{"id":20600,"date":"2021-11-16T01:45:00","date_gmt":"2021-11-16T01:45:00","guid":{"rendered":"https:\/\/sagaciousresearch.com\/blog\/?p=20600"},"modified":"2023-04-04T11:53:20","modified_gmt":"2023-04-04T11:53:20","slug":"understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions","status":"publish","type":"post","link":"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions","title":{"rendered":"Understanding Artificial Intelligence (AI) And The Need To Patent AI Inventions"},"content":{"rendered":"\n<p>Artificial Intelligence has changed the world in ways unimaginable. From reducing human labor and time \u2013 to making hazardous tasks seem like a piece of cake; AI has surely disrupted the general scheme of things. Today, there is probably no sphere wherein AI does not find any application. Be it Amazon\u2019s Alexa or Google\u2019s Siri, AI has transformed how things get done. With the growth in applications of AI, IP system encourages innovations in the area of AI that are created by humans. The future holds potential for Artificial Intelligence, and it is definitely going to scale new heights. Which is why, one must grab every chance to patent AI inventions.<\/p>\n\n\n\n<p>This article discusses the underlying technology behind the workings of Artificial Intelligence, its algorithms, and different types. It also discusses the need to patent AI technologies, the AI trend and how describing technical effects of the AI invention can lead to AI patent grant.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_81 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69da0077bf17a\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69da0077bf17a\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Types_of_AI\" >Types of AI<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Artificial_Intelligence_type_1_%E2%80%93_Based_on_Capabilities\" >Artificial Intelligence type 1 &#8211; Based on Capabilities<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Artificial_Intelligence_type_2_%E2%80%93_Based_on_Functionality\" >Artificial Intelligence type 2 &#8211; Based on Functionality<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Agents_and_environments\" >Agents and environments<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#The_Algorithm\" >The Algorithm<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Patenting_AI_inventions\" >Patenting AI inventions<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Challenges_in_protecting_AI_inventions\" >Challenges in protecting AI inventions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Strategy_to_overcome_the_challenges\" >Strategy to overcome the challenges<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Making_AI_invention_functionality_practical\" >Making AI invention functionality practical<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Rising_Trend_for_patenting_AI_inventions\" >Rising Trend for patenting AI inventions<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Conclusion\" >Conclusion<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/sagaciousresearch.com\/blog\/understanding-artificial-intelligence-and-the-need-to-patent-ai-inventions\/#Having_Queries_Contact_Us_Now\" >Having Queries? Contact Us Now!<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\" id=\"types-of-ai\"><span class=\"ez-toc-section\" id=\"Types_of_AI\"><\/span>Types of AI<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Artificial Intelligence can be broadly categorized into <a href=\"https:\/\/www.forbes.com\/sites\/cognitiveworld\/2019\/06\/19\/7-types-of-artificial-intelligence\/?sh=7f8ab9ca233e\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">two types<\/a> &#8211; based on capabilities and the other based on functionality.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"artificial-intelligence-type-1-based-on-capabilities\"><span class=\"ez-toc-section\" id=\"Artificial_Intelligence_type_1_%E2%80%93_Based_on_Capabilities\"><\/span>Artificial Intelligence type 1 &#8211; Based on Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Based on Capabilities, AI can be further subdivided into:<\/p>\n\n\n\n<p><strong>1.<\/strong> <strong>Narrow or weak AI: <\/strong>Narrow or Weak Artificial Intelligence encompasses almost all the existing AIs. It refers to such AI machines that perform a specific task autonomously. Such AI systems have limited or narrow competencies. Narrow or Weak AIs find application in a number of fields. Many smartphone applications include features such as face recognition, voice-based personal assistants, a search tool, etc. Other applications include vision recognition in self-driving vehicles, recommendation engines suggesting products based on purchase history, or the like. These features are goal-oriented and singular tasks that have narrow parameters and contexts. The narrow AI does not mimic or replicate human intelligence and merely simulates human behaviour on a narrow range of parameters and contexts.<\/p>\n\n\n\n<p><strong>2.<\/strong> <strong>General or strong AI: <\/strong>It is a concept of a machine with general intelligence that mimics human intelligence and\/or human behaviour, with the ability to learn and apply its intelligence to solve any problem. This strong AI uses a theory of mind AI framework, which refers to the ability to discern needs, emotions, beliefs, and thought processes of other intelligent entitles. The theory of mind-level AI is not about replication or simulation but about training machines to truly understand humans.