Apparatus and method for generating a market validation roadmap using generative AI

Abstract

This invention provides an apparatus and method for generating a market validation roadmap using generative AI to provide users with an optimized market entry strategy. [Solution] The method involves providing advertising data corresponding to each of the business model and multiple minimum viable products (MVPs, minimal visualization products) in conjunction with an external SNS platform server, collecting the data, generating marketability test result data for the minimum viable products corresponding to the advertising data using generative artificial intelligence based on the collected market response data, selecting at least one of the multiple minimum viable products based on the marketability test result data, and automatically generating a marketability verification roadmap based on the marketability test result data for at least one minimum viable product.

Description

Technical Field

[0001] The present disclosure relates to an apparatus and method for generating a market validation roadmap using generative AI. Background Art of the Invention

[0002] In recent years, due to the development of artificial intelligence technology, data analysis and decision-making support using AI have been actively carried out in various industrial fields. In particular, generative AI is a technology that can learn a vast amount of data and generate new content by itself, and is used to generate various forms of data such as images, texts, voices, and videos. Such generative AI plays an important role in creative work, automated report creation, and data-driven decision-making processes in various fields, and also helps in market analysis and validation processes.

[0003] Generally, before a new product or service is launched into the market, various data analyses and consumer surveys are required to verify the marketability of the product or service. However, existing market validation methods are time-consuming and the scope of data to be analyzed is limited, so there is a limit in quickly reflecting new market trends and consumer responses. In particular, when resources are limited, such as for startups and small and medium-sized enterprises, an automated solution is needed for efficient market validation.

[0004] Therefore, there is a need for an apparatus and method that can provide a market validation roadmap by automatically generating and analyzing data required for market validation using generative AI.

Summary of the Invention

Problems to be Solved by the Invention

[0005] Embodiments of the present disclosure can provide an apparatus and method for generating a market validation roadmap using generative AI.

[0006] The technical challenges to be addressed by these embodiments are not limited to those described above, and other technical challenges not mentioned may be considered by those skilled in the art from the various embodiments described below. [Means for solving the problem]

[0007] A server that provides a marketability verification roadmap for a business model using artificial intelligence generated according to one embodiment includes at least one processor. The server includes memory that stores instructions that the at least one processor perform at least one operation, the at least one operation which, in conjunction with an external SNS platform server, provides advertising data corresponding to each of a plurality of minimum viable products (MVPs, minimum visibility products) corresponding to the business model to the platform SNS advertisements. The server can perform the following steps: collect data; use the generative artificial intelligence to generate marketability test result data for the minimum viable products corresponding to the advertising data based on the collected market response data; select at least one of the plurality of minimum viable products based on the marketability test result data; and automatically generate a marketability verification roadmap based on the marketability test result data for the at least one minimum viable product. [Effects of the Invention]

[0008] According to the embodiment, the server can provide users with an optimized market entry strategy by using generative artificial intelligence to generate marketability test result data for minimal functional products corresponding to advertising data, and by automatically generating various marketability verification roadmaps based on the marketability test result data.

[0009] According to the embodiment, the server can simplify existing time-consuming and complex market research processes by analyzing not only existing formatted data but also unformatted data through generative artificial intelligence.

[0010] The effects that can be obtained from the examples are not limited to those mentioned above, and other effects not mentioned can be clearly derived and understood by those with ordinary skill in the art based on the detailed description below. The accompanying drawings, included as part of the detailed description to facilitate understanding of the embodiments, provide various embodiments and, together with the detailed description, illustrate the technical features of the various embodiments. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows the configuration of an electronic device according to one embodiment. [Figure 2] This figure shows the configuration of a program according to one embodiment. [Figure 3] This document describes how a server operates that provides a marketability verification roadmap for a business model using generative artificial intelligence, according to one embodiment. [Figure 4] This block diagram shows the server configuration according to one embodiment. [Modes for carrying out the invention]

[0012] The following embodiments combine the components and features of the embodiments in a predetermined form. Some components or features of an embodiment may be included in other embodiments or may be substituted for corresponding components or features of other embodiments.

[0013] The description of the drawings does not include any procedures or steps that could obscure the essence of the various embodiments, nor does it describe any procedures or steps that can be understood at the level of a person with ordinary skill in the art.

[0014] Throughout the specification, where a part "comprising" or "including" a component, this means, unless otherwise stated, that it may further include other components rather than excluding them. Furthermore, "a" or "an," "one," "it," and similar related terms may be used in the context describing various embodiments (particularly in the context of the following claims) to include both singular and plural forms unless explicitly stated otherwise in this specification.

[0015] Hereinafter, embodiments of various models will be described in detail with reference to the accompanying drawings. The detailed description disclosed below, along with the accompanying drawings, is an exemplary embodiment of various models. It is intended to describe the forms and not to show only one embodiment.

[0016] Furthermore, specific terms used in various embodiments are provided to facilitate understanding of those embodiments, and the use of these specific terms can be modified in other ways without departing from the technical idea of ​​the various embodiments.

[0017] This figure shows the configuration of an electronic device according to one embodiment.

[0018] Figure 1 is a block diagram of an electronic device 101 in a network environment 100 according to various embodiments. Referring to Figure 1, in the network environment 100, the electronic device 101 can communicate with an electronic device 102 via a first network 198 (e.g., a short-range wireless communication network) or with at least one of an electronic device 104 or a server 108 via a second network 199 (e.g., a long-range wireless communication network). According to one embodiment, the electronic device 101 can communicate with an electronic device 104 via a server 108. According to one embodiment, the electronic device 101 may include a processor 120, memory 130, input module 150, acoustic output module 155, display module 160, audio module 170, sensor module 176, interface 177, connection terminal 178, haptic module 8, 708, haptic module 8, 77, battery 189, communication module 190, subscriber identification module 196, or antenna module 197. In some embodiments, the electronic device 101 may omit at least one of these components (e.g., connection terminal 178) or may have one or more other components added. In some embodiments, some of these components (e.g., sensor module 176, camera module 180, or antenna module 197) may be incorporated into a single component (e.g., display module 160). The electronic device 101 may be referred to as a client, terminal, or peer.

[0019] The processor 120 can, for example, execute software (e.g., program 140) to control at least one other component (e.g., hardware or software component) of the electronic device 101 connected to the processor 120, and can perform various data processing or calculations. According to one embodiment, as at least part of the data processing or calculation, the processor 120 stores instructions or data received from other components (e.g., sensor module 176 or communication module 190) in volatile memory 132, processes the instructions or data stored in volatile memory 132, and stores the resulting data in non-volatile memory. According to one embodiment, the processor 120 may include a main processor 121 (e.g., central processing unit or application processor) or an auxiliary processor 123 (e.g., graphics processing unit, neural network processing unit (NPU), image signal processor, sensor hub processor, or communication processor) that can operate independently or together with it. For example, if the electronic device 101 includes a main processor 121 and an auxiliary processor 123, the auxiliary processor 123 may use less power than the main processor 121 or be configured to specialize in a specified function. The auxiliary processor 123 can be implemented separately from or as part of the main processor 121.

