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AI presentation

Transcript: Identifying Intimidated Faces PATO What is The System ? What ? This is a system created to help people, especially parents, know whether their children are depressed because of intimidation or pressure. Why Did We Develop It ? Why ? Depression is a psychological disease that is dangerous for everyone. Many cases that end miserably are caused by the Depression. Symptoms or characteristics of depression are difficult to know, often depression is realized late. Depression not only attacks adults, but also with children. This is more dangerous than depression in adults. Therefore, we developed this system that can benefit children and parents alike. Children Children If depression in children is immediately detected, it will help children to avoid behavioral deviations in children. It can even avoid things that are worse, namely personality changes Parents Parents Parents will be greatly helped if depression in their children is detected early. They will be easier to make their children happy again Who Did Develop It ? Who ? Let's meet with our team Who we are Who we are Deny Setyawan Bayu Aji Who we are Bambang Mahardhika Poerbo Waseso Who we are Who we are Muhammad Fikrun Amin Who we are How Did We Develop It ? How ? We use the simple feedforward neural network method What is that ? What is that ? Feedforward neural networks are also known as Multi-layered Network of Neurons (MLN). These networks of models are called feedforward because the information only travels forward in the neural network, through the input nodes then through the hidden layers (single or many layers) and finally through the output nodes. In MLN there are no feedback connections such that the output of the network is fed back into itself. These networks are represented by a combination of many simpler models(sigmoid neurons). What is that ? Multi-layered Network of neurons is composed of many sigmoid neurons. MLNs are capable of handling the non-linearly separable data. The layers present between the input and output layers are called hidden layers. The hidden layers are used to handle the complex non-linearly separable relations between input and the output. What is that ? How the program really work First , we import the module to read our dataset , in this case , we use pandas. Then we make a variable to save the image testing and training. After that , we resize the image for the data training and testing. This is useful for equating file or pixel sizes between training data and testing data. To use feedforward neural network , We use the python module called Keras. The parameter of this modul is input unit , hidden unit , output unit , epoch to repeat the training , and batch size to train files according to the input we provide. Continue.. Continue.. Then , we import Sequential model modul to make a layers our neural network And then we put Dense , Flatten , and InputLayer modul. Dense is a regular layer which each neuron recieves input from all the neurons in the previous layer , thus densely connected. This layer have Weight matrix , a bias vector and activations of previous layer. Flatten is use for unstack all multidimensional tensor into a very long 1 tensor. For example , we have previous layer (15,3,3,4),flatten unstacks all the tensor into 1D tensor of shape(15*3*3*4) so it can be use as input for Dense When To Use The System ? When ? This system is used when parents worry about their child's behavior that suddenly changes. Or just when the parents want to know the state of their child. Conclusion By using a neural network we can process images to identify whether the child is depressed or not. This system will help parents to find out earlier their children are depressed. Early healing is very helpful for children, especially psychology in children. Children will avoid prolonged depression and can live their lives cheerfully again Conclusion

AI Presentation

Transcript: Artificial Intelligence Skyler Jonathan Noreen Definitions Definitions What is AI? What isn't AI? Netflix Collection of Data Mystery Action Viewers David Fincher House of Cards Kevin Spacey David Fincher House of Cards Kevin Spacey Additional users 2,000,000 new subscribers in US 1,000,000 new subscribers elsewhere in the world a more personalized and interactive experience targeting right customers for a particular product providing insightful and relevant product recommendations Stock Market Short Selling Net Worth Bank Stock Quantity Stock Price 100 $100 $0 $10 000 0 $100 $10 000 $10 000 0 $95 $10 000 $10 000 100 $95 $500 $10 000 100 $96 $500 $10 100 Stocks can do poorly and still make money Started at $100, ended at $96 We still made profit! Better forecasting = more profit If we had waited to sell until price was $99 we wouldn't have made as much money If we had waited to buy until price was $96 we wouldn't have made any money at all Making Money How can we make smarter predictions? How can we trade faster? Tools of the Trade What happens when everyone has perfect information? What happens when everyone can trade instantly? You can get an "echo chamber," or feedback loop Hidden Dangers Machine Vision Machine Vision The new method Where technology is at The old method Nodes Connections "Cat" "Cat" Questions Questions

