OpenAI Use cases for the Enterprise – And what is all about Chat GPT?9 min read

Enterprise solutions of Chat GPT by OpenAI

We are living in a data-rich world today. Modern technologies working on the basis of processing tonnes of unstructured data, collectively called Big Data is changing how the internet, the tech companies, and human lifestyle overall transform. One significant development is artificial intelligence (AI) trained models that can process human generated data and share unprecedented insights.

OpenAI is a leading research institute focused on the development of AI technologies funded by Microsoft up to $3 Billion till now and a plan to add another $10 billion. One of the key areas of focus for OpenAI is the creation of “friendly AI” products, which are designed to be beneficial to humanity and operate within ethical boundaries.

How are OpenAI models trained?

OpenAI models are trained using a variety of techniques, depending on the specific model and its intended use. In general, however, most OpenAI models are trained using a combination of supervised and unsupervised learning techniques.

What is supervised learning?

Supervised learning involves training a model on a labeled dataset, where the correct output is provided for each input. The model learns to map the input data to the correct output, and can then be used to make predictions on new, unseen data.

What is unsupervised learning?

Unsupervised learning, on the other hand, involves training a model on an unlabelled dataset, where the correct output is not provided. The model can learn from the data itself, identifying patterns and relationships in the data without any external guidance.

 One of the most notable examples of a friendly AI product from OpenAI is GPT-3, a state-of-the-art language processing AI model, popularly called Chat GPT. GPT-3 can understand and generate human-like text, making it useful for tasks such as machine translation and text summarization. Importantly, GPT-3 is designed to operate within a set of ethical guidelines, such as avoiding the generation of harmful or offensive content.

 

What is Chat GPT-3?

Chat GPT-3(Generative Pre-trained Transformer 3 ) is an AI-integrated chatbot from OpenAI for interactive dialogue based conversation

Why are people crazy about Chat GPT?

Chat GPT interacts with a user in a dialogue format with real human like features. It can answer follow-up questions, admit its mistakes, ask for more clarity and challenge incorrect premises. It is also trained to reject inappropriate statements.

The Times described it as the “world’s first truly useful chatbot”.

 

What can Chat GPT do for you?

Chat GPT uses generative AI to generate answers to your questions which seems so well informed and detailed as if humanlike. It can describe a topic for you, solve a problem, generate code for an application or debug a code.

What is generative AI?

Generative AI is the next technological revolution commanding how online content and experiences around them are created. Simply put, it creates original content from a few instructional texts or queries instead of analyzing and remodeling existing data.

From producing poetry, and art to debugging or creating complex code, generative AI is replacing a lot of old school tasks.

Some Futuristic Solutions By Generative AI of OpenAI

Code Review To Generate Clean And Agile Code

One of the most important characteristics of a good code is clean code. OpenAI can be used for code review or debug code using Codex Review API an extension of ChatGPT. 

This extension might be used on top of an IDE to immediately notify if the code is becoming too redundant even during writing and also point out the errors. Similarly, it might be used on top of a code quality assurance platform like SonarQube to continuously monitor code quality.

Sit On Top of your Enterprise Knowledge Graph

Different organizations use different knowledge graphs today to handle the bulk of data generated while running a business. An NLP system like OpenAI can be used on top of a knowledge graph for an effective query which can help in automatic tasks using well informed bots, empowering enterprise chatbots, performing sentiment analysis, predictive analysis on organizational data, and gaininig valuable insights.

Microsoft is planning to integrate GPT software on top of its search engine Bing to offer unique search services and close up the market gap with Google Search, its immediate competitor. Integrating Chat GPT will enable Bing to understand the intent behind search queries and respond in a human-like fashion.

Humane Response To Patient

We have already witnessed the introduction  of various chatbots in healthcare related apps. However, these apps are not very humanlike in response as patients can only select a preloaded set of questions or responses as a means of interaction. This can seem cumbersome in times of emergency.

 A language model is exactly designed for this to predictively answer and ask questions in a natural tone. Its ability to explain complex medical topics in a realistic, natural language tone can be helpful for having a meaningful conversation with patients and relieve doctors and health professionals from preliminary questionnaire rounds.

It can also use its analytics power to tally with its huge volume of training data to find and share interesting responses and also keep training simultaneously to improve.

Content Management

OpenAI can serve as an excellent writing assistant for its ability of information extraction and classification. Information extraction is the process in which we find out some information about a text, say a keyword or a style of writing. OpenAI also exhibits classification where texts can be classified based on tone, style, sentiment, and topic. 

These properties can be utilized, along with a  few specific pieces of information supplied by the user when prompted, to generate very high quality write ups.

