained elsewhere herein. Elements specific to a given example may be described regarding that particular example. A person having ordinary skill in the art will understand that a given element need not be the same and / or similar to the specific portrayal of a related element in any given figure or example in order to share features of the related element.

[0066] It is to be understood that the foregoing description is intended to be illustrative and not restrictive. Many other implementations will be apparent to those of skill in the art upon reading and understanding the above description. The scope of the present implementations should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

[0067] The foregoing disclosure encompasses multiple distinct examples with independent utility. While these examples have been disclosed in a particular form, the specific examples disclosed and illustrated above are not to be considered in a limiting sense as numerous variations are possible. The subject matter disclosed herein includes novel and non-obvious combinations and subcombinations of the various elements, features, functions and / or properties disclosed above both explicitly and inherently. Where the disclosure or subsequently filed claims recite “a” element, “a first" element, or any such equivalent term, the disclosure or claims is to be understood to incorporate one or more such elements, neither requiring nor excluding two or more of such elements.

[0068] As used herein '‘same” means sharing all features and “similar” means sharing a substantial number of features or sharing materially important features even if a substantial number of features are not shared. As used herein “may” should be interpreted in a permissive sense and should not be interpreted in an indefinite sense. Additionally, use of “is” regarding examples, elements, and / or features should be interpreted to be definite only regarding a specific example and should not be interpreted as definite regarding every example. Furthermore, references to “the disclosure” and / or “this disclosure” refer to the entirety of the writings of this document and the entirety of the accompanying illustrations, which extends to all the writings of each subsection of this document, including the Title, Background, Brief description of the Drawings, Detailed Description, Claims, Abstract, and any other document and / or resource incorporated herein by reference.

[0069] As used herein regarding a list, “and" forms a group inclusi ve of all the listed elements. For example, an example described as including A, B, C, and D is an example that includes A, includes B. includes C, and also includes D. As used herein regarding a list, “or” forms a List of elements, any of which may be included. For example, an example described as including A, B, C, or D is an example that includes any of the elements A, B, C, and D. Unless otherwise stated, an example including a list of alternatively-inclusive elements does not preclude other examples that include various combinations of some or all of the alternatively-inclusive elements. An example described using a list of alternatively-inclusive elements includes at least one element of the listed elements. However, an example described using a list of alternatively-inclusive elements does not precludeanother exampie that includes all of the listed elements. And, an example described using a list of alternatively-inclusive elements does not preclude another example that includes a combination of some of the listed elements. As used herein regarding a list, "and / or” forms a list of elements inclusive alone or in any combination. For example, an example described as including A, B, C, and / or D is an example that may include: A alone; A and B; A, B and C; A, B, C, and D; and so forth. The bounds of an “and / or” list are defined by the complete set of combinations and permutations for the list.

[0070] Where multiples of a particular element are shown in a FIG., and where it is clear that the element is duplicated throughout the FIG., only one label may be provided for the element, despite multiple instances of the element being present in the FIG. Accordingly, other instances in the FIG. of the element having identical or similar structure and / or function may not have been redundantly labeled. A person having ordinary skill in the art will recognize based on the disclosure herein redundant and / or duplicated elements of the same FIG. Despite this, redundant labeling may be included where helpful in clarifying the structure of the depicted examples.

[0071] The Applicant(s) reserves the right to submit claims directed to combinations and subcombinations of the disclosed examples that are believed to be novel and non-obvious. Examples embodied in other combinations and sub-combinations of features, functions, elements and / or properties may be claimed through amendment of those claims or presentation of new claims in the present application or in a related application. Such amended or new claims, whether they are directed to the same example or a different example and whether they are different, broader, narrower or equal in scope to the original claims, are to be considered within the subject matter of the examples described herein.