[0020] The auxiliary processor 123 can, for example, control at least one of the components of the electronic device 101's component 1, module 176, or communication module 190, together with the main processor 121, either on behalf of the main processor 121 when the main processor 121 is inactive (e.g., in sleep mode) or when the main processor 121 is active (e.g., running an application). According to one embodiment, the auxiliary processor 123 (e.g., an image signal processor or a communication processor) can be implemented as part of other functionally related components (e.g., a camera module 180 or a communication module 190). According to one embodiment, the auxiliary processor 123 (e.g., a neural network processing unit) may include hardware structures specialized for processing artificial intelligence models.

[0021] Artificial intelligence models can be generated through machine learning. Such learning may be performed, for example, on the electronic device 101 on which the artificial intelligence model is run, or via a separate server (e.g., server 108). The learning algorithm may include, but is not limited to, guided learning, unguided learning, semi-guided learning, or reinforcement learning. The artificial intelligence model may include multiple artificial neural network layers. The artificial neural network may be, but is not limited to, one of the following: deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), restricted Boltzmann machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), or a combination of two or more deep neural networks. In addition to the hardware structure, the artificial intelligence model may include additional or alternative software structures.

[0022] Memory 130 can store various data used by at least one component of the electronic device 101 (e.g., the processor 120 or the sensor module 176). The data can include, for example, software (e.g., program 140), and input data or output data for related instructions. Memory 130 can include volatile memory 132 or non-volatile memory 134.

[0023] Program 140 can be stored as software in memory 130 and can include, for example, an operating system 142, middleware 144, or an application 146.

[0024] Input module 150 can receive instructions or data used by a component of the electronic device 101 (e.g., the processor 120) from outside the electronic device 101 (e.g., the user). Input module 150 can include, for example, a microphone, a mouse, a keyboard, keys (e.g., buttons), or a digital pen (e.g., a stylus pen).

[0025] The acoustic output module 155 can output an acoustic signal to the outside of the electronic device 101. The acoustic output module 155 can include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback and recording playback. The receiver can be used to receive an incoming call. According to one embodiment, the receiver can be implemented separately from or as part of the speaker.

[0026] Module 160 can visually provide information to the outside of the electronic device 101 (e.g., the user). The display module 160 can include, for example, a display, a hologram device, or a projector and a control circuit for controlling the corresponding device. According to one embodiment, the display module 160 can include a touch sensor set to sense touch or a pressure sensor set to measure the intensity of the force generated by touch.

[0027] The audio module 170 can convert sound into electrical signals, or conversely, convert electrical signals into sound. According to one embodiment, the audio module 170 can acquire sound via the input module 150, or output sound via the sound output module 155, or via an external electronic device (e.g., electronic device 102) (e.g., speaker or headphones) directly or wirelessly connected to the electronic device 101.

[0028] The sensor module 176 can sense the operating state of the electronic device 101 (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the sensed state. According to one embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0029] Interface 177 can support one or more designated protocols that can be used for the electronic device 101 to connect directly or wirelessly to an external electronic device (e.g., electronic device 102). According to one embodiment, interface 177 may include, for example, a high-resolution multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0030] The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (e.g., electronic device 102). According to one embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0031] The tactile module 179 can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that the user can perceive through touch or kinesthetic sense. According to one embodiment, the tactile module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0032] The camera module 180 can capture still images and video. According to one embodiment, the camera module 180 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0033] The power management module 188 can manage the power supplied to the electronic device 101. According to one embodiment, the power management module 188 can be implemented, for example, as at least part of a power management integration circuit (PMIC).

[0034] The battery 189 can supply power to at least one component of the electronic device 101. According to one embodiment, the battery 189 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0035] The communication module 190 can support the establishment of a direct (e.g., wired) or wireless communication channel between the electronic device 101 and an external electronic device (e.g., electronic device 102, electronic device 104, or server 108), and the execution of communication over the established communication channel. The communication module 190 operates independently of the processor 120 (e.g., the application processor) and may include one or more communication processors that support direct (e.g., wired) or wireless communication. According to one embodiment, the communication module 190 may include a wireless communication module 192 (e.g., a cellular communication module, a near-field wireless communication module, or a GNSS (global navigation satellite system) communication module) or a wired communication module 194 (e.g., a LAN (local area network) communication module, or a power line communication module). Of these communication modules, the corresponding communication module can communicate with a first network 198 (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network 199 (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network, e.g., an electronic device 104). Some of these types of communication modules may be integrated into a single component (e.g., a single chip) or implemented in multiple separate components (e.g., multiple chips). The wireless communication module 192 can verify or authenticate the electronic device 101 within a communication network such as the first network 198 or the second network 199 using subscriber information (e.g., an International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 196.

[0036] The wireless communication module 192 can support 5G networks following 4G networks and next-generation communication technologies, such as NR connectivity technology. NR connectivity technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module 192 can support high-frequency bands (e.g., mmWave bands) to achieve high data rates. The wireless communication module 192 can support various technologies to ensure performance in high-frequency bands, such as beamforming, massive array multiple-input and multiple-output (massive MIMO (multiple-input and multiple-output)), full-dimensional multiple-input / output (FD-MIMO), array antenna beamforming, or large-scale antennas. The wireless communication module 192 can support various requirements specified by the electronic device 101, external electronic devices (e.g., electronic device 104), or network systems (e.g., second network 199). According to one embodiment, the wireless communication module 192 has a peak data rate of 0.5 for eMBB realization (e.g., 20 Gbps or more), loss coverage of 0.5 for mMTC realization (e.g., 164 dB or less), or U-plane latency (e.g., downlink (DL) and uplink (UL)) for URLRC realization.

[0037] The antenna module 197 can transmit or receive signals or power to an external device (e.g., an external electronic device). At least one antenna suitable for a communication scheme used in a communication network such as network 198 or a second network 199 may be selected from a plurality of antennas by, for example, the communication module 190 (integrated circuit).

[0038] According to various embodiments, the antenna module 197 can form an mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., the bottom surface) of the printed circuit board and capable of supporting a specified high-frequency band (e.g., the mmWave band), and an antenna (e.g., an array antenna) disposed on or above a plurality of frequency bands on a second surface (e.g., the top surface or side surface) of the printed circuit board.

[0039] At least some of the aforementioned components are connected to each other via a peripheral device communication method (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and can exchange signals (e.g., instructions or data) with each other.

[0040] According to one embodiment, commands or data can be transmitted to or received between the electronic device 101 and an external electronic device 104 via a server 108 connected to a second network 199. Each of the external electronic devices 102 or 104 may be the same or a different type of device as the electronic device 101. According to one embodiment, all or part of the operation performed by the electronic device 101 can be performed by one or more of the external electronic devices 102, 104, or 108. For example, if the electronic device 101 must automatically perform a function or service, or automatically in response to a request from a user or other device, the electronic device 101 may, instead of performing the function or service itself, or additionally, request one or more external electronic devices to perform at least part of that function or service. One or more external electronic devices that receive the request may perform at least part of the requested function or service, or additional functions or services related to the request, and communicate the results of the execution to the electronic device 101. The electronic device 101 may process the results as they are or additionally and provide them as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technologies can be used. The electronic device 101 can, for example, provide ultra-low latency services using distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an IoT (Internet of Swing) device. The server 108 may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device 104 or the server 108 can be included in the second network 199. The electronic device 101 can be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technologies.

