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Expert system example

Expert System Examples - ITGS New

Expert System Examples. Expert systems are a key part of the ITGS HL topics, along with artificial intelligence and robotics. Diagnostics is a common function of expert systems, whether it be in the knowledge domain of car repairs, computer faults, or medicine Expert Systems: Examples Examples of expert systems in Python: Bagger.py: This file is an example of a simple rule-based system that describes how to pack items at a supermarket check-out Example : There are many examples of an expert system. Some of them are given below - MYCIN - One of the earliest expert systems based on backward chaining. It can identify various bacteria that can cause severe infections and can also recommend drugs based on the person's weight. DENDRAL Expert System - Examples 1. University of Education, Okara Campus 1 2. •In 1965 DENDRAL was used in expert system •MYCIN was developed in 1976 University of Education, Okara Campus 2 3

It is one of the best Expert System Example. DENDRAL: Expert system used for chemical analysis to predict molecular structure. PXDES: An Example of Expert System used to predict the degree and type of lung cancer. CaDet: One of the best Expert System Example that can identify cancer at early stages Shells − A shell is nothing but an expert system without knowledge base. A shell provides the developers with knowledge acquisition, inference engine, user interface, and explanation facility. For example, few shells are given below −. Java Expert System Shell (JESS) that provides fully developed Java API for creating an expert system Expert systems are used in many industries, occupations and commercial sectors — particularly in the developing world where experts may be thin on the ground. Examples include agriculture, education, environment, law, manufacturing, medicine, power systems, tax assessments and loan applications The performance of an expert system is based on the expert's knowledge stored in its knowledge base. The more knowledge stored in the KB, the more that system improves its performance. One of the common examples of an ES is a suggestion of spelling errors while typing in the Google search box Example expert systems Medicine MYCIN (1976) Identification of bacteria in blood and urine samples; prescription of antibiotics INTERNIST / CADUCEUS (1970s / 1984) Diagnosis of majority of diseases in field of internal medicine PUFF (1979) Interpretation of respiratory tests for diagnosis of pulmonary disorders BABY (19??) Patient monitoring in a newbor

An expert system is an example of a knowledge-based system.Expert systems were the first commercial systems to use a knowledge-based architecture. In general view, an expert system includes the following components: a knowledge base, an inference engine, an explanation facility, a knowledge acquisition facility, and a user interface.. The knowledge base represents facts about the world. In. Here's an Expert System example - when one thinks about making use of an expert system in AI to leverage profits for a business, ROSS is the expert system that often comes up. It is an Artificial Intelligence-based attorney that uses a variety of techniques to mimic human intelligence Shells − A shell is nothing but an expert system without knowledge base. A shell provides the developers with knowledge acquisition, inference engine, user interface, and explanation facility. For example, few shells are given below − Java Expert System Shell JESS that provides fully developed Java API for creating an expert system EXAMPLES OF ES IN MEDICAL (1) PXDES <ul><li>It is example of medical expert system. </li></ul><ul><li>It is a lung disease, X-ray diagnosis. </li></ul><ul><li>It takes our lungs picture from upper side of body which looks like a shadow. </li></ul><ul><li>The shadow is used to determine the type and degree of harmness. </li></ul><ul><li>These systems include three modes: </li></ul><ul><li>The knowledge base </li></ul><ul><li>The explanation interface </li></ul><ul><li>The knowledge.

Expert Systems Examples . There are numerous examples of expert systems. Some of them are: MYCIN: This was one of the earliest expert systems that was based on backward chaining. It has the ability to identify various bacteria that cause severe infections. It is also capable of recommending drugs based on a person's weight One example of an expert system is an artificial intelligence system that emulates an auto mechanic's knowledge in diagnosing automobile problems. This hypothetical expert system would likely be the result of engineering using an actual mechanic's knowledge base For example, CLIPS can also integrated with android to create expert system apps. Expert Systems can also be used in websites to give desired results based on user preferences. It is an artificially intelligent Expert System that suggests food items based user preference of different tastes Qutuf (قُطُوْف): An Arabic Morphological analyzer and Part-Of-Speech tagger as an Expert System