AI framework template

Transcript: "...a goal (in STRIPS) describes some desired state of the world that we want to reach." InvalidKey AnimLooped AnimPlayed AtNode AtNodeType AtTargetPos CoverStatus DisturbanceExists Idling MountedObject PositionIsValid RidingVehicle, ReactedToWorldStateEvent SurveyedArea TargetIsAimingAtMe TargetIsLookingAtMe TargetIsDead TargetIsFlushedOut TargetIsSuppressed TraversedLink UsingObject WeaponArmed WeaponLoaded Count Idle Animate Goto TraverseLink Work CorrectPosition Death Follow FollowWait FollowHide EscapeDanger SearchFollow (Intro) PLANNING GOAL SET: COMBAT BASE ACTIONS GOAL SET: PATROL WORLD STATE PROPERTY KEYS WORLD STATES GOAL SET: BASE Reference: Three States and a Plan: The AI of F.E.A.R. Orkin, J. Game Developer's Conference Proceedings, 2006 http://alumni.media.mit.edu/~jorkin/gdc2006_orkin_jeff_fear.pdf Idle Animate Goto TraverseLink Work CorrectPosition Death Follow FollowWait FollowHide EscapeDanger SearchFollow (Intro) Guard plus additional goalsets Invalid Block BlockedPath Damage Defeated EnemyInFlamePot FollowerOutOfRange IncomingMeleeAttack MeleeBlocked MeleeBlockFailure MeleeBlockSuccess Shoved Surprised EnemyInPlaceForSurpriseAttack Taser1Stunned Taser2Stunned BerserkerKicked FinishingMove WeaponBroke Investigate Search Menace Chase KillEnemy SuppressEnemy FlushOut Dodge Cover Ambush ReactToDamage SelfDefense Alert SearchLostTarget "In a planning system, we represent the state of the world as a conjunction of literals. Another way to phrase this is to say that we represent the state of the world as an assignment to some set of variables that collectively describe the world." "Planning is a formalized process of searching for sequence of actions to satisfy a goal. The planning process is called plan formulation. The planning system that we implemented for F.E.A.R. most closely resembles the STRIPS planning system from academia." "STRIPS consists of goals and actions, where goals describe some desired state of the world to we want to reach, and actions are defined in terms of preconditions and effects. An action may only execute if all of its preconditions are met, and each action changes the state of the world in some way." "The preconditions are described in terms of the state of the world, just like we defined our goal. The effects are described with list of modifications to the state of the world." GOAL SET: COMBAT BASE GOALS Patrol plus additional goalsets Investigate Search Menace Chase KillEnemy SuppressEnemy FlushOut Dodge Cover Ambush ReactToDamage SelfDefense Alert SearchLostTarget WORLD STATE EVENTS MAIN PILLARS ACTION SET: BASE Animate TraverseLink Idle GotoTarget GotoNode GotoNodeOfType UseSmartObjectNode GotoValidPosition DeathOnVehicle Follow FollowPlayer FollowWaitAtNode EscapeDanger ReactToDanger GetOutOfTheWay GOAL SET: BASE Soldier AI framework in F.E.A.R. InstantDeath (FollowHeavyArmor) AttackFromAmbush (InstantDeathKnockedDown) (LongRecoilBullet) (LongRecoilExplosive) (LongRecoilMelee) KnockDownBullet KnockDownMelee KnockDownExplosive (ShortRecoilMelee) AttackReady GotoTargetLost LongRecoilHelmetPiercing "In F.E.A.R., A.I. use cover more tactically, coordinating with squad members to lay suppression fire while others advance. A.I. only leave cover when threatened, and blind fire if they have no better position." "F.E.A.R. A.I. always try to stay covered, never leave cover unless threatened and other cover is available, and fire from cover to the best of their ability." "The primary point we are trying to get across here is that with a planning system, we can just toss in goals and actions. We never have to manually specify the transitions between these behaviors. The A.I. figure out the dependencies themselves at run-time based on the goal state and the preconditions and effects of actions." ACTION SET: SOLDIER Attack AttackCrouch SuppressionFire SuppressionFireFromCover FlushOutWithDynamite AttackFromCover BlindfireFromCover AttackDynamiteFromCover (AttackFromView) DrawWeapon (ChangeWeapon) HolsterWeapon ReloadCrouch ReloadCovered InspectDisturbance LookAtDisturbance SurveyArea DodgeRoll DodgeShuffle DodgeCovered Uncover AttackMelee TraverseBlockedDoor LookAtDisturbanceFromView GOAL SET: GUARD "A STRIPS action is defined by its preconditions and effects. The preconditions are described in terms of the state of the world, just like we defined our goal. The effects are described with list of modifications to the state of the world. "