Claims

CLAIMS:

1. A hardware-based voice-activated artificial intelligence (Al) system for versatile task execution, comprising: an input interface, comprising a microphone and analog-to-digital converter, configured to receive spoken language input provided by a user, wherein the microphone captures an audio signal, and the analog-to-digital converter digitizes the captured audio signal into a digital signal; a processing module, comprising a central processing unit (CPU) and memory, configured to process the received spoken language input by executing a machine learning algorithm or a natural language processing routine stored in the memory, wherein the CPU executes instructions to enable analysis of the digital signal for identifying user intents, extracting entities, and determining context; a graphics processing unit (GPU) and a control circuit, configured to generate a response or action based on the analysis of the spoken language input, wherein the GPU and control circuit executes an algorithm to perform a plurality of tasks and functionalities, including data processing, image recognition, language translation, financial transactions, or cryptocurrency trading; a communication module communicatively linked with an external system, including a trading platform, online voting system, or online form, wherein the communication module comprises: a network interface configured to establish a secure and efficient connection with the external system over a network protocol; a data format conversion hardware-based component configured to translate data and messages between the hardware-based voice-activated artificial intelligence (Al) system and the external system; and an authentication and authorization module configured to verify and authorize access to the external system, wherein the module utilizes an encryption and authentication protocol to provide a secure interaction; and a user interface, comprising a display and a speaker, configured to deliver the generated response or action to the user, wherein the display presents textual or graphical information and the speaker provides a voice-based response or audio feedback to the user.

2. The hardware-based voice-activated Al system of claim 1, further comprising a user authentication module comprising a biometric sensor, a facial recognition camera, or a fingerprint scanner, wherein the user authentication module is configured to verify an identity of the user based on voice biometrics or other biometric data.

3. The hardware- based voice-activated Al system of claim 1, further comprising a confirmation module configured to send a confirmation request to the user after processing the user’s spoken language input, wherein the confirmation request seeks user validation or modification of the generated response or action before executing the response or action.

4. The hardware-based voice-activated Al system of claim 1, further comprising a data encryption and security module configured to encrypt user data, financial transactions, and cryptocurrency data.

5. The hardware-based voice-activated Al system of claim 1, further comprising a hardwarebased feedback and learning system, wherein historical user interactions and transaction data are processed and stored in the memory to continuously improve the performance of the system, adapt to user preferences, and enhance natural language understanding.

6. The hardware-based voice-activated Al system of claim 1, further comprising: an integration module for ChatGPT that allows for the integration of ChatGPT to generate a contextually aware response, wherein the integration module is configured to process the digital signal to understand user intent and generate an output signal comprising embedded instructions and transaction-specific data for communication with a DeFi platform, wherein the DeFi platform is configured to receive the output signal and initiate a requested transaction according to the embedded instructions, wherein the requested transaction includes cryptocurrency swapping or smart contract execution; and an educational content integration module configured to continuously transmit updated and relevant educational content to ChatGPT, wherein ChatGPT assimilates the content into the response.

7. The hardware-based voice-activated Al system of claim 6, further comprising:an Eleven Labs' text-to-speech platform, wherein the Eleven Labs’ text-to-speech platform is connected to an audio device and is configured to translate the ChatGPT-generated output signal into an audible response; and a Langchain platform configured to optimize a personalization of the response by processing the ChatGPT-generated output signal to extract insights into user preferences and behaviors, wherein the Langchain platform is further configured to tailor the response according to the user preferences and deliver the tailored response to the user via the audio device.

8. A hardware-implemented method for operating a versatile voice-activated artificial intelligence (Al) system, comprising the steps of: receiving, via a hardware-based voice input interface comprising a microphone and analog- to-digital converter, spoken language input provided by a user, wherein the microphone captures an audio signal and the analog -to-digi tai converter digitizes the captured audio signal into a digital signal; processing, using a hardware-based processing module comprising a central processing unit (CPU) and memory, the digital signal by executing a machine learning algorithm and a natural language processing routine stored in the memory to analyze and interpret the digital signal, wherein the CPU executes instructions to identify user intents, extract entities, and determine context; generating, through a graphics processing unit (GPU) and a control circuit, a response or action based on the spoken language input, wherein the GPU and control circuit executes an algorithm to perform a plurality of tasks and functionalities, including data processing, image recognition, language translation, financial transactions, or cryptocurrency trading; and delivering the generated response or action to the user via a hardware- based user interface comprising a display and a speaker, wherein the display presents textual or graphical information and the speaker provides a voice-based response or audio feedback,9. The method of claim 8, further comprising the step of integrating Whisper ASR with the processing module using an integration module, wherein the Whisper ASR comprises a software interface and an API, and wherein the Whisper ASR is configured to process the digital signal and convert it into a text signal.