Expert systems are proficient in reasoning, classification, configuration, pattern matching, diagnosis, and planning, certain industries are set up for disruption. Financial services, healthcare, customer service, aviation, and written communication can all be carried out by expert systems. The first expert system to be approved by the American Medical Association was the Pathfinder system. Built at Stanford University in the 1980s, this decision-theoretic expert system was built for. An example of an expert advisory system is MoreCrop, which stands for Managerial Options for Reasonable Economical Control of Rusts and Other Pathogens. MoreCrop is designed to provide disease management options in different geographic regions and agronomic zones of the Pacific Northwest using the vast information available on wheat. The system uses HTML, CSS and Javas... This is an example of a partially completed Expert System (ES). This video shows the back box (UI) only and not the code An expert system is an advanced computer application that is implemented for the purpose of providing solutions to complex problems, or to clarify uncertainties through the use of non-algorithmic programs where normally human expertise will be needed. Expert systems are most common in complex problem domain and are considered as widely used alternatives in searching Continue readin Practical expert systems within each of these application areas do exist [1]. The purpose of this paper is primarily to explore and illustrate the concepts and The bicycle repair expert system is a typical example of a diagnostics application. Through a question and answer dialogue with the user the system wil

Video: Expert Systems: Examples - GitHu

Expert Systems - GeeksforGeek

Exsys Corvid Expert System Demos. EXSYS has customers worldwide who have developed and deployed thousands of Knowledge Automation Expert Systems. Many of these systems are proprietary, classified or for other reasons not publicly available. However, the following are some sample systems built with Exsys Corvid that can be run online For example, ROSIE has special commands which let a ROSIE expert system talk to the local operating system just as if it were a user on the system. This feature of operating system accessibility allows the expert system to monitor and control other jobs while it is running for example, it can run a simulation program written in another language. The most common example of this class is maintenance expert, which retrieves detailed information on part of a machine as and when they are required. In short, it can be said that the expert system is very much essential for the business organization First installment in the Play then Program series for while True: learn()!We start out going in the game to find out when expert systems have real-world uses.. expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires human expertise. The first expert system was developed in 1965 by Edward Feigenbaum and Joshua Lederberg of Stanford University in California, U.S. Dendral, as their expert system was later known, was designed to analyze chemical compounds

Expert System - Examples - SlideShar

Expert systems are set up in 5 steps (using 3 components). These steps can be abbreviated to IKIUT: Experts in a field are interviewed and their knowledge is collected. All of the knowledge collected from the experts is organised and stored in the knowledge base. This allows the knowledge base to be searched by the user For example, a patient might display signs of an infection to the doctor, who might suspect that it is blood-related but requires more information from a trusted knowledge base — the online medical expert system. Among the uses for medical expert systems could be to determine whether a patient should leave the general practitioner's office. For example, expert systems now help diagnose illnesses, search for minerals, analyze compounds, recommend repairs, and do financial planning. Expert systems can support either operations or management activities. Expert Systems Structure The components of an expert system include a knowledge base an

For example a small expert system is under development to diagnose signals from an inductive loop detector tester which when completed will demonstrate the practicality if imbedding an expert system in testing hardware. Other current applications range from bridge rail retrofit design systems. Expert Systems 4 understand the reasons for a program's conclusions. This capability is especially important when end-users accept legal, moral, or financial responsibility for actions taken on the program'srecommendations. 1.2. Some Examples There are many expert systems in routine use (see[Rauch-Hindin 86],[Buchanan 86],[Walker and Miller 86],[Harmon &King85]forlists ofexamples) An expert system (ES) These systems are used, for example, to control manufacturing processes. 11.5 Expert System Technology [Figure 11.6] There are several levels of ES technologies available. Two important things to keep in mind when selecting ES tools include: 1. The tool selected for the project has to match the capability and. Expert systems are often used in complex problem-solving programs. These typically require intelligence and human decisions, which take considerable time to evaluate. The systems use pre-defined rules to determine behaviors or outcomes of specific events. The rules can be modified to support future changes, if necessary, due to unexpected. However, these rule-based expert systems are prone to issues of inability to learn, ineffective search strategy, opaque relations between rules, and so on. Fuzzy Expert System A Fuzzy Expert System is a gathering of membership functions and fuzzy rules. These functions and rules are used to reason concerning the data

