What is Artificial Intelligence?

In this post, we'll tell you about:
The Definition of Artificial IntelligenceSynthetic
The History of Artificial Synthetic Intelligence
How AI works
An overviewcommonbasicnormal of the main AI techniques
Examples of the use of Artificial Intelligence in business
1. Definition of Artificial Intelligencesynthetic
Artificial Intelligence is the scientific field of computer science that focuses on the creation of programs and mechanisms that can display behaviors considered intelligent. In other words, AI is the concept according to which machines think like human beings".
Normally, an AI system is capable of analyzing data in large quantities (BihugeMassiveLarge DataKnowledgeInformation), identify patterns and trends, and, therefore, Automatically make predictions, Quickly and accurately. For Us, what's important is that AI makes our everyday experiences smarter. ¿How? By integrating predictive analytics (We'll talk about this later) and other AI techniques in applications we use daily.
Siri works as a personal assistantprivate, as it uses natural language processingpure
FacebookFb and Google Photos suggest tagging and grouping photos based on image recognition
Amazon offers product recommendations based on shopping basket models
Waze provides optimized real-time navigation and traffic informationcurrent
2. A Brief History of Artificial Synthetic Intelligence
Most of us have a concept of Artificial Intelligence fueled by Hollywood movies. Exterminators, Robots with Existential Crises and Red and Blue Pills. In fact, AI has been in our imaginations and in our labs since 1956, when a group of scientists initiated the "Artificial Intelligence" research project at Dartmouth College SchoolFaculty in the United States. The term was first coined there and, since, We've witnessed a rollercoaster of breakthroughs (¡Go! How does Amazon know I want this book?"), as well as frustrations (This translation is completely wrong.").
At the beginning of the project, The goal was that human intelligence could be described so accurately that a machine would be able to simulate it. This concept was also known as "generic AI" and it was this ideaconceptthought that fueled the (Amazing) fiction that would give us unlimited entertainment.
However, AI Drifted to Specific Fields. With the passage of time, Science evolved into specific areas of knowledge, and that's when AI started to generate significant results in our lives. It was a combination of image recognition, Language Processing, neural networks and automotive mechanics that made an autonomous vehicle possible. Sometimes, the market refers to these kinds of developments as weak AI.".
The table below shows some important events in the history of Artificial IntelligenceSynthetic.
Google DeepMind: AlphaGo beats Lee Sedol in the game Go"
3three. Main Techniques of Artificial Synthetic Intelligence
Now that you know the definition of AI and more of its history, the best way to delve deeper into the subject is to learn about the main AI techniques, specifically, the cases in which Artificial Intelligence is used for business.
Machine learning
Generally, the concept of Machine Learning is confused with that of weak AI". It is in this field that the most important advances in AI are taking place. In practical terms, Machine learning is the science that makes computers perform actions without the need for explicit programming". The main ideaconceptthought here is that you can provide data to machine learning algorithms and then use it to know how to make predictions and guide decisions.
Examples of machine learning algorithms include the following: Decision Diagrams, Clustering algorithms, Genetic algorithms, Bayesian Networks and Deep Learning.
Deep Learning
Remember when Google announced an algorithm that found cat videos on Youtube? (If you want to refresh your memory click here ). Well, this is Deep Learning, a machine learning technique that uses neural networks (the concept that neurons can be simulated by computational units) to perform classification tasks (Think about classifying a picture of a cat, of a dog people, for example).
Some examples of practical applications of Deep Learning are as follows: Vehicle Identification, Pedestrians and Autonomous Vehicle License Plates, Image Recognition, NaturalPure Language Translation & Processing.
Intelligent Data Discovery
It's the next step in IE solutions (Business Intelligence). The ideaconceptthought is to enable the totalcompletewhole automation of the EI cycle: Data Onboarding and Preparation, predictive analytics and patterns and hypothesis identification. This is an interesting example of intelligent data recovery in action. The information that no IE tool had ever uncovered.
