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Mule Meetup Pune - August 2019
1.
[08/31/2019]: [MuleSoft And
Artificial Intelligence] [Pune Meetup]
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MuleSoft Inc. Agenda 2 • Introductions • What is Artificial Intelligence • Intelligent Application with Mulesoft and AI • [MuleSoft and AI Application] • What’s next • Networking time
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MuleSoft Inc. Your Organizer 3 Niranjan Joshi Santosh Ojha Seemant Jain Vijay Pande Mukesh Thakur A SHOW OF HANDS: Who is new to this Meetup? Manish Yadav
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MuleSoft Inc. INTRODUCTION TO AI
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MuleSoft Inc. Lets First Understand How We Think (Human Intelligence) 5 • What is Intelligence ? • How you play chess? • How you play cards? • How you drive a car? • How you recognize voices of your relatives and friends?
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MuleSoft Inc. Intelligence 6 • Intelligence has been defined in many ways, including: the capacity for logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem solving. More generally, it can be described as the ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context. • Intelligence is most often studied in humans but has also been observed in both non-human animals and in plants. Intelligence in machines is called artificial intelligence, which is commonly implemented in computer systems using programs and, sometimes, appropriate hardware.
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MuleSoft Inc. 7 What is Artificial Intelligence? “The art of creating machines that perform functions that require intelligence when performed by people.” (Kurzweil) “The study of how to make computers do things at which, at the moment, people are better.” (Rich and Knight)
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MuleSoft Inc. 8 Humans perceive by patterns whereas the machines perceive by set of rules and data. Humans store and recall information by patterns, machines do it by searching algorithms. For example, the number 40404040 is easy to remember, store, and recall as its pattern is simple. Humans can figure out the complete object even if some part of it is missing or distorted; whereas the machines cannot do it correctly. Difference between Human and Machine Intelligence
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MuleSoft Inc. 9
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MuleSoft Inc. 10 • What Contributes to AI? • Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving.
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MuleSoft Inc. 11 • The domain of artificial intelligence is huge in breadth and width. While proceeding, we consider the broadly common and prospering research areas in the domain of AI −
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MuleSoft Inc. Real Life Applications of Research Areas 12 There is a large array of applications where AI is serving common people in their day-to-day lives
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MuleSoft Inc. Task Classification of AI 13 The domain of AI is classified into Formal tasks, Mundane tasks, and Expert tasks.
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MuleSoft Inc. How AI works 14 • In our IoT and Mulesoft Meet up ,we discussed about sensors and Actuators,So sensors take data from External enviroment and feed to AI engine and Actuators performs the action after reacving signal from AI engine • Mechatronics- mechanics, electronics and computing which, combined, make possible the generation of simpler, more economical, reliable and versatile systems. • Cybernetics- the study of communication and control, typically involving regulatory feedback, in living organisms, in machines, and in combinations of the two.
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MuleSoft Inc. Agents and Environment 15 • An AI system is composed of an agent and its environment. The agents act in their environment. The environment may contain other agents. • What are Agent and Environment? • An agent is anything that can perceive its environment through sensors and acts upon that environment through effectors. • A human agent has sensory organs such as eyes, ears, nose, tongue and skin parallel to the sensors, and other organs such as hands, legs, mouth, for effectors. • A robotic agent replaces cameras and infrared range finders for the sensors, and various motors and actuators for effectors. • A software agent has encoded bit strings as its programs and actions.
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MuleSoft Inc. Programming Algorithm, Fuzzy logic in AI 16 • Searching • Searching is the universal technique of problem solving in AI. There are some single-player games such as tile games, Sudoku, crossword, etc. The search algorithms help you to search for a particular position in such games.
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MuleSoft Inc. Example of search Algorithms 17 • Breadth-First Search • It starts from the root node, explores the neighboring nodes first and moves towards the next level neighbors. It generates one tree at a time until the solution is found. It can be implemented using FIFO queue data structure. • Depth-First Search • It is implemented in recursion with LIFO stack data structure. It creates the same set of nodes as Breadth-First method, only in the different order. • Bidirectional Search • Uniform Cost Search • Iterative Deepening Depth-First Search • Informed (Heuristic) Search Strategies • To solve large problems with large number of possible states, problem-specific knowledge needs to be added to increase the efficiency of search algorithms.
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MuleSoft Inc. Fuzzy Logic Systems 18 • Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO. • The conventional logic block that a computer can understand takes precise input and produces a definite output as TRUE or FALSE, which is equivalent to human’s YES or NO. • The inventor of fuzzy logic, Lotfi Zadeh, observed that unlike computers, the human decision making includes a range of possibilities between YES and NO, such as − • fuzzy logic works on the levels of possibilities of input to achieve the definite output. • Fuzzy Logic Systems Architecture • It has four main parts as shown − • Fuzzification Module − It transforms the system inputs, which are crisp numbers, into fuzzy sets. It splits the input signal into five steps such as −
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MuleSoft Inc. Fuzzy Logic Systems four main parts 19 • Fuzzification Module − It transforms the system inputs, which are crisp numbers, into fuzzy sets. It splits the input signal into five steps such as − •Knowledge Base − It stores IF-THEN rules provided by experts. •Inference Engine − It simulates the human reasoning process by making fuzzy inference on the inputs and IF-THEN rules. •Defuzzification Module − It transforms the fuzzy set obtained by the inference engine into a crisp value.
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MuleSoft Inc. Natural Language Processing 20 • Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English. • Processing of Natural Language is required when you want an intelligent system like robot to perform as per your instructions, when you want to hear decision from a dialogue based clinical expert system, etc. • The field of NLP involves making computers to perform useful tasks with the natural languages humans use. The input and output of an NLP system can be − • Speech • Written Text • Components of NLP • There are two components of NLP as given − • Natural Language Understanding (NLU) • Understanding involves the following tasks − • Mapping the given input in natural language into useful representations. • Analyzing different aspects of the language.