<\/p>\n\n\n\n<p>One of the most notable attempts at achieving strong AI is Fujitsu-built \u201cK-computer.\u201d However, considering&nbsp;<a href=\"https:\/\/www.cnet.com\/news\/fujitsu-supercomputer-simulates-1-second-of-brain-activity\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">it took 40 minutes to simulate a single second of a neural activity<\/a>, it is difficult to determine whether or not the strong AI will be achieved in the foreseeable future. As image and facial recognition technology advances, there may be an improvement in the ability of machines to learn and see.<\/p>\n\n\n\n<p><strong>3. Artificial superintelligence: <\/strong>Artificial superintelligence is a hypothetical AI that does not just mimic or understand human intelligence and behaviour. It is where machines become self-aware and surpass the capacity of human intelligence and ability. Artificial superintelligence, while able to replicate the capabilities of human beings, would be exceedingly better because of its overwhelmingly greater memory.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"artificial-intelligence-type-2-based-on-functionality\"><span class=\"ez-toc-section\" id=\"Artificial_Intelligence_type_2_%E2%80%93_Based_on_Functionality\"><\/span>Artificial Intelligence type 2 &#8211; Based on Functionality<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p><strong>1.<\/strong> <strong>Reactive Machines<\/strong>: Mostly basic and rather primitive, these AI systems have limited capabilities. These machines do not have memory storage, and they try to react to the present stimuli as per possible best action. This also means that they do not have the capability to learn. They cannot \u201clearn\u201d from their past experiences and therefore cannot use them to better their present actions. These machines can only be trusted for responding to a limited set of instructions. They cannot \u2018improve\u2019 their operations based on their memory. One famous example of such an AI machine is IBM\u2019s Deep Blue, the one that beat Grandmaster Garry Kasparov in Chess.<\/p>\n\n\n\n<p><strong>2. Limited Memory<\/strong>: Limited memory machines are capable of learning from past experiences and storing data but for a very short duration of time. These can be thought of as improvements over reactive AI machines. In addition to functioning as a reactive machine, it is also capable of learning from its past. It uses its past memory and volumes of data to train itself for solving future problems.<\/p>\n\n\n\n<p><strong>3. Theory of Mind<\/strong>: Although researchers are still engaged in innovating, this new type of machine is believed to have \u201chuman-like\u201d emotions, beliefs and would be able to behave just like humans in society. While the previous-mentioned machines are a reality, this type of AI system is still a concept. It is the next level of AI system that is still a \u2018work under progress.\u2019<\/p>\n\n\n\n<p><strong>4.<\/strong> <strong>Self-Aware<\/strong>: These types of machines exist only hypothetically. Believed to be the future of Artificial Intelligence, these super-intelligent machines will have their own consciousness and would be extremely \u201cself-aware,\u201d just like Human Beings or even better.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"agents-and-environments\"><span class=\"ez-toc-section\" id=\"Agents_and_environments\"><\/span>Agents and environments<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p><a href=\"https:\/\/www.tutorialspoint.com\/artificial_intelligence\/artificial_intelligence_agents_and_environments.htm#:~:text=An%20AI%20system%20is%20composed%20of%20an%20agent,sensors%20and%20acts%20upon%20that%20environment%20through%20effectors.\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Agent and Environment<\/a> are two significant portions of any AI. Before we begin to understand how an AI works, it is crucial to grasp an understanding of \u201can agent and an environment.\u201d An agent is something that can perceive while an environment is what it perceives. An agent perceives the environment through sensors and acts upon it through effectors. Examples of the agent include a program, a chatbot, a robot, etc. A \u2018human agent\u2019 has its sensory organs as \u2018sensors\u2019 and organs such as legs and hands as effectors. Similarly, a \u2018robotic agent\u2019 has cameras and infrared sensors that are parallel to sensors, while it has motors and actuators for effectors.<\/p>\n\n\n\n<p>The agent and environment vary depending on application areas. For instance, in the case of a robot in a room, the robot is the agent while the room is the environment. Similarly, in the case of a vehicle on the road, the vehicle is the agent while the latter is the environment. Likewise, in the case of a software program, the program is the agent while the data and rules are the environment.<\/p>\n\n\n\n<p>Thus, the agent is basically a solution for solving a problem, i.e., the environment. In order to work in the environment, the agent needs intelligence, which is where the AI comes into the picture. The AI helps in designing an \u201cagent program\u201d for the agent. The agent program runs on a computation device that is equipped with sensors and actuators. This agent program with the architecture that comprises the sensors and the actuators contributes a structure to the agent. Architecture is the machinery on which execution is done by the agent, while an agent program is an implementation of an agent function.