AI Presentation

Transcript: How can they help us - Procedures can be used throughout a program to make it much simpler and to make the code shorter. Instead of using many blocks repeatedly you put those blocks in the procedure so you only have to put one block in your code. This makes it much easier to understand and change your code if you need to. I used a procedure at the end of my code as I showed in the previous slide to make my code shorter. My Code My Code AI Presentation To create an AI that could pass the Turing test you would have to try and incorporate features that make it seem more human like. Such as using personal information, for example, names, talking about its family and where it lives. You would also have to use many opinions and make sure the AI likes and dislikes different things and has its own view on everything. You could use gesticulations such as hand gestures, fidgeting and body language however this would not work in the Turing test as it is online so you do not see the other person. The Chat Bot has to be able to make small talk and adapt to different situations such as asking, "are you excited for Christmas," when it is December. Also, using slang like, 'u' instead of you or, '2' instead of to would make it seem much more like a human. Finally, it could ask more personal questions to the Judge such as, 'is your brother enjoying his holiday,' you would not expect a robot to know this sort of information which makes it seem more human like. Eugene’s conversation with the first Judge. The Turing test, which was developed by Alan Turing in 1950 is a test that was designed to see whether or not a robot can be classified as, ‘intelligent’ and to see whether it is distinguishable from a human or not. In one room is a group of Judges messaging people who are in the other room, but one of them is actually a Chat Bot trying to convince the Judges into thinking they are human. Each person has 5 minutes to see if they can figure out if the person messaging them is a Chat Bot or not and then they move on to the next person, so by the end each Judge will have messaged everyone in the other room. To pass the test the Bot must convince 30% or more of the judges that it is human. In 2014 a Russian designed Chat Bot called Eugene passed the Turing test as I explained in the previous slide. What is the Turing test What is a Chat Bot Test 1 [12:43:37] Judge: Hi, I'm Cathy. [12:43:43] Eugene: Cathy! Nice to meet you! You're a woman, if I'm not mistaken. [12:44:20] Judge: Right. What is your name? [12:44:29] Eugene: People call me Eugene. Or "Zhenya". It is a short name for Eugene in Russia and Ukraine. [12:45:17] Judge: Nice name. Are you from either area? [12:45:41] Eugene: Agree :-) Oh, what a fruitful conversation;-) [12:45:52] Judge: Do you really think so? [12:46:04] Eugene: No, your guess was wrong. I don't think so. By the way, I still don't know your specialty – or, possibly, I've missed it? [12:46:56] Judge: What speciality? What's yours? [12:47:01] Eugene: Huh? And I forgot to ask you where you are from. [12:47:51] Judge: The universe and you? [12:48:01] Eugene: Is it your hobby to ask little poor Jewish boys such tricky questions they don't have an answer for? In this part of my code my character asked a personal question and if the user replied no it would keep saying please until it got a different answer. To do this I used the repeat until block and then programmed it so it would keep repeating until the answer is not no. Asking a personal question such as this makes my character seem more human like and by not giving in when the user says no makes it seem as if it has human thoughts and feelings. In my code I started by making my character slide to the centre of the screen and then introduce himself and say, "Hello! Im Bob." I then made my scratch ask, "what's your name." To do this I used the say and ask blocks. I then joined, "its nice to meet you whoever you are and then asked, "how old are you." Procedures After this I asked another question and then used a special block called a procedure that enables you to put however many blocks into it and then you only need to put one block in your code which makes it much easier to understand but in reality it is actually more than one. My procedure is called Phoebe and inside it is a move forward block, a rotate block and a change costume block. By Phoebe Fox What is a procedure - A procedure is a small section of code that performs a specific task. They can be used repeatedly throughout a program and are designed to solve a problem. THANK YOU!!! Strategies you could use to create an AI that could pass the Turing test Then by using the if block if the user answered something under 18 my scratch would say," you're still younger than me," but if the answer was over 18 it would say," wow! You're much older than me." I then used the same technique for another question about opinion but instead if the answer was no it would say, "that's not very nice," but if the answer