[0041] Server 108 is connected to electronic devices 101 and can provide services to the connected electronic devices 101. Server 108 can also store and manage various information of users who have completed the membership registration procedure and have joined as members, and can provide various purchase and payment functions related to the service. Furthermore, Server 108 may share execution data of service applications running on multiple electronic devices 101 in real time so that services can be shared among users. Such a server 108 can have the same hardware configuration as a conventional web server or service server. However, in terms of software, it can be implemented through some language such as C, C++, Java, Python, Golang, or Kotlin, and can include program modules that perform various functions. Generally, Server 108 refers to a computer system and the computer software (server program) installed for this purpose that is connected to an unspecified number of clients and / or other servers via an open computer network such as the Internet, receives work requests from clients or other servers, derives and provides the results of those work. Furthermore, server 108 should be understood as a broader concept that includes not only the server program described above, but also a series of application programs running on server 108, and various databases (DB: Database, hereinafter referred to as "DB") that may be built internally or externally. Therefore, server 108 classifies and stores and manages member registration information and various information and data related to the game in the DB. This DB can be implemented internally or externally to server 108.Furthermore, Server 108 can be implemented using server programs provided by various operating systems such as Windows, Linux, Unix, and Macintosh on general-purpose server hardware. Typical examples include IIS (Internet Information Server), CUN, and NCPA used in Windows environments, which can be used to implement web services. Server 108 may also be linked to authentication and payment systems for user authentication of services and for purchase settlements related to services.

[0042] The first network 198 and the second network 199 refer to a connection structure that enables information exchange between each node, such as terminals and servers, or a network connecting server 108 and electronic devices 101 and 104. The first network 198 and the second network 199 include, but are not limited to, the Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), 3G, 4G, LTE, 5G, Wi-Fi, etc. The first network 198 and the second network 199 may be closed networks such as LAN and WAN, but it is preferable that they be open networks such as the Internet. The Internet refers to a global open computing network structure consisting of the TCP / IP protocol, TCP, UDP (user datagram protocol), and multiple services that exist at a higher layer, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), and SNMP (Simple Network Management Protocol).

[0043] A database can have a general data structure implemented in the storage space (hard disk or memory) of a computer system using a database management program (DBMS). A database can have a data storage form that allows for free retrieval (extraction), deletion, editing, and addition of data. A database can be implemented for the purposes of one embodiment of this disclosure using relational database management systems (RDBMS) such as Oracle, Infomix, Sybase, and DB2, object-oriented database management systems (OODBMS) such as Gemston, Orion, and O2, and XML native databases such as Excelon and Sekaiju, and can have appropriate fields or elements to achieve its own functionality.

[0044] Software can include computer programs, code, instructions, or a combination of one or more of these, which can configure a processing unit to operate as desired, or which can instruct the processing unit independently or in combination. Software and / or data can be permanently or temporarily embodied in any kind of machine, component, physical device, virtual device, computer storage medium or device, or transmitted signal wave, in order to be interpreted by a processing unit or to provide instructions or data to a processing unit. Software can be distributed across a network of computer systems and stored or executed in a distributed manner. Software and data can be stored on one or more computer-readable recording media.

[0045] The methods according to the embodiments are carried out in the form of program instructions that can be executed via various computer means and can be recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., individually or in combination. The program instructions recorded on the medium may be specifically designed and configured for the embodiments, or they may be known and usable by those skilled in the computer software art. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as optical discs, and program instructions such as ROM, RAM, and flash memory. Examples of program instructions include not only machine code, such as that produced by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above can be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

[0046] Figure 2 shows the configuration of a program according to one embodiment.

[0047] Figure 2 is a block diagram 200 showing program 140 according to various embodiments. According to one embodiment, program 140 may include an operating system 142, middleware 144, or an application 146 executable on the operating system 142 for controlling one or more resources of the electronic device 101. The operating system 142 may include, for example, Android™, iOS™, Windows™, Symbian™, Tizen™, or Bada™. At least some of the programs of program 140 may be preloaded onto the electronic device 101 at the time of manufacture, for example, or may be downloaded or updated from an external electronic device (e.g., electronic device 102 or 104, or server 108) when used by a user. All or part of program 140 may include a neural network.

[0048] The operating system 142 can control the management (e.g., allocation or retrieval) of one or more system resources (e.g., processes, memory, or power) of the electronic device 101. It may include one or more driver programs for driving module 176, interface 177, haptic module 179, camera module 180, power management module 188, battery 189, communication module 190, subscriber identification module 196, or antenna module 197.

[0049] Middleware 144 can provide various functions to application 146 so that application 146 can use functions or information provided from one or more resources of electronic device 101. Middleware 144 may include, for example, application manager 201, window manager 203, multimedia manager 205, resource manager 207, power manager 209, database manager 211, package manager 213, connectivity manager 2, connectivity manager 2, location manager 219, graphics manager 221, security manager 223, call manager 225, or speech recognition manager 227.

[0050] The application manager 201 can, for example, manage the lifecycle of application 146. The window manager 203 can, for example, manage one or more GUI resources used on the screen. The multimedia manager 205 can, for example, determine one or more formats required for playback of media files and perform encoding or decoding of the media files using codecs that conform to the selected corresponding formats. The resource manager 207 can, for example, manage the source code of application 146 or the memory space of memory 130. The power manager 209 can, for example, manage the capacity, temperature, or power of battery 189 and use that information to determine or provide relevant information necessary for the operation of electronic device 101. According to one embodiment, the power manager 209 can be linked with the BIOS (basic input / output system) (not shown) of the electronic device 101.

[0051] The database manager 211 can, for example, create, search, or modify databases used by application 146. The package manager 213 can, for example, manage the installation or updates of applications distributed in the form of package files. The connectivity manager 215 can, for example, manage wireless or direct connections between electronic device 101 and external electronic devices. The call management manager 217 can, for example, provide a function to notify the user of the occurrence of specified events (e.g., incoming calls, messages, or alarms). The location manager 219 can, for example, manage the location information of electronic device 101. The graphics manager 221 can, for example, manage one or more graphic effects or associated user interfaces to be provided to the user.

[0052] The security manager 223 can, for example, provide system security or user authentication. The call manager 225 can, for example, manage voice call functions or video call functions provided by the electronic device 101. The voice recognition manager 227 can, for example, send user voice data to the server 108 and receive from the server 108 instructions corresponding to functions executed on the electronic device 101 based on at least part of the voice data, or character data converted based on at least part of the voice data. According to one embodiment, the middleware 244 can dynamically remove some existing components or add new components. According to one embodiment, at least part of the middleware 144 may be included as part of the operating system 142, or it may be implemented in separate software different from the operating system 142.