Apart from content generation, it is frequently used for content quality checking to maintain tone, salience, and sentiment of a write-up. This can have further application in filtering and categorizing good content from trash.

Content moderation is an obligatory task for organizations dealing with user-generated images or text. However,  it is also a prolonged and tedious job that the AI can help in easing out by doing the preliminary round of filtering and segregation.

Text in the image collected from the user interface is filtered for quality and profane, NSFW, or low quality content is removed and stored segregated in an organizational database. Only hate speech is shared with moderators for validation.

Text in the image collected from the user interface is filtered for quality and profane, NSFW, or low-quality content is removed and stored segregated in an organizational database. Only hate speech is shared with moderators for validation.

Content moderation is also equally important for the publishing industry. As time passes the idea of what is socially acceptable keeps changing. GPT 3 trained with the latest cultural values can scrutinize and guide newly written or to be reprinted content to become more pleasing to the mass.

 

Continuous generation of your Training Data Set

Datasets are very important ingredients for any kind of AI/ML research. Sometimes it is difficult to find sufficient datasets to train a model due to enterprise confidentiality or government regulation. There is actually a huge market for synthetic data for various AI/ML research.

GPT 3 being a generative AI can create humanlike data for Data Science research and influence to level of  the playing field of data commodity market.

One of the interesting applications of OpenAI is Dall-E 2 which is a Neural Network model using NLP to generate images based on text instructions. This can further be used to feed ML engines.

 

Other Uses of GPT 3

A Few other innovative use cases of GPT 3 are:

  • ChatGPT can be integrated to WhatsApp business accounts to carry on a human-like conversation based on specific keywords till the owner is free to respond back
  • Based on certain prompts it can generate replies to E-mails
  • It can generate YouTube text summary for any YouTube video
  • It can write Tweets and tweet replies
  • Azure OpenAI can analyze knowledge gap,  generate reports on a variety of topics and fill the gap in customer’s knowledge base of companies
  • The ability to generate realistic, natural language content can be a game changer for the education sector
  • With its huge resource of information and up to date training on social and cultural constructs, it can help to bring back the days of neutral journalism

 

Are Chat GPT models trained via supervised learning or unsupervised learning?

Chat GPT is capable of understanding and generating human-like text. This suggests that it may be trained on a large dataset of labeled text data, allowing it to learn the relationships between words and their meanings. However, it is also possible that GPT-3 is trained using unsupervised learning techniques, allowing it to learn from the data itself and generate text that is coherent and realistic.

 

Another example of an NLP model from OpenAI is DALL-E 2, a state-of-the-art artificial intelligence (AI) system capable of generating images from text descriptions.

Besides its image generation capabilities, DALL-E 2 is also able to perform a range of other tasks, such as image translation and text summarization. This makes it a versatile and powerful AI system that has the potential to be applied in a variety of fields.

In addition to GPT-3 and DALL-E 2, OpenAI has developed several other friendly AI products, such as AI systems for playing games and robotics applications. Overall, the development of friendly AI products is a key area of focus for OpenAI, and the institute is dedicated to creating AI technologies that can be used for the benefit of humanity.

The Automation of Creativity

All these brilliant innovations certainly raise the question, is AI going to take away creativity, one of the last bastions of humanity? To answer this we need to first understand what creativity is. It can loosely be defined as a  “self-reconfiguring process under which solutions to a problem are achieved, in a new and unexpected way” (De Garrido, 2021).

Machines are generating solutions based on algorithms and training models so the process by which they are generating these creative outputs can be defined as “algorithmic creativity”

However, the fun fact is these machines need to be trained from an outside environment before they can become autonomous. They still need some impetus from the external environment and their creative potential is largely conditioned by humans. Humans can actually still play with their algorithms or training data and control their outputs.

 

In fact, the creators of DALL-E 2 have taken steps to prevent the program from generating inappropriate or offensive content, such as excluding explicit or violent material from the training data and implementing filters to prevent reinforcing harmful stereotypes.

In terms of not taking over human thinking capacity, it’s important to keep in mind that AI-generated creativity is still a tool, and it’s up to humans to decide how it is used. As long as it is used responsibly and ethically, AI-generated creativity can be a powerful force for good.

 

Wrapping Up

While powerful AI engines become capable of wearing the thinking cap of humans, AI-generated creativity has the potential to help humanity in many ways. For example, it can be used to create new forms of art and media that can inspire and delight people. It can also be used to generate new ideas and solutions to problems, helping to drive innovation and progress. Additionally, AI-generated creativity can help to amplify human creativity by providing new starting points and possibilities for exploration.

 

 

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