<\/p>\n\n\n\n<p>That is,<\/p>\n\n\n\n<p>Agent = Architecture + agent program<\/p>\n\n\n\n<p>An example of the agent program is the \u201cautonomous driving\u201d program for \u201cautonomous vehicle\u201d equipped with computers, sensors, or the like, which is the architecture. The sensors in the architecture perceive \u2018sensor data\u2019 from the environment. The sensor data is inputted to the agent program for returning \u201cactions\u201d that are performed via the actuators.<\/p>\n\n\n\n<p>Based on the interaction between the agent and the environment and its applicability, agents can be categorized into different types:<\/p>\n\n\n\n<ol class=\"wp-block-list\" type=\"i\">\n<li>Simple-reflex agent<\/li>\n\n\n\n<li>Model-based reflex agent<\/li>\n\n\n\n<li>Goal-based agent<\/li>\n\n\n\n<li>Utility-based agent<\/li>\n\n\n\n<li>&nbsp;Learning agent <\/li>\n<\/ol>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"667\" height=\"292\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-22.png\" alt=\"\" class=\"wp-image-20612\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-22.png 667w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-22-300x131.png 300w\" sizes=\"(max-width: 667px) 100vw, 667px\" \/><figcaption class=\"wp-element-caption\"><strong>Types of Agents<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>1. The <strong>simple-reflex agent<\/strong> works on the condition-action rule. It receives <a href=\"https:\/\/en.wikipedia.org\/wiki\/Percept_(artificial_intelligence)\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">percepts<\/a> from the environment via the sensors and performs actions in a fully observable environment based on the said rule. \u201cPercepts\u201d are inputs that an intelligent agent is receiving at any moment. The condition-action rule refers to the fulfillment of action in response to a condition. For example, a room cleaner agent works only where there is dirt in a room. In other words, for a room-cleaner to perform its \u2018action,\u2019 there should be dirt in the room, which is the necessary \u2018condition.\u2019<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"376\" height=\"243\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-23.png\" alt=\"\" class=\"wp-image-20614\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-23.png 376w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-23-300x194.png 300w\" sizes=\"(max-width: 376px) 100vw, 376px\" \/><figcaption class=\"wp-element-caption\"><strong>Simple-reflex agent<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>The simple-reflex agent is rather simplistic in nature. It has limited intelligence with no capability to adapt to changes in the environment. This inefficiency may be overcome by the model-based reflex agent.<\/p>\n\n\n\n<p>2. The <strong>model-based reflex agent<\/strong> uses a model (knowledge about the environment) to perform actions in a partially observable environment. This model is the information about \u201chow are things in the world right now.\u201d It also maintains an internal state that represents the current situation or current state based on a percept history. The percept history is a history of all that the agent has perceived to date. The state is updated based on information of how the world evolves and how the agent\u2019s actions affect the world.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"382\" height=\"223\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-24.png\" alt=\"\" class=\"wp-image-20616\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-24.png 382w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-24-300x175.png 300w\" sizes=\"(max-width: 382px) 100vw, 382px\" \/><figcaption class=\"wp-element-caption\"><strong>Model-based reflex agent<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>There may be a time when the knowledge of the current state of the environment may not always be sufficient for the agent to decide what actions are to be performed unless there is a goal to achieve. The capabilities of the model-based agent can be further expanded to the goal-based agent.<\/p>\n\n\n\n<p>3. A <strong>goal-based agent<\/strong> is comparatively more flexible than reflex-based agents or model-based agents: the reason being an explicit modeling of the knowledge supporting a decision. A goal describes a set of desirous situations. The goal-based agent knows its goal that describes desirable situations and has the capability to select an action for achieving the goal. For this, the goal-based agent performs searching and planning to select the action from a long sequence of possible actions. The selected action that the goal-based agent performs is intended to reduce its distance from the goal, which makes the agent proactive.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"403\" height=\"241\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-25.png\" alt=\"\" class=\"wp-image-20618\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-25.png 403w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-25-300x179.png 300w\" sizes=\"(max-width: 403px) 100vw, 403px\" \/><figcaption class=\"wp-element-caption\"><strong>Goal-based agent<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>Sometimes, the goal achieved by the goal-based agent may not be the best as the world is uncertain. So, a measure of success for achieving the goal may be helpful to determine the best way to achieve a goal.