[0053] Application 146 may include, for example, applications such as Home 251, Dialer 253, SMS / MMS 255, IM (instant message) 257, Browser 259, Camera 261, Alarm 263, Contact 265, Voice Recognition 267, Media 327, Email 269, Album 275, Watch 277, Health 279 (e.g., measuring biometric information such as exercise level or blood glucose), or Environmental Information 281 (e.g., measuring atmospheric pressure, humidity, or temperature information). According to one embodiment, application 146 may further include an information exchange application (not shown) that can support information exchange between the electronic device 101 and an external electronic device. The information exchange application may include, for example, a notification relay application configured to transmit specified information (e.g., calls, messages, or alarms) to an external electronic device, or a device management application configured to manage an external electronic device. The notification relay application may transmit notification information to an external electronic device in response to a specified event (e.g., receiving a mail) that has occurred in another application of the electronic device 101 (e.g., an email application 269). Additionally or alternatively, the notification relay application can receive notification information from an external electronic device and provide it to the user of the electronic device 101.

[0054] The device management application can, for example, control the power (e.g., turn on or turn off) or functions (e.g., brightness, resolution, or focus) of an external electronic device or some component thereof (e.g., a display module or camera module of an external electronic device) that communicates with the electronic device 101. The device management application can also, either additionally or alternatively, support the installation, removal, or updating of applications running on the external electronic device.

[0055] In this specification, the terms neural network, neural network network, and network function may be used interchangeably. A neural network can consist of a set of interconnected computational units, sometimes commonly called “nodes.” These “nodes” may also be called “neurons.” A neural network is configured to contain at least two or more nodes. The nodes (or neurons) that make up a neural network may be interconnected by one or more “links.”

[0056] Within a neural network, two or more nodes connected via links can form a relative input-output node relationship. The concepts of input and output nodes are relative; any node that is an output node to another node is an input node to another node, and vice versa. As mentioned above, the relationship between input and output nodes can be generated around links. One input node can be connected to one or more output nodes via links, and vice versa.

[0057] In a relationship between input and output nodes connected via a single link, the output node can determine its value based on the data input to the input node. Here, the nodes interconnecting the input and output nodes may have weights. These weights can be variable and may be changed by the user or algorithm to enable the neural network to perform a desired function. Here, the edges or links interconnecting the input and output nodes have weights that can be variably applied by the user or algorithm to enable the neural network to perform a desired function. For example, if one or more input nodes are interconnected to one output node by each link, the output node can determine its value based on the values ​​input to the input nodes connected to the output node and the weights set for the links corresponding to each input node.

[0058] As described above, a neural network is formed when two or more nodes are interconnected via one or more links, creating a relationship between input and output nodes within the neural network. The number of nodes and links in the neural network, the relationships between nodes and links, and the weight values ​​assigned to each link can determine the characteristics of the neural network. For example, if there are two neural networks with the same number of nodes and links but different weight values ​​between links, the two neural networks may be perceived as different from each other.

[0059] This describes how a server operates that provides a marketability validation roadmap for a business model using generative artificial intelligence, according to one embodiment. The embodiment in Figure 3 can be combined with various embodiments of this disclosure.

[0060] Referring to Figure 3, in step S310, the server (for example, server 108 in Figure 1) can work in conjunction with an external SNS platform server to provide the SNS platform server with advertising data corresponding to each of the multiple minimum-function products corresponding to the business model.

[0061] The server could be one that uses generative artificial intelligence to provide a roadmap for validating the marketability of a business model. A minimalist product is a product that implements the core functions of the business model in the simplest form, and represents an experimental stage product for quickly checking market response.

[0062] For example, an advertisement for product A may consist of the product's image, description, price, hashtags, and click links. For example, advertising data may be automatically generated via artificial intelligence in a way that makes it customizable to the target consumer. Advertising targeting variables can include the user's location, age, gender, past search history, and purchase history. For example, a server can deliver optimized advertisements to the SNS platform server based on the advertising targeting variables and advertising data. For example, the advertising data is mainly delivered to the SNS platform server in a structured data format such as JSON or XML, and the data can be updated in real time on the server.

[0063] In step S320, the server can collect market response data corresponding to advertising data from the SNS platform server.

[0064] Market response data can include both formatted and unformatted data.

[0065] For example, formatted data may include the number of times advertising data was exposed to users of the SNS platform server via the SNS platform server, the number of times users selected a link corresponding to the advertising data, the number of times they purchased a product or service through a link corresponding to the advertising data, and the number of times they responded to a survey provided through a link corresponding to the advertising data.

[0066] For example, unstructured data may include text obtained by parsing the structure of markup language on a web page associated with an SNS platform server.

[0067] For example, the server can analyze the collected unstructured data using natural language processing techniques. For example, the server can quantify unstructured data by performing sentiment analysis in multiple steps, separating positive, neutral, and negative feedback.

[0068] Specifically, the server can analyze the HTML documents of web pages provided by the SNS platform server. For example, the server can hierarchically analyze the HTML documents of web pages based on the tags written in the HTML code of the web pages. For example, the server can convert the overall structure of the HTML document into a tree format and set parent-child relationships during the parsing process. For example, the server can detect HTML tags containing necessary information such as comments, postings, and usernames. For example, the server can extract only the necessary text from the parsed HTML code. For example, the server can identify target elements using specific classes or IDs and obtain the necessary data. For example, the server can classify the extracted text according to pre-defined criteria. For example, the server can store comments and postings separately and classify positive, neutral, and negative feedback in multiple stages using natural language processing techniques.

[0069] In step S33O, the server can use generative artificial intelligence to generate marketability test result data for the minimum functional product corresponding to the advertising data, based on the collected market response data.

[0070] Marketability test results data may include interest levels calculated using the number of exposures and the number of times a link was selected, purchase levels calculated using the number of times a link was selected and the number of purchases made, and engagement levels calculated using the number of purchases made and the number of times a survey was answered.

[0071] For example, a server can calculate the level of interest by calculating the number of clicks relative to the number of times an ad is displayed. For instance, if an ad for product A is displayed 10,000 times and 500 of those times result in clicks, the level of interest can be calculated as (500 / 10,000) × 100 = 5%.

[0072] For example, a server can calculate the percentage of clicks that resulted in an actual purchase. If 50 out of 500 clicks resulted in a purchase, the purchase rate can be calculated as (50 / 500) × 100 = 10%.

[0073] For example, the server can calculate engagement based on the percentage of users who complete a survey after a purchase. For instance, if 10 out of 50 purchases complete the survey, the engagement can be calculated as (10 / 50) × 100 = 20%.

[0074] For example, the server can assign weights to each performance indicator (interest level, purchase level, involvement level). For instance, the server can set the purchase level to 50%, the interest level to 30%, and the involvement level to 20%, and then calculate the final overall score.

[0075] For example, the server can synthesize the aforementioned data to generate marketability test results for each product and objectively evaluate the performance of each MVP.

[0076] In step S3 4 0, the server can select at least one of several minimum-function products based on the marketability test results data.

[0077] For example, the server can compare the marketability test results of each minimum-function product. For instance, if product A records interest of 5%, purchase of 10%, and engagement of 20%, while product B records 3%, 7%, and 15% respectively, the server can select product A.

[0078] For example, a server can calculate an overall score by applying weights to each performance metric.

[0079] For example, a server can sometimes analyze multiple products simultaneously and select several products together, taking into account their complementary characteristics.

[0080] For example, the server can store data on the final selected product and use that information to inform future product development and marketing strategies.

[0081] In step S3 5 0, the server can automatically generate a marketability verification roadmap based on marketability test results data for at least one minimum-function product.