10. The method of claim 9, further comprising the step of integrating ChatGPT using an integration module to generate a contextually aware response, wherein the integration module processes the text signal to understand user intent and generate an output signal comprising embedded instructions and transaction-specific data for communication with a DeFi platform.

11. The method of claim 10, wherein the DeFi platform is configured to receive the output signal and initiate a requested transaction based on the embedded instructions, and wherein the requested transaction includes cryptocurrency swapping or smart contract execution.12, The method of Claim 10, further comprising the step of integrating an educational content integration module with ChatGPT, wherein the education content integration module is configured to continuously transmit updated and relevant educational content to ChatGPT, and wherein ChatGPT assimilates the content into the response.

13. The method of Claim 10, further comprising the step of connecting an Eleven Labs' text-to- speech platform to an audio device, wherein the Eleven Labs' text-to-speech platform is configured to translate the ChatGPT -generated output signal into an audible response.

14. The method of Claim 13, further comprising the step of utilizing a Langchain platform to optimize a personalization of the response by processing the ChatGPT -generated output signal, extracting valuable insights into user preferences and behaviors, and tailoring the ChatGPT -generated output signal to align with the user's preferences and delivering the tailored output signal to the user via the audio device.

15. A hardware-based voice-activated artificial intelligence (Al) system for versatile task execution, comprising: an input interface comprising: a microphone configured io receive spoken language input provided by a user in a form of an audio signal; and a converter configured to convert the captured audio signal to a digital signal;a processing module, comprising a central processing unit (CPU) and memory, configured to process the received spoken language input by executing a machine learning algorithm or a natural language processing routine stored in the memory, wherein the CPU executes instructions to identify user intents, extract entities, and determine context; a control circuit configured to generate a response or action based on the spoken language input, wherein the control circuit is configured to execute an algorithm to perform a plurality of tasks and functionalities; a communication module communicatively linked with an external system; and an audio device for providing audio feedback to the user according to the generated response or action.

16. The hardware-based voice-activated Al system of claim 15, wherein the tasks and functionalities comprise data processing, image recognition, language translation, financial transactions, or cryptocurrency trading.17, The hardware-based voice-activated Al system of claim 15, wherein the external system comprises a trading platform, online voting system, or online form,18, The hardware-based voice-activated Al system of claim 15, further comprising an integration module for Whisper ASR with the processing module, wherein Whisper ASR comprises a software interface and an API, and wherein Whisper ASR is configured to convert the digital signal into a text signal for communication with a DeFi platform.

19. The hardware-based voice-activated Al system of claim 18, further comprising: an integration module for ChatGPT that allows for the integration of ChatGPT to generate a contextually aware response, wherein the integration module is configured to process the digital text signal to understand user intent and generate an output signal comprising embedded instructions and transaction-specific data for communication with the DeFi platform, wherein the DeFi platform is configured to receive the output signal and initiate a requested transaction according to the embedded instructions, wherein the requested transaction includes cryptocurrency swapping or smart contract execution; andan educational content integration module configured to continuously transmit updated and relevant educational content to ChatGPT, wherein ChatGPT assimilates the content into the response.

20. The hardware-based voice-activated Al system of claim 19, further comprising: an Eleven Labs' text-to-speech platform, wherein the Eleven Labs’ text-to-speech platform is connected to the audio device and is configured to translate the ChatGPT-generated output signal into an audible response; and a Langchain platform configured to optimize a personalization of the response by processing the ChatGPT-generated output signal to extract insights into user preferences and behaviors, wherein the Langchain platform is further configured to tailor the response according to the user preferences and deliver the tailored response io the user via the audio device.

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