<\/p>\n\n\n\n<p>4. The <strong>utility-based agent<\/strong> is similar to that of the goal-based agent with a capability for utility measurement. The utility measurement gives a measure of success at a given state for achieving the goal. That is, the utility-based agent has the capability to select actions based on the utility for each state such that the expected utility is maximized. In particular, the utility describes how&nbsp;\u201chappy\u201d&nbsp;the agent is that may be determined using a <a href=\"https:\/\/stackoverflow.com\/questions\/40372897\/what-is-the-difference-between-a-performance-measure-and-a-utility-function\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">utility function<\/a>. The utility function maps a state onto a real number which describes the associated degree of happiness.&nbsp;<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"418\" height=\"259\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-26.png\" alt=\"\" class=\"wp-image-20620\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-26.png 418w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-26-300x186.png 300w\" sizes=\"(max-width: 418px) 100vw, 418px\" \/><figcaption class=\"wp-element-caption\"><strong>Utility-based agent<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>The environment is not only uncertain, but it can be dynamic too. As the environment expands, amount of tasks to be performed by the agent may also increase. This may require the agent to learn new actions so as to work in environments that are unknown, which results in another type of agent, i.e., the learning agent.<\/p>\n\n\n\n<p>5. The <strong>learning agent<\/strong> has learning capabilities to learn from past experiences and act with basic knowledge. Eventually, the learning agent builds the ability to act and adapt automatically through learning. In particular, the learning agent has a learning element to learn from the environment, a critic component to take feedback from critics that describes how well the agent is performing based on a predefined performance standard, a performance element to select an action and a problem generator to suggest actions that will lead to new and informative experiences.<\/p>\n\n\n\n<p>The learning agent, therefore, learns, analyzes performance, and looks for new ways to improve.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"418\" height=\"298\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-27.png\" alt=\"\" class=\"wp-image-20622\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-27.png 418w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-27-300x214.png 300w\" sizes=\"(max-width: 418px) 100vw, 418px\" \/><figcaption class=\"wp-element-caption\"><strong>Learning Agent<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"the-algorithm\"><span class=\"ez-toc-section\" id=\"The_Algorithm\"><\/span>The Algorithm<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In order to fully understand what runs an AI machine, it is imperative to know an AI\u2019s algorithm. Simply put, algorithms are step-by-step instructions that a machine or system needs in order to perform the desired function. One should think of it as an instruction manual that lets a machine know exactly what to do and when to do it. Artificial intelligence is powered by algorithms, using techniques such as machine learning, deep learning and data science.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"392\" height=\"269\" src=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-28.png\" alt=\"\" class=\"wp-image-20624\" srcset=\"https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-28.png 392w, https:\/\/sagaciousresearch.com\/blog\/wp-content\/uploads\/2021\/11\/1-28-300x206.png 300w\" sizes=\"(max-width: 392px) 100vw, 392px\" \/><figcaption class=\"wp-element-caption\"><strong>Algorithm of Artificial Intelligence<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n<p>Machine learning (ML) algorithms feed data to an AI system using statistical techniques. The statistical techniques enable the AI system to learn and progressively improve at performing tasks without having to be specifically programmed to do so. Programming concepts, such&nbsp;as&nbsp;functional programming, attribute-based programming,&nbsp;and&nbsp;object-oriented programming may be used to program an application to react to every input and output, which has downsides. In a real-world scenario, there are too many inputs and outputs that may not be predictable. The predictability may be achieved through machine learning algorithms.<\/p>\n\n\n\n<p>A large amount of data is fed to machine learning algorithms as input data. Initially, the input data is pre-processed, i.e., cleaned to remove unwanted or redundant data and achieve an accurate outcome. The Machine learning algorithms crunch the input data and produce a model that has \u201crules\u201d created based on the input data. Further, the validity of the model may be tested. For instance, if there is 100% of the input data, then the data is split into, say 70% of data for creating the model and 30% of test data for testing that evaluating the model. A model based on the 70% data is created. The 30% of test data is then played against the model, predicting values and determining how accurate the predictions are. Furthermore, the data may be randomized to a new subset of data for improving the results. All these steps of pre-processing data (structured or semi-structured), selecting appropriate machine learning algorithms, and creating right parameters for creating the most accurate set of data, are achieved through data science techniques.