A Business Expert System (BES) is a knowledge based information system, which is based on artificial intelligence. A Knowledge Based information system adds a knowledge base that uses its knowledge about a specific, complex application area to act as an expert.. Also, BES provides decision support to managers in the form of advice from an expert in a specific problem area such as medical. The fuzzy expert system is a form of problem solving used by a computer system, often used in the creation of artificial intelligence. Expert systems are types of decision-making computer software based on Boolean logic, meaning that the system uses a series of yes or no answers to try and solve a problem. Fuzzy expert systems expand on the traditional expert system and are based in fuzzy. 0. 44 613. The principles of MQL4-programs development are shown on sample of creating a simple Expert Advisor system based on the standard MACD indicator. In this Expert Advisor, we will also see examples of implementing such features as setting take profit levels with the support of trailing stop as well as the most means ensuring safe work Picking a block that you know you can successfully model in an expert system gives your staff a visible example of the value and operation of expert systems, and increases their confidence in.

What is Expert System in AI (Artificial Intelligence

Experts make decisions based on qualitative & quantitative information. The system engineer has to translate the standard procedures into the form suitable for the expert system. Acquiring the knowledge from experts is a complex task that often is a bottleneck in expert system construction Knowledge engineer and Domain expert Knowledge engineer: A knowledge engineer is a computer scientist who knows how to design and implement programs that incorporate artificial intelligence techniques. Domain Expert: A domain expert is an individual who has significant expertise in the domain of the expert system being developed

Artificial Intelligence - Expert System

Komponen Expert System. User Interface digunakan manajer untuk memasukkan instruksi dan informasi dari sistem. Metode input yang digunakan oleh manajer yaitu: · Menu. · Command. · Natural Language. · Output Expert System memakai 2 bentuk penjelasan (explanation) : · Explanation of Question. · Explanation of Problem Solution Other Key Terms used in Expert System. Apart from the expert system components listed above, the following terms are also extensively used when discussing expert systems. Facts and rules - A fact is a small piece of important knowledge. Facts have limited use. An expert system selects the rules to solve a problem

or Boolean. For example, the slot Name has symbolic values, and the slot Age numeric values. Slot values can be assigned when the frame is created or during a session with the expert system. Typical information included in a slo An expert system (ES) is a computer program designed to solve procedural problems. Knowledge is represented in a expert system as frames, or data structures, and rules, which encode the procedural rules for problem-solving. This article overviews expert systems, explains how they work, and cites numerous examples. It describes artificial neural networks (NNs) and inference engines and offers a.

Elements of an Expert System • User interface - mechanism by which user and system communicate. • Exploration facility - explains reasoning of expert system to user. • Working memory - global database of facts used by rules. • Inference engine - makes inferences deciding which rules are satisfied and prioritizing Therefore, the professionals use an expert system which studies the existing processes, the goals to be achieved and then suggest actions that should be undertaken to achieve the goals. 3. Monitoring and control. The expert system's job here is to constantly analyse the real-time data that is incoming from the various devices Hybrid expert system is the combination of two or more types of intelligent systems. Prominently, there are two types in hybrid expert systems. The first one is neural expert systems and the second one is neuro-fuzzy systems. Neural expert system combines the features of rule based expert system along with neural network features Expert System is an intuitive and dependable PC based dynamic framework that utilizes the two realities and heuristics to take care of complex dynamic issues. An expert system in AI may be a computing system that emulates the decision-making ability of a person's expert problems with which expert systems are concerned, it may be more useful to employ heuristics: strategies that often lead to the correct solution, but that also sometimes fail. Conventional rule-based expert systems, use human expert knowledge to solve real-world problems that normally would require human intelligence. Expert