[0082] For example, the server can identify key components of a market validation roadmap based on marketability test results data. For instance, the main components of a market validation roadmap may include additional marketing campaigns, product improvements, and target market expansion plans.

[0083] For example, a server can establish detailed strategies for each component. For instance, the roadmap could include strategies such as resetting the target audience if interest is low, or adding discount promotions if purchase rates are high.

[0084] For example, the server can determine the timing of each strategy within a marketability validation roadmap and visualize the execution schedule. For instance, it could visualize the first marketing campaign taking place one month later, the second three months later, and product improvements being reflected six months later.

[0085] For example, the server defines the resources required for each strategy through a marketability roadmap. This includes resource allocation such as advertising budget, development personnel, and marketing personnel.

[0086] For example, the server can use generative artificial intelligence to adjust the market validation roadmap in real time in response to market reactions. For instance, if a product records a higher level of interest than expected, the server can use the generated artificial intelligence to instantly allocate additional marketing budgets or change the priorities of planned strategies.

[0087] According to one embodiment, a GRU (gated recurrent unit) model, a modified version of a reproducible neural network (RNN), can be used to automatically generate a marketability validation roadmap. Generally, RNNs can effectively model time-series information because hidden layer values ​​for existing inputs stored internally are considered in the output for the next input value. However, because RNNs have a structure that depends on past observations, problems can arise such as the disappearance of slopes or the presence of very large slope values. A model that solves this is the LSTM (long short-term memory network), where the nodes inside the LSTM are replaced with memory cells, allowing for the accumulation of information, the deletion of some past information, and other ways of compensating for the problems of RNNs. The GRU is a model that improves speed by simplifying the structure of such an LSTM.

[0088] For example, a GRU model may include a first input layer, one or more first hidden layers, and a first output layer. For instance, each training data set, consisting of multiple marketability test results and multiple ground truth marketability roadmaps, is input to the first input layer, passes through one or more first hidden layers and a first output layer to be output to a first output vector, the second output vector is input to a first layer of a first loss function connected to the first output layer, and a first loss value is output using a first loss function that compares one ground truth vector, and the parameters of the GRU model can be trained in a direction that reduces the first loss value.

[0089] For example, one or more first hidden layers may contain one or more GRU blocks, and one GRU block may contain a reset gate and an update gate. Here, the reset gate and update gate may contain a sigmoid layer. For example, the sigmoid layer may be, JPEG2026086324000002.jpg1756 This could be a layer where the activation function is . For example, a hidden state is controlled via a reset gate and an update gate, with each gate having a weight corresponding to its input.

[0090] Specifically, for example, the reset gate resets past information, and the weight r(t) derived through the previous hidden layer can be determined by Equation 1.

[0091]

number

[0092] For example, multiple marketability test result days and multiple ground truth marketability verification roadmaps are input to the input layer. The reset gate, upon receiving the current input value (xt) generated based on the values ​​input to the input layer, performs an inner product with the current weight Wr, and then performs an inner product with the previous time point's hidden state (h(t-1)) generated based on the values ​​input to the input layer, and finally, the two values ​​are summed and input to a sigmoid function, outputting the result as a value between 0 and 1. These values ​​between 0 and 1 can determine how much of the previous time point's hidden state value is utilized.

[0093] The update gate determines the rate of updating of past and present information, where z(t) is the amount of information at the present time, and can be determined by Equation 2.

[0094]

number

[0095] For example, when the current input value (xt) is input, it is dot-producted with the current weight W z, and the previous hidden state (h (t-1)) is dot-producted with the previous weight U z. Finally, the two values ​​are combined and input to the sigmoid function, resulting in a value between 0 and 1. Then, 1-z(t) can be multiplied by the information of the hidden layer from the previous time (h(t-1)).

[0096] This allows z(t) to reflect how much of the current information is used and how much of 1-z(t) is used for past information.

[0097] By multiplying by the result of the reset gate, the set of candidate information for the current time point t can be determined by equation (3).

[0098]

number

[0099] For example, when the current input value (xt) is input, the dot product of the current weight W h and the previous hidden state (h (t-1)) can be taken with the previous weight U h, multiplied by r(t), and the result can be input to the tanh function.

[0100] By combining the results of the update gate and the candidate group, the current weights of the hidden layer can be determined by equation (4).

[0101]

number

[0102] For example, the current weight of the hidden layer can be determined by the sum of the product of the update gate's output value z(t) and the current hidden state (h(t)), and the product of the value discarded by the update gate, 1-z(t), and the previous hidden state (h(t-1)).

[0103] In step S3 6 0, the server can provide the marketability verification roadmap to the customer terminal.

[0104] A customer company terminal may be a terminal of a customer company that has applied for a marketability test of its business model. For example, a customer company terminal may include the electronic device 101 shown in Figure 1.

[0105] Artificial intelligence models can be generated through machine learning. Such learning may be performed, for example, on the electronic device 101 on which the artificial intelligence model is run, or via a separate server (e.g., server 108). The learning algorithm may include, but is not limited to, guided learning, unguided learning, semi-guided learning, or reinforcement learning. The artificial intelligence model may include multiple artificial neural network layers. The artificial neural network may be, but is not limited to, one of the following: deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), restricted Boltzmann machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), or a combination of two or more deep neural networks. In addition to the hardware structure, the artificial intelligence model may include additional or alternative software structures.

[0106] Memory 130 can store various data used by at least one component of the electronic device 101 (e.g., processor 120 or sensor module 176). The data may include, for example, software (e.g., program 140) and input or output data for associated instructions. Memory 130 may include volatile memory 132 or non-volatile memory 134.

[0107] The program 140 can be stored as software in memory 130 and may include, for example, an operating system 142, middleware 144, or an application 146.

[0108] The input module 150 can receive instructions or data used by the components of the electronic device 101 (e.g., the processor 120) from outside the electronic device 101 (e.g., a user). The input module 150 may include, for example, a microphone, mouse, keyboard, keys (e.g., buttons), or a digital pen (e.g., a stylus pen).

[0109] The acoustic output module 155 can output an acoustic signal to the outside of the electronic device 101. The acoustic output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general applications such as multimedia playback and recording / playback. The receiver can be used to receive incoming phone calls. According to one embodiment, the receiver can be implemented separately from or as part of the speaker.

[0110] Information can be visually provided to an external party (e.g., a user) outside of the electronic device 101.

[0111] Audio module 170 can convert sound into electrical signals and, conversely, convert electrical signals into sound.

