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AI in Cloud by Albert StepanyanAKA Cyberhulk
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“The Three Laws of Robotics:
― Isaac Asimov, I, Robot1: A robot may not injure a human being or, through inaction, allow a human being to come to harm;
2: A robot must obey the orders given it by human beings except where such orders would conflict with the First Law;
3: A robot must protect its own existence as long as such protection does not conflict with the First or Second Law;
The Zeroth Law: A robot may not harm humanity, or, by inaction, allow humanity to come to harm.”
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AI in CloudWhy artificial intelligence is succeeding: Then and now
The opportunity is boundless. The data keeps growing while
machines become faster so yesterday’s, today’s and the
future’s AI systems can only keep succeeding.
Machine learning and Artificial Intelligence
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AWS Predictive modelling
IBM Watson
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The future is already here5 Big Predictions for Artificial Intelligence in 2017
• Rise of big data. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them
• In software engineering, behavioral design patterns are design patterns that identify common communication patterns between objects and realize these patterns. By doing so, these patterns increase flexibility in carrying out this communication.
• Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages and, in particular, concerned with programming computers to fruitfully process large natural language corpora.
• Amazon Machine Learning is a service that allows developers of all knowledge levels to easily use the technology for hands-on learning..
• Watson is a cloud platform from the field of Artificial Intelligence . It was developed by IBM to provide answers to questions that are entered in digital form in natural language . The program, named after Thomas J. Watson , one of the first Presidents of IBM, was developed as part of the DeepQA research project.
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Collect everything instead of only a few things. In the past we were extremely limited in what data we could
capture and store about any particular event, whether it was a census, an earthquake, or a weather pattern.
Advances in storage technology enable Big Data to pull in vast quantities of data and store it for analysis.
Big Data source
AI was coined by John McCarthy, an American computer scientist, in 1956 at The Dartmouth Conference where the discipline was born. Today, it is an umbrella term that encompasses everything from robotic process automation to actual robotics. It has gained prominence recently due, in part, to big data, or the increase in speed, size and variety of data businesses are now collecting
Artificial Intelligence
Let the data guide the questions, instead of the questions guiding the data. In the past we’ve always
started with questions in our minds, and we’ve gathered data to try to answer them. With Big Data we often
reverse that process by letting the data speak for itself, which allows us to see patterns that guide the
formulation of more intelligent questions.
Unstructured data
Today Google AI, AWS AI as well as IBM Watson are the leaders on the market leveraging full scale ML and AI capabilities in Cloud.
AWS, IBM
ML works with data and processes it to discover patterns that can be later used to analyze new data. ML usually relies on specific representation of data, a set of “features” that are understandable for a computer. For example, if we are talking about text it should be represented through the words it contains or some other characteristics such as length of the text, number of emotional words etc. This presentation depends on the task you are dealing with and is typically referred to as “feature extraction”.
Machine Learning
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Predictive modellingPredictive modelling uses statistics to
predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.
Structuring Data
IOT is full of big unstructured data. In order have ML and PM up and running
data should be structured and collected into meaningful models,
which then will be processed by data modelling algorithm and behavioural
pattern will be identified.
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Behavioural analysisPredictive modelling is all about analyzing data and finding
similarities
Problem UnderstandingWe need to consider the
problem and how the solution should look like
Data UnderstandingTake inconsideration the amount, the availability, the quality of the
data. If it is relevant to our current problem.
ModellingFinding the model that suits to our current problematic, what is the best method. Using AWS predictive modelling provides one of the best solutions on the market.
Data pre-processingClean to data to concentrate on what is really important, find the best way for modelling and increase the quality of the data.
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What is Amazon Machine Learning?
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2Amazon Machine Learning (Amazon ML) is a robust, cloud-based service that makes it easy for developers of all skill levels to use machine learning technology. Amazon ML provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon ML makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure
DatasourcesA datasource is an object that contains metadata about your input data. Amazon ML reads your input data, computes descriptive statistics on its attributes, and stores the statistics—along with a schema and other information—as part of the datasource object. Next, Amazon ML uses the datasource to train and evaluate an ML model and generate batch predictions.
ML modelsAn ML model is a mathematical model that generates predictions by finding patterns in your data. Amazon ML supports three types of ML models: binary classification, multiclass classification and regression.
EvaluationsAn evaluation measures the quality of your ML model and determines if it is performing well.
PredictionsReal time and batch predictions.
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Human FactorAI is not all about data, AI evolves
Teaching computer is like teaching a kid. It starts absorbing data and tries to structure it.
Teaching a kidHaving large amounts of visual and audio data, kids start to digest it and differentiate.
Kids start to understand Computer starts to
analyze the data using ML techniques, trying to produce output.
Kids start to analyze Computers start to
communicate using natural language processing techniques.
Kids communicate Final stage, computers
evolve use cognitive analysis and start predicting and producing new ecosystems. IBM Watson is the solution of choice here.
Kids grow and create
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IBM WatsonThe Future of AI
UnderstandWith Watson, you can analyze and interpret all of your data, including unstructured text, images, audio and video.
LearnWith Watson, you can utilize machine learning to grow the subject matter expertise in your apps and systems.
ReasonWith Watson, you can provide
personalized recommendations by understanding a user's personality,
tone, and emotion.
InteractWith Watson, you can create chat bots that can engage in dialog utilize audio
and video metrics.
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Show TimeThis is reality, projects being developed
CySureCySure is an automated risk
assessment and Cyber Security scoring platform that works in
conjunction with predictive modelling and human behavior cognitive
system.
AdTopusAdTopus is a B2B predictive marketing analytics platform which is using cognitive analysis and machine learning techniques to launch most optimal campaigns and identify ideal customer.
HUMBSYAKA human behavior prediction system. Project that can become a breakthrough in artificial intelligence sphere around the world. There is a claim that human intelligence can be so precisely described that a machine can be made to simulate it.
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THANK YOUQuestion ?