Expert Systems Types - Ecommerce Diges

6.2 Essential components of an expert system 110 6.3 The essential features, perceived requirements and 112 motivation for developing an expert system 6.4 The role of an expert system and its responsibility 114 6.5 Knowledge acquisition 115 6.6 Conceptual model of expert systems development 120 6.7 Summary 12 This chapter introduces the basic concepts of an expert system. You'll see how to insert and remove facts in CLIPS. Introduction CLIPS is a type of computer language designed for writing applications called expert systems. An expert system is a program which is specifically intended to model human expertise or knowledge Expert Systems for Python. Migrating from Pyknow. Experta is a Pyknow fork. Just replace any pyknow references in your code/examples to experta and everything should work the same The second part of the expert system determines which disease has the greatest probability of affecting the patient by using the technique of knowledge base systems. This disease is choosen among the selected diseases. For example, if the first part gives only one disease, the second part does nothing but confirming this choice

Expert systems are software programs, that store knowledge extracted from human experts . Expert systems thus appear to mimic human experts in a particular field or domain such as tax or auditing. Early expert systems focused on expert emulation, attempting to replicate the behavior and decisions of human experts. I Medical expert systems generally include two components: (1) a knowledge base (KB), which encapsulates the evidence-based medical knowledge that is curated by experts, and (2) a rule-based. Using their general understanding of the problem they use the facts to derive a conclusion. This process is referred to as reasoning. Expert systems model the reasoning process of humans using a technique called inferencing (Durkin, 1994). An expert system's inference engine controls the application of knowledge from the knowledgeable The expert system should have an explanation capability similar to the reasoning ability of human experts. 5. Adequate Response time: The system should be designed in such a way that it is able to perform within a small amount of time, comparable to or better than the time taken by a human expert to reach at a decision point

Expert Systems in Artificial Intelligence - Javatpoin

  1. An expert system is a computer program that provides expert-level solutions to 'important problems and is: In the example, we see the system asking questions to obtain a description of a new case, and we see the system providing an explanation of its line of reasoning
  2. The clarification feature answers these Questions by reference to system targets, data input and decision rules.For example, in the case of evaluation of loan proposal, the explanation of the expert system will be clarified on the facility inquiry Why an application was approved and why the other was rejected
  3. Rather than re-inventing the wheel, I'd suggest you to use some readily available solution. There are several expert systems out there and I'll focus on those which are either in Python or can be used via Python. CLIPS. CLIPS is an expert system originally developed by NASA. It's considered state of the art and used in university courses when.

An Expert system can be viewed as having two environments[10,16]: the system development environment in which the ES is constructed and the consultation environment which describes how advice is rendered to the users (Fig. 1) expert system how a particular conclusion is reached and why a specific fact is needed § The user interface is the means of communication between a user seeking a solution to the problem and an expert system . B219 Intelligent Systems Week 5 Lecture Notes page 10 of 10. An expert system must be able to explain its reasoning and justify its advice, analysis or conclusion. User interface. The user interface is the means communication between a user seeking a solution to the problem and an expert system. Complete structure of a rule-based expert system

20. It is difficult to get the hands to work until the cotton is fully opened, and it is hard to induce them to pick over ioo lb a day, though some expert hands are found in every cotton plantation who can pick twice as much. 7. 5. He loved riding and walking, was an expert swimmer and enjoyed a game at tennis Expert System. A computer application that performs a task that would otherwise be performed by a human expert. For example, there are expert systems that can diagnose human illnesses, make financial forecasts, and schedule routes for delivery vehicles. Some expert systems are designed to take the place of human experts, while others are. artificial intelligence - artificial intelligence - Expert systems: Expert systems occupy a type of microworld—for example, a model of a ship's hold and its cargo—that is self-contained and relatively uncomplicated. For such AI systems every effort is made to incorporate all the information about some narrow field that an expert (or group of experts) would know, so that a good expert. 1. Introduction. An expert system is a computer system that emulates the decision making ability of a human expert [1] . By so doing, it acts in all respects like a human expert, using human knowledge to solve problems that would require human intelligence