[0112] The sensor module 176 can sense the operating state of the electronic device 101 (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the sensed state. According to one embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0113] Interface 177 can support one or more designated protocols that can be used for the electronic device 101 to connect directly or wirelessly to an external electronic device (e.g., electronic device 102). According to one embodiment, interface 177 may include, for example, a high-resolution multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0114] The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (e.g., electronic device 102). According to one embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0115] According to one embodiment, commands or data can be transmitted to or received between the electronic device 101 and an external electronic device 104 via a server 108 connected to a second network 199. Each of the external electronic devices 102 or 104 may be the same or a different type of device as the electronic device 101. According to one embodiment, all or part of the operation performed by the electronic device 101 can be performed by one or more of the external electronic devices 102, 104, or 108. For example, if the electronic device 101 must automatically perform a function or service, or automatically in response to a request from a user or other device, the electronic device 101 may, instead of performing the function or service itself, or additionally, request one or more external electronic devices to perform at least part of that function or service. One or more external electronic devices that receive the request may perform at least part of the requested function or service, or additional functions or services related to the request, and communicate the results of the execution to the electronic device 101. The electronic device 101 may process the results as they are or additionally and provide them as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technologies can be used. The electronic device 101 can, for example, provide ultra-low latency services using distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an IoT (Internet of Swing) device. The server 108 may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device 104 or the server 108 can be included in the second network 199. The electronic device 101 can be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technologies.

[0116] The tactile module 179 can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that the user can perceive through touch or kinesthetic sense. According to one embodiment, the tactile module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0117] The camera module 180 can capture still images and video. According to one embodiment, the camera module 180 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0118] The power management module 188 can manage the power supplied to the electronic device 101. According to one embodiment, the power management module 188 can be implemented, for example, as at least part of a power management integration circuit (PMIC).

[0119] The battery 189 can supply power to at least one component of the electronic device 101. According to one embodiment, the battery 189 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0120] The communication module 190 can support the establishment of a direct (e.g., wired) or wireless communication channel between the electronic device 101 and an external electronic device (e.g., electronic device 102, electronic device 104, or server 108), and the execution of communication over the established communication channel. It may include one or more communication processors that support wireless communication. According to one embodiment, the communication module 190 includes a wireless communication module 192 (e.g., a cellular communication module, a near-field wireless communication module, or a GNSS (global navigation satellite system) communication module) or a wired communication module 194 (e.g., LAC). Of these communication modules, the corresponding communication module can communicate with a first network 198 (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network 199 (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network). Such a communication module can communicate with device 104 and can be integrated into a single component (e.g., a single chip) or implemented in multiple separate components (e.g., multiple chips). The electronic device 101 can be verified or authenticated within a communication network such as network 199.

[0121] The wireless communication module 192 can support 5G networks following 4G networks and next-generation communication technologies, such as NR connectivity technology. NR connectivity technology supports high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mmTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module 192 can, for example, support high-frequency bands (e.g., mmWave bands) to achieve high data rates. The wireless communication module 192 can support various technologies to ensure performance in high-frequency bands, such as beamforming, massive array multiple-input and multiple-output (massive MIMO (multiple-input and multiple-output)), full-dimension multiple-input and multiple-output (FD-MIMO), array antennas, analog beamforming, or large-scale antennas. The wireless communication module 192 can support various requirements specified by the electronic device 101, external electronic devices (e.g., electronic device 104), or network systems (e.g., second network 199). According to one embodiment, the wireless communication module 192 has a peak data rate of 0.5 for eMBB realization (e.g., 20 Gbps or more), loss coverage of 0.5 for mMTC realization (e.g., 164 dB or less), or U-plane latency (e.g., downlink (DL) and uplink (UL)) for URLRC realization.

[0122] The antenna module 197 can transmit or receive signals or power to an external device (e.g., an external electronic device). According to one embodiment, the antenna module 197 may include an antenna comprising a radiator consisting of a conductor or conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module 197 may include multiple antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication scheme used in a communication network, such as a first network 198 or a second network 199, can be selected from the multiple antennas, for example, by the communication module 190. Signals or power can be transmitted or received between the communication module 190 and an external electronic device via the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit) (RFIC) may be further formed as part of the antenna module 197.

[0123] According to various embodiments, the antenna module 197 can form an mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., the bottom surface) of the printed circuit board and capable of supporting a specified high-frequency band (e.g., the mmWave band), and an antenna (e.g., an array antenna) disposed on or above a plurality of frequency bands on a second surface (e.g., the top surface or side surface) of the printed circuit board.

[0124] At least some of the aforementioned components are connected to each other via a peripheral device communication method (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and can exchange signals (e.g., instructions or data) with each other.

[0125] According to one embodiment, commands or data can be transmitted to or received between the electronic device 101 and an external electronic device 104 via a server 108 connected to a second network 199. Each of the external electronic devices 102 or 104 may be the same or a different type of device as the electronic device 101. According to one embodiment, all or part of the operation performed by the electronic device 101 can be performed by one or more of the external electronic devices 102, 104, or 108. For example, if the electronic device 101 must automatically perform a function or service, or automatically in response to a request from a user or other device, the electronic device 101 may, instead of performing the function or service itself, or additionally, request one or more external electronic devices to perform at least part of that function or service. One or more external electronic devices that receive the request may perform at least part of the requested function or service, or additional functions or services related to the request, and communicate the results of the execution to the electronic device 101. The electronic device 101 may process the results as they are or additionally and provide them as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technologies can be used. The electronic device 101 can, for example, provide ultra-low latency services using distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an IoT (Internet of Swing) device. The server 108 may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device 104 or the server 108 can be included in the second network 199. The electronic device 101 can be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technologies.

[0126] Server 108 is connected to electronic devices 101 and can provide services to the connected electronic devices 101. Server 108 can also store and manage various information of users who have completed the membership registration process and have become members, and can provide various purchase and payment functions related to the service. Furthermore, Server 108 may share execution data of service applications running on multiple electronic devices 101 in real time so that users can share the service. Such a server 108 can have the same hardware configuration as a conventional web server or service server. However, in terms of software, it can be implemented through some language such as C, C++, Java, Python, Golang, or Kotlin, and can include program modules that perform various functions. Generally, Server 108 refers to a computer system and the computer software (server program) installed for this purpose that is connected to an unspecified number of clients and / or other servers via an open computer network such as the Internet, receives work requests from clients or other servers, derives and provides the results of those work. Furthermore, server 108 should be understood as a broader concept that includes not only the server program described above, but also a series of application programs running on server 108, and various databases (DB: Database, hereinafter referred to as "DB") that may be built internally or externally. Therefore, server 108 classifies and stores and manages member registration information and various information and data related to the game in the DB. This DB can be implemented internally or externally to server 108.Furthermore, Server 108 can be implemented using server programs provided by various operating systems such as Windows, Linux, Unix, and Macintosh on general-purpose server hardware. Typical examples include IIS (Internet Information Server), CUN, and NCPA used in Windows environments, which can be used to implement web services. Server 108 may also be linked to authentication and payment systems for user authentication of services and for purchase settlements related to services.

[0127] The first network 198 and the second network 199 refer to a connection structure that enables information exchange between each node, such as terminals and servers, or a network connecting server 108 and electronic devices 101 and 104. The first network 198 and the second network 199 include, but are not limited to, the Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), 3G, 4G, LTE, 5G, Wi-Fi, etc. The first network 198 and the second network 199 may be closed networks such as LAN and WAN, but it is preferable that they be open networks such as the Internet. The Internet refers to a global open computing network structure consisting of the TCP / IP protocol, TCP, UDP (user datagram protocol), and multiple services that exist at a higher layer, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), and SNMP (Simple Network Management Protocol).