<\/p>\n\n\n\n<p>The input data fed to the ML algorithms may be of different modalities, such as: image, video, audio, etc. The different modality of data may be unstructured and unlabelled that are processed and analysed using deep learning techniques, without the need for human labelling. This can be achieved using neural networks, such as artificial neural networks that mimic how human brain works. The neural networks help in finding patterns in data, recognizing the relationship between variables, clustering, and classification.<\/p>\n\n\n\n<p>Nowadays, deep learning and neural networks are at the forefront of AI research and may hold the key to a future where AI can function at levels that are unheard of today. With the rise in AI applications, patenting AI-related applications has also increased.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"patenting-ai-inventions\"><span class=\"ez-toc-section\" id=\"Patenting_AI_inventions\"><\/span>Patenting AI inventions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>AI invention patents are needed to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>protect technical innovations and technical solutions to problems<\/li>\n\n\n\n<li>Prevent others from exploiting an inventor\u2019s AI invention<\/li>\n\n\n\n<li>help the inventor mark out legal exclusivity around a patented product<\/li>\n\n\n\n<li>earn a good return on investment through licensing of the patented product<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"challenges-in-protecting-ai-inventions\"><span class=\"ez-toc-section\" id=\"Challenges_in_protecting_AI_inventions\"><\/span>Challenges in protecting AI inventions<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Most of the AI-related applications, such as the core AI involve advanced mathematics and mathematical models. This challenges eligibility for patent protection of the AI inventions.<\/li>\n\n\n\n<li>In AI inventions that are related to the trained AI models, claiming variations and ranges may be challenging. There may be objections if buzzwords and marketing terms are used for the trained AI models in claims.<\/li>\n\n\n\n<li>Lack of technical information or insufficient of technical information to define or describe technical effects of the AI invention<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"strategy-to-overcome-the-challenges\"><span class=\"ez-toc-section\" id=\"Strategy_to_overcome_the_challenges\"><\/span>Strategy to overcome the challenges<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Most of the AI inventions face a patentability issue due to use of computer systems and algorithms. Also, law surrounding subject matter eligibility rapidly evolves which adds the factor of patentability issue.<\/p>\n\n\n\n<p>In January 2019, the USPTO issued \u201c<a href=\"https:\/\/www.govinfo.gov\/content\/pkg\/FR-2019-01-07\/pdf\/2018-28282.pdf\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Revised Patent Subject Matter Eligibility Guidance<\/a>\u201d to address the changes in law and stem the many patent application rejections. In October 2019, an updated of the revised subject matter eligibility guidance \u201c<a href=\"https:\/\/www.uspto.gov\/sites\/default\/files\/documents\/peg_oct_2019_update.pdf\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Patent Eligibility Guidance Update<\/a>\u201d&nbsp;was released. In the updated revised subject matter eligibility guidance, \u201c<a href=\"https:\/\/www.uspto.gov\/sites\/default\/files\/documents\/101_examples_37to42_20190107.pdf\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">examples<\/a>\u201d&nbsp;are included that help in formulating a strategy for overcoming the challenges. Since the release of January 2019 guidelines, rejections of AI related patent applications have <a href=\"https:\/\/news.bloomberglaw.com\/ip-law\/fewer-ai-patents-rejected-after-agencys-guidance-iancu-says\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">dropped<\/a> from 60% to about 32%.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"making-ai-invention-functionality-practical\"><span class=\"ez-toc-section\" id=\"Making_AI_invention_functionality_practical\"><\/span>Making AI invention functionality practical<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>The AI invention directed to method should have technical means, like a machine, such as a computer or a device to add a technical character to its subject matter as a whole and prevent the AI invention from being an \u201cabstract\u201d that may exclude from patentability.<\/p>\n\n\n\n<p>For example: if the AI invention is to improve a technique for analysing data such as, improves K-nearest neighbours (kNN) classification with no advantage to a technical field, then the AI invention may face rejection. However, if the AI invention applies kNN classification to achieve a specific improvement to a specific technical system then chances of obtaining a patent protecting the AI invention increases.<\/p>\n\n\n\n<p>Thus, a complete description of technical features describing technical effects of the AI invention frames the AI invention in a way to convince patent offices to grant a patent.