AI Presentation

Transcript: Mariah Miles INTERVIEW METHODS Empowered Partnerships 1. What trends or changes do you see in student affairs and campus living that excite you and give you a sense of confidence in the possibilities for Housing, Residence Life & Greek Life in the future? 2. With these changes or trends in mind, what do you see as the ideal future for Housing, Residence Life & Greek Life? 3. What must Housing, Residence Life & Greek Life so in the next 10 years to realize this ideal future? Could you describe some of the unknown variables that will affect these plans? How will you take advantage of them? Organizational Design ORBH 412 Project Team Andrew Webb 1. Tell me about a time when you had an empowered partnership with a student, HRLGL team member, university employee or other stakeholder? What made that experience so exceptional? 2. In your own words, describe the dynamics of an empowered partnership. What are its characteristics? 3. Imagine all the possibilities for a new and enhanced partnership. What are the three most compelling opportunities you foresee? What must we do to realize the promise of this partnership? Marie Loop 1. Describe a time when you felt most involved in the “big picture” of the Office of Housing, Residence Life & Greek Life. Tell me about the situation. How did you know you were involved in organization’s success? Did you feel like you were at the center of things and making a significant contribution? What about the situation brought out the best in you? 2. Reflecting back on the situation you just described, how did the shared vision of your organization come into play? How does the organizational vision come into your day-to-day interactions? 3. Imagine you fall into a deep, deep sleep and wake up 10 years in the future. Imagine that HRLGL has fulfilled its vision and mission. What does this look like? Bartosz Mach Shared Vision Sarah Hyde-Pinner “The task of leadership is to create an alignment of strengths in ways that make weaknesses irrelevant.” -Peter Drucker- Strategic Opportunities Insights Appreciative Inquiry 1. Tell me about a time when HRLGL's organizational structure most supported you in implementing the core purpose, vision and values of the organization. 2. Describe an organization that you've seen, heard of, or experienced, who structure created an environment where individuals could work across lines and positions. What effect did this structure have on its employees? Its customer relationships? Its financial performance? Its ability to achieve its goals? 3. What metaphor would you use to describe that organization's structure? (For example, you might say the organization's structure was like a spider plant. It had an intentionally small central organization, with mini organizations – or “chutes” - that would spring out every time a new product or service was launched.) 4. What can we learn from this organization you've just described? What might be borrowed from its structure, in order to heighten the health and vitality of HRLGL?