[0128] A database can have a general data structure implemented in the storage space (hard disk or memory) of a computer system using a database management program (DBMS). A database can have a data storage form that allows for the free retrieval (extraction), deletion, editing, and addition of data. A database can be implemented for the purposes of one embodiment of this disclosure using relational database management systems (RDBMS) such as Oracle, Infomix, Sybase, and DB2, object-oriented database management systems (OODBMS) such as Gemston, Orion, and O2, and XML native databases such as Excelon Sekaiju, and can have appropriate fields or elements to achieve unique functionality.

[0129] This is a block diagram showing the configuration of a server according to one embodiment. One embodiment shown in Figure 4 can be combined with various embodiments of this disclosure.

[0130] As shown in Figure 4, the server 400 may include a processor 410, a communication unit 420, and memory 430. However, not all of the components shown in Figure 4 are essential components of the server 400. The server 400 can be implemented with more components than those shown in Figure 4, and can also be implemented with fewer components than those shown in Figure 4. For example, the server 400 in some embodiments includes a processor 410 and a communication unit 420. In addition to memory 430, it may further include a user input interface (not shown), an output unit (not shown), and so on.

[0131] The processor 410 typically controls the overall operation of the server 400. The processor 410 comprises one or more processors and can control other components included in the server 400. For example, the processor 410 can control the communication unit 420 and memory 430, etc., by executing a program stored in memory 430. The processor 410 can also perform the functions of the server 400 shown in Figure 3 by executing a program stored in memory 430.

[0132] The communication unit 420 may include one or more components that enable the server 400 to communicate with other devices (not shown) and other devices (not shown), which may be computing devices such as the server 400, or which can receive data stored in external devices via the other devices.

[0133] For example, the communication unit 420 can send and receive messages to establish a connection with at least one device. The communication unit 420 can transmit information generated by the processor 410 to at least one device connected to the server. The communication unit 420 can receive information from at least one device connected to the server. The communication unit 420 can transmit information related to the received information in response to the information received from at least one device.

[0134] Memory 430 can store programs for processing and controlling the processor 410. For example, memory 430 can store information input to the server or information received from other devices via the network. Furthermore, memory 430 can store data generated by the processor 410. Memory 430 can store information input to or output from the server 400.

[0135] Memory 430 may include at least one type of storage medium from among flash memory type, hard disk type, multimedia card micro type, card type memory (e.g., SD or XD memory), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk, and optical disk.

[0136] The embodiments described above can be implemented using hardware components, software components, and / or combinations of hardware and software components. They can be implemented using one or more general-purpose computers, such as programmable logic units (PLUs), microprocessors, or any other devices capable of executing and responding to instructions. While it may be stated for convenience that only one processing unit is used, a person with ordinary skill in the art will know that a processing unit can include multiple processing elements (and / or multiple types of processing elements). Processing configurations are also possible.

[0137] Artificial intelligence models can be generated through machine learning. Such learning may be performed, for example, on the electronic device 101 on which the artificial intelligence model is run, or via a separate server (e.g., server 108). The learning algorithm may include, but is not limited to, guided learning, unguided learning, semi-guided learning, or reinforcement learning. The artificial intelligence model may include multiple artificial neural network layers. The artificial neural network may be, but is not limited to, one of the following: deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), restricted Boltzmann machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), or a combination of two or more deep neural networks. In addition to the hardware structure, the artificial intelligence model may include additional or alternative software structures.

[0138] Memory 130 can store various data used by at least one component of the electronic device 101 (e.g., processor 120 or sensor module 176). The data may include, for example, software (e.g., program 140) and input or output data for associated instructions. Memory 130 may include volatile memory 132 or non-volatile memory 134.

[0139] The program 140 can be stored as software in memory 130 and may include, for example, an operating system 142, middleware 144, or an application 146.

[0140] The input module 150 can receive instructions or data used by the components of the electronic device 101 (e.g., the processor 120) from outside the electronic device 101 (e.g., a user). The input module 150 may include, for example, a microphone, mouse, keyboard, keys (e.g., buttons), or a digital pen (e.g., a stylus pen).

[0141] The acoustic output module 155 can output an acoustic signal to the outside of the electronic device 101. The acoustic output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general applications such as multimedia playback and recording / playback. The receiver can be used to receive incoming phone calls. According to one embodiment, the receiver can be implemented separately from or as part of the speaker.

[0142] Module 160 can visually provide information to an external party (e.g., a user) outside of the electronic device 101. The display module 160 may include, for example, a display, a hologram device, or a control circuit for controlling a projector and corresponding devices. According to one embodiment, the display module 160 may include a touch sensor configured to detect touches, or a pressure sensor configured to measure the intensity of the force generated by a touch.

[0143] The audio module 170 can convert sound into electrical signals, or conversely, convert electrical signals into sound. According to one embodiment, the audio module 170 can acquire sound via the input module 150, or output sound via the sound output module 155, or via an external electronic device (e.g., electronic device 102) (e.g., speaker or headphones) directly or wirelessly connected to the electronic device 101.

[0144] The sensor module 176 can sense the operating state of the electronic device 101 (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the sensed state. According to one embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0145] Interface 177 can support one or more designated protocols that can be used for the electronic device 101 to connect directly or wirelessly to an external electronic device (e.g., electronic device 102). According to one embodiment, interface 177 may include, for example, a high-resolution multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0146] The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (e.g., electronic device 102). According to one embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0147] The tactile module 179 can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that the user can perceive through touch or kinesthetic sense. According to one embodiment, the tactile module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0148] The camera module 180 can capture still images and video. According to one embodiment, the camera module 180 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0149] The power management module 188 can manage the power supplied to the electronic device 101. According to one embodiment, the power management module 188 can be implemented, for example, as at least part of a power management integration circuit (PMIC).

[0150] The battery 189 can supply power to at least one component of the electronic device 101. According to one embodiment, the battery 189 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0151] The communication module 190 can support the establishment of a direct (e.g., wired) or wireless communication channel between the electronic device 101 and an external electronic device (e.g., electronic device 102, electronic device 104, or server 108), and the execution of communication over the established communication channel. The communication module 190 operates independently of the processor 120 (e.g., the application processor) and may include one or more communication processors that support direct (e.g., wired) or wireless communication. According to one embodiment, the communication module 190 may include a wireless communication module 192 (e.g., a cellular communication module, a near-field wireless communication module, or a GNSS (global navigation satellite system) communication module) or a wired communication module 194 (e.g., a LAN (local area network) communication module, or a power line communication module). Of these communication modules, the corresponding communication module can communicate with a first network 198 (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network 199 (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network, e.g., an electronic device 104). Some of these types of communication modules may be integrated into a single component (e.g., a single chip) or implemented in multiple separate components (e.g., multiple chips). The wireless communication module 192 can verify or authenticate the electronic device 101 within a communication network such as the first network 198 or the second network 199 using subscriber information (e.g., an International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 196.