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"rising-trend-for-patenting-ai-inventions\"><span class=\"ez-toc-section\" id=\"Rising_Trend_for_patenting_AI_inventions\"><\/span>Rising Trend for patenting AI inventions<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>In a U.S. Patent and Trademark Office (USPTO) report titled \u201c<a href=\"https:\/\/www.uspto.gov\/sites\/default\/files\/documents\/OCE-DH-AI.pdf\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Inventing AI: Tracing the diffusion of AI with U.S patents<\/a>\u201d, it is mentioned that AI technologies and systems as defined by the U.S. National Institute of Standards and Technology (NIST) \u201ccomprise software and\/or hardware that can learn to solve complex problems, make predictions or undertake tasks that require human-like sensing (such as vision, speech, and touch), perception, cognition, planning, learning, communication, or physical action.\u201d<\/p>\n\n\n\n<p>There is a shift in the patenting behaviour from theoretical to practical applications. The trend of AI related inventions shifting from theory to practical implementation can be seen from the <a href=\"https:\/\/www.wipo.int\/edocs\/pubdocs\/en\/wipo_pub_1055.pdf\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">WIPO Technology Trends 2019 \u2013 Artificial Intelligence<\/a> report. The report states that<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>40% of AI-related patents correspond to machine learning technique<\/li>\n\n\n\n<li>49% of AI-related patents correspond to computer vision<\/li>\n\n\n\n<li>42% of AI-related patents correspond are used in telecom, transportation or life sciences.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"conclusion\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Intelligence is perceived as the \u201ccapacity to think and solve problems.\u201d This capacity, which used to be the sole prerogative of humans is not limited to us \u2013 as intelligence can also be demonstrated by machines or computers, also popularly known as \u201cArtificial Intelligence\u201d or \u201cAI\u201d. With advanced development in technology, AI is increasingly driving important developments across many fields and industries. In most of the applications, AI is used to assist, reduce, or eliminate human involvement in existing processes. Some of the popular applications of AI are autonomous vehicles, advanced manufacturing processes, medical diagnostic tools, e-commerce, etc. It is making an impact on the scale and speed of innovation in almost all areas.<\/p>\n\n\n\n<p>Sagacious IP, a leader in global IP research and consulting, has helped multiple clients secure AI patents. We have an adept team of over 300 professionals who specialize in various domains. <a href=\"https:\/\/sagaciousresearch.com\/patent-drafting\">Click here<\/a> to know more. At Sagacious, IP professionals have expert skills for drafting computer-implemented inventions involving AI-related application. We ensure that the drafts for such computer-implemented inventions involving AI-related application include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Technical solution to a technical problem<\/li>\n\n\n\n<li>Clear identification of technical advantageous features and why they are advantageous.<\/li>\n\n\n\n<li>A disclosure of at least one set of training data and details of how it has been trained<\/li>\n\n\n\n<li>Illustration through examples or use cases that describe how the technical problem is solved.<\/li>\n<\/ul>\n\n\n\n<p>&#8211; Oinam Binarani Devi (ICT Drafting) and the Editorial Team<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Having_Queries_Contact_Us_Now\"><\/span>Having Queries? Contact Us Now!<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\nvar gform;gform||(document.addEventListener(\"gform_main_scripts_loaded\",function(){gform.scriptsLoaded=!0}),document.addEventListener(\"gform\/theme\/scripts_loaded\",function(){gform.themeScriptsLoaded=!0}),window.addEventListener(\"DOMContentLoaded\",function(){gform.domLoaded=!0}),gform={domLoaded:!1,scriptsLoaded:!1,themeScriptsLoaded:!1,isFormEditor:()=>\"function\"==typeof InitializeEditor,callIfLoaded:function(o){return!(!gform.domLoaded||!gform.scriptsLoaded||!gform.themeScriptsLoaded&&!gform.isFormEditor()||(gform.isFormEditor()&&console.warn(\"The use of gform.initializeOnLoaded() is deprecated in the form editor context and will be removed in Gravity Forms 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gfield--no-description field_description_below field_validation_below gfield_visibility_visible\"  ><label class='gfield_label gform-field-label' for='input_203_1'>Last Name<span class=\"gfield_required\"><span class=\"gfield_required gfield_required_asterisk\">*<\/span><\/span><\/label><div class='ginput_container ginput_container_text'><input name='input_1' id='input_203_1' type='text' value='' class='large'     aria-required=\"true\" aria-invalid=\"false\"   \/><\/div><\/div><div id=\"field_203_12\" class=\"gfield gfield--type-text gfield--input-type-text gfield--width-half gfield_contains_required field_sublabel_below gfield--no-description field_description_below field_validation_below gfield_visibility_visible\"  ><label class='gfield_label gform-field-label' for='input_203_12'>First Name<span class=\"gfield_required\"><span class=\"gfield_required gfield_required_asterisk\">*<\/span><\/span><\/label><div