I have to add a functionality to an already existing expert system, that is to manage questions with different types of answers, not Boolean, but for example multiple choice answers. In the knowledge. Expert System Software. Vanguard Software. Example of commercial system illustrating typical uses. 4. Expert Systems: The Structure and Construction of Knowledge-Based Systems. AITopics. Basic, readily-understood information about AI. 5. Rule-Based Expert Systems by Bruce G. Buchanan and Edward H. Shortliffe. AITopics. MYCIN Experiments of the. figure 1. Development of an Expert System for Agricultural Commodities. A. Dath, P. Blair, M. Balakrishnan. 2013. An Expert System is a system that employs human knowledge captured in a computer to solve problems that ordinarily require human expertise. In agriculture, expert systems unite the accumulated. Expand Answer (1 of 3): My own company did an expert system that enabled subject matter experts who were not computer scientists to create high-performance computing applications for heterogeneous platforms (things that mix processor technologies). It was done under contract to the US Air Force. Go ge.. Expert systems are typically very domain specific. For example, a diagnostic expert system for troubleshooting computers must actually perform all the necessary data manipulation as a human expert would. The developer of such a system must limit his or her scope of the system to just what is needed to solve the target problem

Expert systems automate difficult technical inferences and knowledge lookups in return for a front-loaded investment of time and effort. For example, ROSS, a legal system powered by IBM Watson combines an enormous knowledge base with more modern ways of filtering for relevant information from the field of natural language processing Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The thrust of the journal is to publish papers dealing with the design, development, testing, implementation, and/or management of expert and intelligent systems, and also to provide.

Expert system - Wikipedi

  1. components of a categorical expert system, by means of a simple example in Prolog. Two well-known systems, MYCIN and . PROSPECTOR, which reason under uncertainty, are then described. Chapter 5 explains an alternative knowledge representation: the descrip­.
  2. of using an expert system (a system with intelligent reasoning) above a conventional information system (for example a system without intelligent reasoning) are: • It improves the quality of the system. The program will function even with incomplete and uncertain data from the very first time it executes previously non-programmable tasks. This i
  3. The leading platform to prepare for systems design interviews. Master fundamental systems topics, sharpen your design skills, and land your dream job with SystemsExpert
  4. An expert system is a computer application that can think like an expert and solve complex problems related to a specific field. Just like qualified professionals use their knowledge and experience to give advice, an expert system is a computer-based system that uses both facts and heuristics to provide solutions

A troubleshooting system with such capabilities is ultimately a type of expert system. A limitation of traditional expert systems lies in the complexities of adding and modifying knowledge and. UNESCO - EOLSS SAMPLE CHAPTERS EXERGY, ENERGY SYSTEM ANALYSIS AND OPTIMIZATION - Vol. III - Expert Systems and Knowledge Acquisition - Roberto Melli ©Encyclopedia of Life Support Systems (EOLSS) 3.1. Acquisition of Knowledge is a formidable Problem in itsel good expert system application (for example, O'leary [1986]), thus providing empiri­ cal support for those theoretical observations. In particular, each system is based on a set of audit concerns about highly specific environments, each of the systems are the concern of a large number ofauditors, each system operates in a PC environment an

Here is an example of an expert system for decision making coded in SWI-Prolog. It takes a sample portfolio, a current asset price list and a risk tolerance profile it can then make decisions regrading selling financial assets based on specific strategy being applied For example, a junior accountant is asked to enter a number of details about a financial statement using a series of questions, and the expert system presents a number of inconsistencies or points. Feigenbaum EXPERT SYSTEMS IN THE 1980s INTRODUCTION In the space allottedone can only briefly summarise what there is to say about expert systems-where we are and where we willgo in the 1980s-and point the reader to references. Examples willbe given of modern work on expert systems, butonly inbrief- est description. Some of these (perhaps more thana fair share) willbe drawn fro

Expert System in AI: Architecture, Types, Examples

  1. In a fuzzy expert system, the inference process is a combination of four subprocesses: _fuzzification_, _inference_, _composition_, and _defuzzification_. The defuzzification subprocess is optional. For the sake of example in the following discussion, assume that the variables x, y, and z all take on values in the interval [ 0, 10 ], and that.
  2. Expert systems are a type of symbolic AI as they completely rely on knowledge-base enveloping facts, data, and 'if-this-then-that' rules. For this reason, AI expert systems are directed towards solving complex reasoning problems while exhibiting human-level intelligence and expertise
  3. mark on the expert systems that have been developed since. Even today, this expert system and its derivatives are a source of inspiration for expert system researchers. 2. Expert System Principles As an expert system is a software system, the structure of expert systems can b
  4. Expert System. An Expert System is a concept of the Artificial intelligence (AI) representing a computer based system. This system depicts the abilities of a human expert and has the decision making capabilities. • This system is based on the application of knowledge for solving the complex problems or tasks rather than following the fixed procedures or methods
  5. In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, like an expert through the application of knowledge and rules. The first expert systems were created in the 1970's