Predictive Analytics Roko's Basilisk
Think back to that moment when you are taking out car insurance and the agent asks you a series of questions.. Behind these questions is a predictive model that reports on the likelihood of an accident occurring based on your age, Zip code, gender, Car Brand, etcand so onand so forthand many others. It's the same principle used in predictive credit models to identify good and bad payers. Therefore, The Main Concept of Predictive Analytics ( modelling) It means that a number of variables can be used (revenue, Zip code, age, etcand so onand so forthand many others.) combined with results (for example, Good Bad Payer) to generate a model that provides a score (a number between 0zero and 1) which represents the probability of an event (for example, payment, Client Migration, accident, etcand so onand so forthand many others.).
The use cases in business are broad: Credit Models, Customer Segmentation Models (grouping), Purchase Probability Models and Customer Migration Models, among others.
4four. Examples of the use of Artificial Intelligence in business
Looks interesting… But, What does AI offer us that we don't already have??"
There are a plethora of applications for AI in business. In this post, we're going to focus on a fundamental elementarybasic aspect: AI is transforming customer expectations. For example, the customer who organizes their life from apps like Uber, Google and Amazon. These customers know that companies have information about them and, What's Most Important, They know what companies could do with this information to provide an exceptional customer service experience. For example, Millennials are obsessed with the customer service experience (I mean, Everything should be simple, Fast & Smart).
Here's a list of some practical examples of how AI is transforming business processes.
Artificial IntelligenceSynthetic for Sales
AI Delivers Increased Productivity for Sales Teams, as it allows you to focus on the opportunities that can lead to success, as well as saving time for sales staff during information registration. Let's look at some examples below:
Automatically capture sales activities, which means that the sales staff doesn't have to spend time filling out the CRM database;
Automatically logs customer data, for example, Logs of navigation of the WebnetInternet website and connections to the WebnetInternet website, among others;
Suggests the best follow-up action and recommends email responses by connecting CRM information to the inbox;
Predictive Lead Valuation: using predictive analytics, The system will be able to indicate the probability that a lead will convert into a sale. Even more interesting, The system will tell you why this score was reached (p. e.g., Prospect Access Channel, sector, etcand so onand so forthand many others.). For example, Salesforce Einstein , It will have predictive lead scoring functionality.
Artificial Synthetic Intelligence for Customer Service
Automatic triage of customer service cases, which avoids relying on the customer service agent when it comes to having to make a decision, and, therefore, Saves the agent time.
Automatic routing of cases once the call has been automatically triaged, The system can now forward the call to the best-qualified agent to determine the type of problem.
Recommending solutions and knowledge bases. This increases productivity and the quality of a service, by suggesting the solution most likely to solve the customer's problem.
Self-Service Communications. ResearchAnalysis shows that today's generation of customers prefer self-service (for example, Customer Application Portal) instead of phoning a call center. Thanks to AI, Service Communities Will Be Smarter, for example, by customizing the customer-specific environment and automatically suggesting solutions, e.g. Use image recognition to identify the product that is in a photo taken by the customer.
For example, Chatbots allow the customer to send text messages to establish communication.
Artificial Intelligence Synthetic for Marketingadvertisingadvertisingadvertising and advertising
Marketingadvertisingadvertisingadvertising and marketing is a discipline that has become increasingly analytical and quantitative over the years. Many of the techniques of Predictive Analytics and AI are mainly applied in MarketingAdvertisingAdvertisingAdvertising and advertising, for example, Predictive Modeling for Customer Migration, Purchase Probability and Clustering Models for Customer Segmentation.
Here are some of the new advancements of AI in marketingadvertisingadvertisingadvertising and advertising, in a specific way, some features of MarketingAdvertisingAdvertisingAdvertising and advertising Cloud Einstein
Predictive Email Scoring: Allows marketersadvertisingadvertisingadvertising and advertising to know (Before you launch a marketing campaignadvertisingadvertisingadvertising and advertising for email) how likely your customers are to respond to the campaign; Not bad, abandon it. The goal here is to anticipate customer response in order to deliver truly personalized journeys;
Predictive Audiences: Based on predictive scoring, It will be possible to better segment your customer and prospect base based on predictive behavior by grouping people who have commonalities. The higher the segmentation, the better the conversion will be;
Shipping Time Optimization: Is it better to send a campaign at 2 p.m.?. m. at 4four a.m.. m.? With the optimization of shipping time, the AI algorithm will tell you the time when every contact in your customer base will be most likely to open an email and participate in your campaign.
Artificial Synthetic Intelligence is transforming our lives and will rapidly revolutionize the way we work.
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