class='ginput_container ginput_container_text'><input name='input_12' id='input_203_12' type='text' value='' class='large'     aria-required=\"true\" aria-invalid=\"false\"   \/><\/div><\/div><div id=\"field_203_8\" class=\"gfield gfield--type-email gfield--input-type-email gfield--width-half gfield_contains_required field_sublabel_below gfield--no-description field_description_below field_validation_below gfield_visibility_visible\"  ><label class='gfield_label gform-field-label' for='input_203_8'>Your Work Email<span class=\"gfield_required\"><span class=\"gfield_required gfield_required_asterisk\">*<\/span><\/span><\/label><div class='ginput_container ginput_container_email'>\n                            <input name='input_8' id='input_203_8' type='email' value='' class='large'    aria-required=\"true\" aria-invalid=\"false\"  \/>\n                        <\/div><\/div><div id=\"field_203_9\" class=\"gfield gfield--type-phone gfield--input-type-phone gfield--width-half gfield_contains_required field_sublabel_below gfield--no-description field_description_below field_validation_below gfield_visibility_visible\"  ><label class='gfield_label gform-field-label' for='input_203_9'>Phone Number with Country Code<span class=\"gfield_required\"><span class=\"gfield_required gfield_required_asterisk\">*<\/span><\/span><\/label><div class='ginput_container ginput_container_phone'><input name='input_9' id='input_203_9' type='tel' value='' class='large'   aria-required=\"true\" aria-invalid=\"false\"   \/><\/div><\/div><div id=\"field_203_17\" class=\"gfield gfield--type-select gfield--input-type-select gfield--width-half gfield_contains_required field_sublabel_below gfield--no-description field_description_below field_validation_below gfield_visibility_visible\"  ><label class='gfield_label gform-field-label' for='input_203_17'>Country<span class=\"gfield_required\"><span class=\"gfield_required gfield_required_asterisk\">*<\/span><\/span><\/label><div class='ginput_container ginput_container_select'><select name='input_17' id='input_203_17' class='large gfield_select'    aria-required=\"true\" aria-invalid=\"false\" ><option value='' >Please Select Country<\/option><option value='United States' >United States<\/option><option value='Canada' >Canada<\/option><option value='United Kingdom' >United Kingdom<\/option><option value='China' >China<\/option><option value='India' >India<\/option><option value='North Korea' >North Korea<\/option><option value='South korea' >South korea<\/option><option value='United Arab Emirates' >United Arab Emirates<\/option><option value='Afghanistan' >Afghanistan<\/option><option value='Albania' >Albania<\/option><option value='Algeria' >Algeria<\/option><option value='Andorra' >Andorra<\/option><option value='Angola' >Angola<\/option><option value='Antigua and Barbuda' >Antigua and Barbuda<\/option><option value='Argentina' >Argentina<\/option><option value='Armenia' >Armenia<\/option><option value='Australia' >Australia<\/option><option value='Austria' >Austria<\/option><option value='Azerbaijan' >Azerbaijan<\/option><option value='The Bahamas' >The Bahamas<\/option><option value='Bahrain' >Bahrain<\/option><option value='Bangladesh' >Bangladesh<\/option><option value='Barbados' >Barbados<\/option><option value='Belarus' >Belarus<\/option><option value='Belgium' >Belgium<\/option><option value='Belize' >Belize<\/option><option value='Benin' >Benin<\/option><option value='Bhutan' >Bhutan<\/option><option value='Bolivia' >Bolivia<\/option><option value='Bosnia and Herzegovina' >Bosnia and Herzegovina<\/option><option value='Botswana' >Botswana<\/option><option value='Brazil' >Brazil<\/option><option value='Brunei' >Brunei<\/option><option value='Bulgaria' >Bulgaria<\/option><option value='Burkina Faso' >Burkina Faso<\/option><option value='Burundi' >Burundi<\/option><option value='Cabo Verde' >Cabo Verde<\/option><option value='Cambodia' >Cambodia<\/option><option value='Cameroon' >Cameroon<\/option><option value='Central African Republic' >Central African Republic<\/option><option value='Chad' >Chad<\/option><option value='Chile' >Chile<\/option><option value='Colombia' >Colombia<\/option><option value='Comoros' >Comoros<\/option><option value='Congo' >Congo<\/option><option value='Costa Rica' >Costa Rica<\/option><option value='C\u00f4te d\u2019Ivoire' >C\u00f4te d\u2019Ivoire<\/option><option value='Croatia' >Croatia<\/option><option value='Cuba' >Cuba<\/option><option value='Cyprus' >Cyprus<\/option><option value='Czech Republic' >Czech Republic<\/option><option value='Denmark' >Denmark<\/option><option value='Djibouti' >Djibouti<\/option><option value='Dominica' >Dominica<\/option><option value='Dominican Republic' >Dominican Republic<\/option><option value='East Timor (Timor-Leste)' >East Timor (Timor-Leste)<\/option><option value='Ecuador' >Ecuador<\/option><option value='Egypt' >Egypt<\/option><option value='El Salvador' >El Salvador<\/option><option value='Equatorial Guinea' >Equatorial Guinea<\/option><option value='Eritrea' >Eritrea<\/option><option value='Estonia' >Estonia<\/option><option value='Eswatini' >Eswatini<\/option><option value='Ethiopia' >Ethiopia<\/option><option value='Fiji' >Fiji<\/option><option value='Finland' >Finland<\/option><option value='France' >France<\/option><option value='Gabon' >Gabon<\/option><option value='The Gambia' >The Gambia<\/option><option value='Georgia' >Georgia<\/option><option value='Germany' >Germany<\/option><option