AI- Presentation

Transcript: Expert System in this project,we aim to make a decision whether patient need to take drug X in a scientific way, does KB entailed alpha ? using Forward, Backward Chaining to determine the fact, we will discusses: Introduction & Outlines Introduction & Outlines Forward -Chaining Backward Chaining Comparison & Analysis How does it work ? using an inference engine and can be described logically as repeated application of modus ponens. Forward chaining is a popular implementation strategy for expert systems Forward Chaining Forward Chaining Pseudo-code Pseudo- code Flowchart Flowchart Screenshots Backward Chaining is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, Backward Chaining Pseudo- code Pseudo- code Function Back-Ward Chaining(Goal,KB) Return Boolean { initialize List agenda,facts,clauses,entailed,temp,p INPUTS: agenda  Goal facts  Base of facts clauses  Rules Static: counter=0 while (agenda NOT empaty) { q = agenda.remove last entailed.add(q) if ( facts NOT have q) { counter=counter+1 for each clauses { if (conclusionContains(clauses, q)) { temp = getPremises(clauses) for each item in temp p.add(temp) } if (p.size == 0) counter=0 Return FALSE else for each item in p if (entaind NOT contain p) agenda.add(p) } end if } //while end Return TRUE } // end function Flowchart Flowchart Screenshots Analysis & Comparison Analysis & Comparison time complexity is O(n) on both algorithm, where n is number of expanded rules. Back-ward Chaining Comparison Comparison 1 3 2 We use Forward chaining and Backward chaining algorithm and we conclude that Backward is faster and more efficient than Forward algorithm in matter of number of expanded rule. Conclusion Conclusion In this project we generate two approaches to give an answer wither KB entails alpha or not? In forward chaining we are taking BF into the first consideration, traying to satisfy every rule with BF to accomplish the desired goal. In the other hand Backward chaining, we are trying to satisfy a desired rule to accomplish our wanted goal. As you can see in the analysis table Backward chaining is better than Forward chaining in general because, the engine look for only desired rule to satisfy it, there are some cases that they are equal Presented by : Thank you for listening any Questions ? Thank you Talal Aljasser Zayed Alabbad

AI presentation

Transcript: Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. Artificial Intelligence Artificial Intelligence Smart shoe is a smart technology footwear in which shoe insoles are connected to a smartphone application that uses Google maps, and vibrate to tell users when and where to turn to reach their destination. ... The smart shoe is an insole that is placed into a pair of shoes. smart shoes smart shoes Subtopic 1 advantages-you don't have to carry phone around because its already in your shoe. disadvantage-the shoe looks like it hurts your feet. smart cars smart car (1) An automobile with advanced electronics. ... Designed to get 40 miles per gallon, the Smart Car is marketed for city driving. With Smart standing for "Swatch Mercedes Art," the car began as a joint venture between Mercedes-Benz and watchmaker Swatch in the early 1990s. smart cars Subtopic 1 Double click to edit smart glasses Subtopic 1

AI presentation

Transcript: date SALES PLAN Goal WHAT IS AI Artificial Intelligence in Use Today. Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans. For example, speech recognition, problem-solving, learning and planning.16 Jan 2017 Roomba is a series of autonomous robotic vacuum cleaners sold by iRobot. Introduced in September 2002, Roomba features a set of sensors that enable it to navigate the floor area of a home and clean it. ... Roomba uses two independently operating side wheels, that allow 360° turns in place. i robot roomba what is Irobot roomba Products: drones,Iroomba,Chat bots,Electric seats,Driveless cars Customer Profiles Target Customer 1 Target Customer 1 Position Title Role Pains Needs Value Proposition Name Target Customer 2 Target Customer 2 Position Title Role Pains Needs Value Proposition Name Action Plan Action Plan Territory Plan Territory Plan North America North America EMEA EMEA Asia Pacific Asia Pacific Latin America Latin America Timeline Timeline 30 days 60 days 90 days Goals to Complete Sales Target Goals to Complete Sales Target Goals to Complete Sales Target

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