6.expert systems - SlideShar

  1. 5 Forward Chaining. This chapter discusses a forward chaining rule based system and its expert system applications. It shows how the forward chaining system works, how to use it, and how to implement it quickly and easily using Prolog. A large number of expert systems require the use of forward chaining, or data driven inference
  2. 4. Learning and training of users is the fact that the expert system is always an excellent teacher for all users, not only in the relevant expertise, but also the natural way by explaining the reasoning. Even expert system has the support and collaboration can take advantage of expert system. 5. Potential commercial management of expert.
  3. Expert system can advice, modifies, update, expand & deals with uncertain and irrelevant data. [6]. analyzes and processes the rules. matching antecedents from the responses given by the users and 3. ARCHITECTURE OF AN EXPERT SYSTEM An expert system tool, or shell, is a software development environment containing the basic components of expert.
  4. Heuristic DENDRAL (later shortened to DENDRAL) was a chemical-analysis expert system. The substance to be analyzed might, for example, be a complicated compound of carbon, hydrogen, and nitrogen. Starting from spectrographic data obtained from the substance, DENDRAL would hypothesize the substance's molecular structure
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Expert Systems in Artificial Intelligence (AI) : Types

  1. The database is typically created by a human expert, and as such, the extent of knowledge that an expert system contains is typically confined to that of the human providing the content. For example, a medical diagnosis expert system may contain a knowledge-base consisting of many different facts about diseases, symptoms, and conditions
  2. Expert System; It facilitates decision-making. It automates decision-making. The decision environment is unstructured. The decision environment have structure. It extracts or gains knowledge from a computer system. Inject expert knowledge in to a computer system. Characteristics of the problem domain is complex and broad
  3. Examples of semantics: How semantics processes a text. External stimuli: Information sources—text documents, web pages, social media and emails, etc.—while potentially diverse in terms of content and context, are nonetheless information that must be 'processed' to be understood. Neurons: These are the pieces that make up the semantic.
  4. Expert Systems: An Introduction K S R Anjaneyulu is a Research Scientist in the Knowledge Based Computer Systems Group at NeST. He is one of the For example, in a TV troubleshooting expert system, the WM could contain the details of the particular TV being looked at
  5. Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the Expert Systems with Applications citation style
  6. Expert: Has the special knowledge, judgement, experience and methods to give advice and solve problems. Provides knowledge about task performance. Knowledge Engineer: Usually also the System Builder. Helps the expert (s) structure the problem area by interpreting and integrating human answers to questions, drawing analogies, posing counter.
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Generally, Expert System in AI users and ES itself uses User interface as a medium of interaction between users. Also, the user of the Expert Systems need not be necessarily an expert in Artificial Intelligence. Although, at a particular recommendation, it explains how the Expert Systm has arrived. Hence, the explanation may appear in the. Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic. Toggle navigation ? users online users online. Logout; Open hangout; Open chat for current fil For example, MYCIN was an early expert system for medical diagnosis and EMYCIN was an inference engine extrapolated from MYCIN and made available for other researchers. As expert systems moved from research prototypes to deployed systems there was more focus on issues such as speed and robustness Expert knowledge systems are often made private to serve a company's team or a department. For example, the customer support department can use an expert knowledge system to quickly find answers to common customer problems. This type of knowledge bases includes expert guides made on specific topics Expert.ai's platform will automatically enrich news content with descriptive metadata to provide AP clients with enhanced search and discovery options. Transform Insurance Processes with AI. Artificial Intelligence is a reality. The cognitive computing solutions of expert.ai enhance our efficiency and effectiveness and thus help us to improve.