value='Ghana' >Ghana<\/option><option value='Greece' >Greece<\/option><option value='Grenada' >Grenada<\/option><option value='Guatemala' >Guatemala<\/option><option value='Guinea' >Guinea<\/option><option value='Guinea-Bissau' >Guinea-Bissau<\/option><option value='Guyana' >Guyana<\/option><option value='Haiti' >Haiti<\/option><option value='Honduras' >Honduras<\/option><option value='Hungary' >Hungary<\/option><option value='Iceland' >Iceland<\/option><option value='Indonesia' >Indonesia<\/option><option value='Iran' >Iran<\/option><option value='Iraq' >Iraq<\/option><option value='Ireland' >Ireland<\/option><option value='Israel' >Israel<\/option><option value='Italy' >Italy<\/option><option value='Jamaica' >Jamaica<\/option><option value='Japan' >Japan<\/option><option value='Jordan' >Jordan<\/option><option value='Kazakhstan' >Kazakhstan<\/option><option value='Kenya' >Kenya<\/option><option value='Kiribati' >Kiribati<\/option><option value='Kosovo' >Kosovo<\/option><option value='Kuwait' >Kuwait<\/option><option value='Kyrgyzstan' >Kyrgyzstan<\/option><option value='Laos' >Laos<\/option><option value='Latvia' >Latvia<\/option><option value='Lebanon' >Lebanon<\/option><option value='Lesotho' >Lesotho<\/option><option value='Liberia' >Liberia<\/option><option value='Libya' >Libya<\/option><option value='Liechtenstein' >Liechtenstein<\/option><option value='Lithuania' >Lithuania<\/option><option value='Luxembourg' >Luxembourg<\/option><option value='Madagascar' >Madagascar<\/option><option value='Malawi' >Malawi<\/option><option value='Malaysia' >Malaysia<\/option><option value='Maldives' >Maldives<\/option><option value='Mali' >Mali<\/option><option value='Malta' >Malta<\/option><option value='Marshall Islands' >Marshall Islands<\/option><option value='Mauritania' >Mauritania<\/option><option value='Mauritius' >Mauritius<\/option><option value='Mexico' >Mexico<\/option><option value='Micronesia' >Micronesia<\/option><option value='Moldova' >Moldova<\/option><option value='Monaco' >Monaco<\/option><option value='Mongolia' >Mongolia<\/option><option value='Montenegro' >Montenegro<\/option><option value='Morocco' >Morocco<\/option><option value='Mozambique' >Mozambique<\/option><option value='Myanmar (Burma)' >Myanmar (Burma)<\/option><option value='Namibia' >Namibia<\/option><option value='Nauru' >Nauru<\/option><option value='Nepal' >Nepal<\/option><option value='Netherlands' >Netherlands<\/option><option value='New Zealand' >New Zealand<\/option><option value='Nicaragua' >Nicaragua<\/option><option value='Niger' >Niger<\/option><option value='Nigeria' >Nigeria<\/option><option value='North Macedonia' >North Macedonia<\/option><option value='Norway' >Norway<\/option><option value='Oman' >Oman<\/option><option value='Pakistan' >Pakistan<\/option><option value='Palau' >Palau<\/option><option value='Panama' >Panama<\/option><option value='Papua New Guinea' >Papua New Guinea<\/option><option value='Paraguay' >Paraguay<\/option><option value='Peru' >Peru<\/option><option value='Philippines' >Philippines<\/option><option value='Poland' >Poland<\/option><option value='Portugal' >Portugal<\/option><option value='Qatar' >Qatar<\/option><option value='Romania' >Romania<\/option><option value='Russia' >Russia<\/option><option value='Rwanda' >Rwanda<\/option><option value='Saint Kitts and Nevis' >Saint Kitts and Nevis<\/option><option value='Saint Lucia' >Saint Lucia<\/option><option value='Saint Vincent and the Grenadines' >Saint Vincent and the Grenadines<\/option><option value='Samoa' >Samoa<\/option><option value='San Marino' >San Marino<\/option><option value='Sao Tome and Principe' >Sao Tome and Principe<\/option><option value='Saudi Arabia' >Saudi Arabia<\/option><option value='Senegal' >Senegal<\/option><option value='Serbia' >Serbia<\/option><option value='Seychelles' >Seychelles<\/option><option value='Sierra Leone' >Sierra Leone<\/option><option value='Singapore' >Singapore<\/option><option value='Slovakia' >Slovakia<\/option><option value='Slovenia' >Slovenia<\/option><option value='Solomon Islands' >Solomon Islands<\/option><option value='Somalia' >Somalia<\/option><option value='South Africa' >South Africa<\/option><option value='Spain' >Spain<\/option><option value='Sri Lanka' >Sri Lanka<\/option><option value='Sudan' >Sudan<\/option><option value='South Sudan' >South Sudan<\/option><option value='Suriname' >Suriname<\/option><option value='Sweden' >Sweden<\/option><option value='Switzerland' >Switzerland<\/option><option value='Syria' >Syria<\/option><option value='Taiwan' >Taiwan<\/option><option value='Tajikistan' >Tajikistan<\/option><option value='Tanzania' >Tanzania<\/option><option value='Thailand' >Thailand<\/option><option value='Togo' >Togo<\/option><option value='Tonga' >Tonga<\/option><option value='Trinidad and Tobago' >Trinidad and Tobago<\/option><option value='Tunisia' >Tunisia<\/option><option value='Turkey' >Turkey<\/option><option value='Turkmenistan' >Turkmenistan<\/option><option value='Tuvalu' >Tuvalu<\/option><option value='Uganda' >Uganda<\/option><option value='Ukraine' >Ukraine<\/option><option value='Uruguay' >Uruguay<\/option><option value='Uzbekistan' >Uzbekistan<\/option><option value='Vanuatu' >Vanuatu<\/option><option value='Vatican City' >Vatican City<\/option><option value='Venezuela' >Venezuela<\/option><option value='Vietnam' >Vietnam<\/option><option value='Yemen' >Yemen<\/option><option value='Zambia' 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