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MuleSoft Inc. Machine learning and AI Technologies 21 • Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task. There are Many AI tools available in Market for doveloping AI solution,some of them are • Google ML Kit Google ML Kit, Google's machine learning beta SDK for mobile developers. • Infosys Niaknowledge-based AI platform, to collect and aggregate organisational data from people, processes and legacy systems into a self-learning knowledge base • Tesnsor FlowFor dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications • IBM watsonQuestion-answering computer system capable of answering questions posed in natural language
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MuleSoft Inc. Intelligent Application with MuleSoft and AI 22
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MuleSoft Inc. Importance of MuleSoft(connected application network) in AI 23 • It is a way to connect applications, data, and devices through APIs that exposes some or all of their assets and data on the network. That network allows other consumers from other parts of the business to come in and discover and use those assets. .Without a connected application network, AI is not going anywhere their is need of strong Application network for development ,easy to use, Monitoring, scalable, deployable AI system. • API strategies enable organizations to easily connect together any application, data source or device into a central nervous system where data can freely flow. This application network is how the AI ‘brain’ can plug into a business’ digital ecosystem to consume its data, provide valuable insights, and ultimately take action.
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MuleSoft Inc. 24
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MuleSoft Inc. Orchestrating the ML pipeline with Mule flows 25
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MuleSoft Inc. 26
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MuleSoft Inc. 27 • Now we have Intelligent mule
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MuleSoft Inc. Sample Project ->MuleSoft and AI 28 IBM Watson Tone Analyzer Integration Using Mule
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MuleSoft Inc. Let's begin with what we need before we start: 29 • In this competitive world, it is very important to understand the linguistic tone of a customer so that we can decide whether we need to respond to the customer immediately. • These days, customer satisfaction is more important to a sales manager or representative. A sales manager or representative may want to understand the linguistic tone from his customer's sent mail. For example, when a customer sends a mail to a sales manager or representative, the sales manager or representative may want to understand the tone of the mail so that the sales manager or representative can decide on further actions. This powerful feature can be achieved by leveraging IBM Watson Tone Analyzer service.
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MuleSoft Inc. 30 • Here we want to show how a Salesforce user (sales manager or representative) can understand the tone of his customer's sent mail by integrating Salesforce and IBM Watson Tone Analyzer service using Mule Soft ESB. • We have written a Mule flow that makes the integration of Salesforce and IBM Watson Tone Analyzerservice very easy. • Prerequisites • However, below are the prerequisites to test the flow shown below: • An account at IBM Blumix. • A deployed Tone Analyzer service to IBM Blumix. • An account at Salesforce. • A custom contact field CutomerTone__c on Salesforce. See here to create a custom field on any • Salesforce object.
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MuleSoft Inc. Flow Steps 31 • Receive mail from the configured mailbox using Mule IMAP connector. Once mail is received, the current Mule Message contains • email body as payload and the customer mail address as an inbound header fromAddress. • Enrich the current Mule Message with the Salesforce contact ID corresponding to the fromAddressretrieved above. The enriched Mule Message now contains a flow variable contactId that holds the Salesforce contact ID corresponding to the customer mailaddress. • Post the mail body held in the current payload to the IBM Tone Analyzer service. The Tone Analyzer service gives a JSON response representingthe tone of the mail in the case of success. • Calculate the tone based on the rule described here. As of now, we are interested only in Emotion Tone. The Emotion Tone has threechildren tones named Cheerfulness, Negative, and Anger. Each of these tones has an attribute called normalized score representing the value of the tone.If the sum of normalized scores of Negative and Anger tones is greater than Cheerfulness tone, then we consider the tone of the customer to be Angry otherwise Normal. • Update the Salesforce Contact corresponding to the contact ID held in the flow variable contactId with the tone calculated above.
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MuleSoft Inc. Tone-Analyzer Flow Design 32 • The main flow that receives an incoming mail from a customer.
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MuleSoft Inc. Get-Sf-Contact-Id Flow 33 • Sub-flow retrieves the Salesforce contact ID corresponding to the customer mail address. • This sub-flow finally returns a contact ID corresponding to the customer mail address. • In the tone analyzer flow, we use an enricher to enrich the message with the contact ID • retrieved from Salesforce and this contact id is stored in a flow variable #[flowVars.contactId]
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MuleSoft Inc. Get-Tone Flow 34 • This sub-flow gets the tone of the mail from the customer. It posts the mail body received from the customer to IBM Watson Tone Analyzer and retrieves the linguistic tone of the mail.
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MuleSoft Inc. Update-Sf-Contact-With-Tone Flow 35 • This sub-flow updates the tone of the customer mail to the custome field CustomerTone__c of Salesforce contact ID. • This flow applies some logic on the tone response retrieved from the get-tone flow. This logic is encapsulated in the Mule expression component. • This logic finally gives a JSON payload, represents the tone either Angry or Normal, and is updated to Salesforce contact's custom field CustomerTone__c. • So finally, this flow updates tone, either Angry or Normal, to the Salesforce contact.
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MuleSoft Inc. What’s next 36 • Share: – Tweet your pictures with the hashtag #MuleMeetup – Invite your network to join: <https://meetups.mulesoft.com/pune/> • Feedback: – Contact your organizer <Santosh Ojha> to suggest topics – Contact MuleSoft at meetup@mulesoft.com for ways to improve the program • Our next meetup: – Date: <___> – Location: <___> – Topic: <___>
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MuleSoft Inc. 39 Thank you !