Chat GPT is on everyone’s lips as it revolutionizes artificial intelligence. The tool itself explains what it is and what applications it has in the economic sectors.

It is the most talked-about tool, attracting attention both on social networks and in the media. Chat GPT has been a turning point in the world of artificial intelligence, going beyond scientific and specialized fields to surprise the whole of society.

The extensive capabilities of Chat GPT have led to numerous questions: What is it really, does it have its own intelligence, does it have any use, will it continue to learn over time until it dominates humans?

To answer these questions, or most of them, we will be guided by the Chat GPT tool itself. Let’s see how it sells itself.

What is Chat GPT and who created it?

Chat GPT is a language model developed by OpenAI. OpenAI is an artificial intelligence research organization based in San Francisco, California. It was founded in 2015 by a group of AI researchers and entrepreneurs, including Elon Musk, Sam Altman and Greg Brockman.

OpenAI’s goal is to develop high-quality, freely accessible AI technologies for society at large. To achieve this, the organization conducts research in a wide variety of areas, such as deep learning, natural language processing and automatic gaming.

Chat GPT is one of the many projects that OpenAI has developed. It is a language model that has been trained with a large amount of text data to be able to perform a wide variety of natural language related tasks.

Its ability to understand the context and intent behind user questions or queries makes it a very useful tool for developing chatbots and improving accuracy in information search systems.

What is Chat GPT for?

Chat GPT has been trained to perform a wide variety of tasks related to natural language.

This makes it a very useful tool for a variety of applications, such as automatically generating responses in a chatbot or improving accuracy in information search systems.

Here are four key points where the Chat GPT language model can be used:

  • Text generation: the model can be used to generate coherent and natural text, whether in the form of stories, articles or answers to questions.
  • Improving accuracy in search systems: the model can help improve accuracy in information search systems as it can understand the context and intent behind user queries.
  • Developing chatbots: the model can be used to develop chatbots that can have natural conversations with users, responding consistently and accurately to their questions.
  • Improving natural language processing: the model can be used to improve natural language processing in various applications, such as machine translation or sentiment detection in text.

Where does Chat GPT get the information to generate complex responses?

Chat GPT has been trained with a large amount of text data in order to perform a wide variety of natural language related tasks. This text data includes books, articles, news, conversations, among others, which are used to teach the model how to understand and generate text in a coherent and natural way.

Therefore, Chat GPT obtains the necessary information to generate complex answers from this text data, which allows it to understand the context and intent behind the users’ questions or queries.

In addition, the model can also use other types of information, such as images or videos, to enhance its ability to understand the world around it and generate more accurate and coherent responses.

Examples of Chat GPT application in economic sectors
Let’s look at some examples of how this tool can revolutionize the economy.

FINANCIAL SERVICES
The GPT language model can be used to improve online customer service through chatbots that can answer questions and solve problems quickly and efficiently.

E-COMMERCE
GPT chat can be used to generate personalized product descriptions and recommendations for customers in an online store.

MEDIA
The GPT language model can be used to write news content and articles quickly and efficiently, allowing media companies to publish more content in less time.

HEALTHCARE SERVICES
It can also be used to generate medical reports and medical record summaries more quickly and accurately.

EDUCATION
To create customized educational content for students based on their needs and level of knowledge.

TECHNOLOGY SERVICES
To improve online customer service through chatbots that can answer technical questions and solve problems related to the company’s products or services.

TRANSPORTATION SERVICES
The GPT language model can be used to generate real-time information about train and bus schedules, as well as to provide route recommendations and travel tips to customers.

ENTERTAINMENT INDUSTRY
Chat GPT can write synopses and reviews of movies and TV shows, as well as provide personalized content recommendations to users.

Companies using GPT Chat

There are several companies that are already implementing Chat GPT in their internal operations, both in Spain and in other countries. Some examples are:

  • Jobandtalent and Expensya, two Spanish scaleups that use ChatGPT to draft memos, reports and publications, summarize data and simplify laws.
  • Microsoft, which uses ChatGPT to offer businesses and application developers a way to take advantage of new technology2, and also uses GPT-4 for its new and improved Bing search engine.
  • Duolingo, the world’s most popular language learning app, which will add a new subscription model with Duolingo Max, which will make use of GPT-4 to offer more detailed chats, more complete answers and even “role-playing” with an AI designed to boost new language acquisition.
  • Slack, the platform that many companies use for different tasks on the Internet, which will implement ChatGPT for its virtual assistant called “Einstein,” who will deliver drafts, summarize threads and other external research without workers having to waste time opening external tabs.
  • Snapchat, the photo social network, which will turn to ChatGPT to shape its “My AI” tool, a chatbot with the most advanced version of OpenAI’s software to further customize its users’ experience.
    Koo, a platform very similar to Twitter, has just added ChatGPT to its service to help its users write short microblogs.

Application of Chat GPT in the field of data analysis

Chat GPT can be used for data analysis and for data engineers in several ways. For example, it can be used for:

  1. Improve the accuracy and speed of data extraction and cleansing. The GPT language model can analyze large data sets and extract relevant information quickly and accurately, allowing data engineers to focus on more valuable tasks.
  2. Generate reports and data summaries more efficiently. The GPT language model can analyze large data sets and generate useful summaries and visualizations that can help data engineers understand and communicate the results of their analysis more effectively.
  3. Improve the efficiency of the data modeling process. The GPT language model can help data engineers generate hypotheses and test different data modeling approaches more quickly and efficiently, which can improve the accuracy and effectiveness of their models.
  4. Generate code for data analysis applications. The GPT language model can be trained to generate code in different programming languages, which can help data engineers automate parts of the data analysis process and save time and effort.

Interested in specializing in data analysis?

If you are fascinated by the wide range of possibilities offered by Chat GPT in the field of business and you are also interested in the world of technology and data analysis, you should know about two EDEM programs: the Bootcamp in Data Science and the Master in Data Analytics.

In the Bootcamp in Data Science, students learn, in a 100% practical way, to analyze large volumes of data, extract insights and build AI models to make business decisions to end up working as Data Scientist, Data Analyst, Chief Data Officer (CDO), Business Intelligence Analyst or Machine Learning Analyst.

For its part, the Master in Data Analytics specializes students in a sector that is increasingly in demand in the labor market, where they learn to:

  • Know the tools.
  • Collect the right data.
  • Learn how to analyze them.
  • Draw conclusions that allow you to make decisions.

 

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