[0152] The wireless communication module 192 can support 5G networks following 4G networks and next-generation communication technologies, such as NR connectivity technology. NR connectivity technology supports high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mmTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module 192 can, for example, support high-frequency bands (e.g., mmWave bands) to achieve high data rates. The wireless communication module 192 can support various technologies to ensure performance in high-frequency bands, such as beamforming, massive array multiple-input and multiple-output (massive MIMO (multiple-input and multiple-output)), full-dimension multiple-input and multiple-output (FD-MIMO), array antennas, analog beamforming, or large-scale antennas. The wireless communication module 192 can support various requirements specified by the electronic device 101, external electronic devices (e.g., electronic device 104), or network systems (e.g., second network 199). According to one embodiment, the wireless communication module 192 has a peak data rate of 0.5 for eMBB realization (e.g., 20 Gbps or more), loss coverage of 0.5 for mMTC realization (e.g., 164 dB or less), or U-plane latency (e.g., downlink (DL) and uplink (UL)) for URLRC realization.

[0153] The antenna module 197 can transmit or receive signals or power to an external device (e.g., an external electronic device). According to one embodiment, the antenna module 197 may include an antenna comprising a radiator consisting of a conductor or conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module 197 may include multiple antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication scheme used in a communication network, such as a first network 198 or a second network 199, can be selected from the multiple antennas, for example, by the communication module 190. Signals or power can be transmitted or received between the communication module 190 and an external electronic device via the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit) (RFIC) may be further formed as part of the antenna module 197.

[0154] According to various embodiments, the antenna module 197 can form an mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., the bottom surface) of the printed circuit board and capable of supporting a specified high-frequency band (e.g., the mmWave band), and an antenna (e.g., an array antenna) disposed on or above a plurality of frequency bands on a second surface (e.g., the top surface or side surface) of the printed circuit board.

[0155] At least some of the aforementioned components are connected to each other via a peripheral device communication method (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and can exchange signals (e.g., instructions or data) with each other.

[0156] According to one embodiment, commands or data can be transmitted to or received between the electronic device 101 and an external electronic device 104 via a server 108 connected to a second network 199. Each of the external electronic devices 102 or 104 may be the same or a different type of device as the electronic device 101. According to one embodiment, all or part of the operation performed by the electronic device 101 can be performed by one or more of the external electronic devices 102, 104, or 108. For example, if the electronic device 101 must automatically perform a function or service, or automatically in response to a request from a user or other device, the electronic device 101 may, instead of performing the function or service itself, or additionally, request one or more external electronic devices to perform at least part of that function or service. One or more external electronic devices that receive the request may perform at least part of the requested function or service, or additional functions or services related to the request, and communicate the results of the execution to the electronic device 101. The electronic device 101 may process the results as they are or additionally and provide them as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technologies can be used. The electronic device 101 can, for example, provide ultra-low latency services using distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an IoT (Internet of Swing) device. The server 108 may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device 104 or the server 108 can be included in the second network 199. The electronic device 101 can be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technologies.

[0157] Server 108 is connected to electronic devices 101 and can provide services to the connected electronic devices 101. Server 108 can also store and manage various information of users who have completed the membership registration process and have become members, and can provide various purchase and payment functions related to the service. Furthermore, Server 108 may share execution data of service applications running on multiple electronic devices 101 in real time so that users can share the service. Such a server 108 can have the same hardware configuration as a conventional web server or service server. However, in terms of software, it can be implemented through some language such as C, C++, Java, Python, Golang, or Kotlin, and can include program modules that perform various functions. Generally, Server 108 refers to a computer system and the computer software (server program) installed for this purpose that is connected to an unspecified number of clients and / or other servers via an open computer network such as the Internet, receives work requests from clients or other servers, derives and provides the results of those work. Furthermore, server 108 should be understood as a broader concept that includes not only the server program described above, but also a series of application programs running on server 108, and various databases (DB: Database, hereinafter referred to as "DB") that may be built internally or externally. Therefore, server 108 classifies and stores and manages member registration information and various information and data related to the game in the DB. This DB can be implemented internally or externally to server 108.Furthermore, Server 108 can be implemented using server programs provided by various operating systems such as Windows, Linux, Unix, and Macintosh on general-purpose server hardware. Typical examples include IIS (Internet Information Server), CUN, and NCPA used in Windows environments, which can be used to implement web services. Server 108 may also be linked to authentication and payment systems for user authentication of services and for purchase settlements related to services.

[0158] The first network 198 and the second network 199 refer to a connection structure that enables information exchange between each node, such as terminals and servers, or a network connecting server 108 and electronic devices 101 and 104. The first network 198 and the second network 199 include, but are not limited to, the Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), 3G, 4G, LTE, 5G, Wi-Fi, etc. The first network 198 and the second network 199 may be closed networks such as LAN and WAN, but it is preferable that they be open networks such as the Internet. The Internet refers to a global open computing network structure consisting of the TCP / IP protocol, TCP, UDP (user datagram protocol), and multiple services that exist at a higher layer, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), and SNMP (Simple Network Management Protocol).

[0159] A database can have a general data structure implemented in the storage space (hard disk or memory) of a computer system using a database management program (DBMS). A database can have a data storage form that allows for the free retrieval (extraction), deletion, editing, and addition of data. A database can be implemented for the purposes of one embodiment of this disclosure using relational database management systems (RDBMS) such as Oracle, Infomix, Sybase, and DB2, object-oriented database management systems (OODBMS) such as Gemston, Orion, and O2, and XML native databases such as Excelon Sekaiju, and can have appropriate fields or elements to achieve unique functionality.

[0160] Software can include computer programs, code, instructions, or a combination of one or more of these, which can configure a processing unit to operate as desired, or which can instruct the processing unit independently or in combination. Software and / or data can be permanently or temporarily embodied in any kind of machine, component, physical device, virtual device, computer storage medium or device, or transmitted signal wave, in order to be interpreted by a processing unit or to provide instructions or data to a processing unit. Software can be distributed across a network of computer systems and stored or executed in a distributed manner. Software and data can be stored on one or more computer-readable recording media.

[0161] The methods according to the embodiments are carried out in the form of program instructions that can be executed via various computer means and can be recorded on computer-readable media. Hardware devices including interpreters and other devices that can execute high-level language codes, such as magnetic media, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program instructions such as ROMs, RAMs, and flash memory, may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

[0162] Although embodiments have been described above with limited drawings, a person with ordinary skill in the art can apply various technical modifications and variations based on the above. For example, the described techniques may be performed in a different order than described, and / or the components of the described systems, structures, devices, circuits, etc. may be combined or assembled in a different manner than described, or replaced or substituted by other components or equivalents, and still satisfactory results may be achieved.

[0163] Therefore, other embodiments, other forms, and those equivalent to the claims described below also fall within the scope of the claims.

Claims

[Claim 1] A roadmap for verifying the market viability of business models using generative artificial intelligence. The servers provided will be: At least one processor and Includes memory that stores instructions that tell at least one processor to perform at least one operation, The aforementioned at least one operation is, In conjunction with an external SNS platform server, it provides the SNS platform server with advertising data corresponding to each of the business model and its corresponding minimum performance product (MVP). We collect market response data corresponding to advertising data from SNS platform servers. Using artificial intelligence generated based on collected market response data, marketability test result data for minimal product features corresponding to advertising data is generated. Based on marketability test results data, select at least one of several minimum-function products. Based on marketability test results data for at least one minimal product, a marketability verification roadmap is automatically generated. This includes providing the above market feasibility verification roadmap to customer terminals. server.

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