Generative AI

Commercial Application

There has been much hype about Chat GPT and Wall E, the most common contestants in the Generative AI space. Whilst many applications to date have been non-commercial, e.g. within the student and education sphere, where Chat GPT is able to convincingly reproduce exam passable scripts- Chat GPT was able to achieve a passing mark in a professional exam paper set by the Institute of Chartered Accountants in England and Wales. There have been many exploratory commercial uses of Chat GPT. This article will look at practical applications to date.

Throughout all applications of generative AI such as CHAT GPT it has been widely agreed that whilst the software is extremely powerful, there are many instances where there have been factual inaccuracies and potential bias for interpretation. At present, it is widely agreed there can be no application of generative AI without a human to review the results. The technology will augment but not completely reduce the human element, though it can reduce the number of resources required.

Coding: At present, this is one of the areas where Chat GPT is the strongest. Computer language is much more structured than human language often resulting in better code generated by Chat GPT than English language passages! Having said that, the primary contribution of Chat GPT in coding is one of speed, where a combination of generative AI and human supervision and review can really speed up coding.

Data: Chat GPT effortlessly handles vast amounts of both structured and unstructured data. Software companies are fast embedding generative AI capabilities into developed software. E.g.  Microsoft’s Azure OpenAI Service is embedded with GPT 3.5. CarMax has successfully used this technology to speed up data processing. It is for the CIO’s to imagine applications for generative AI within their organisations

Content: The technology can be used to produce reports which may be summaries of information from various data sources for internal distribution, produce social media content for marketing, below are some ways content can be created:

  • Natural language processing: GPT-3 can understand and respond to human input in natural language, making it useful for tasks like chatbots, language translation, and summarization.
  • Language translation: from one language to another
  • Text summarization: summaries of long articles or documents
  • Dialogue generation: Generate realistic and engaging dialogue for virtual assistants, chatbots, and other types of conversational interfaces.
  • Text classification: Classify text into different categories or labels, such as spam or non-spam, positive or negative sentiment, or topic categories like politics or sports.
  • Text generation: Generate text that is similar to a given input, allowing it to be used for tasks like poetry generation, song lyric generation, and story generation.
  • Text completion: Complete incomplete sentences or paragraphs, eg predictive typing or helping people write emails or other documents more quickly.
  • Sentiment analysis: Analyze the sentiment of text, helping businesses and organizations understand how people feel about their products, services, or brand.
  • Knowledge base construction: Generate knowledge base articles
  • Content moderation: GPT-3 can be used to automatically detect and flag inappropriate or offensive content, helping businesses and organizations to maintain safe and welcoming online communities.
  • Customer service chatbots:  Chatbots powered by the ChatGPT model could be used to handle customer inquiries and resolve issues, providing a more efficient and personalized service.
  • Online gaming chatbots:  Chatbots powered by the ChatGPT model could be used to provide in-game support, or to facilitate communication between players.
  • Social media chatbots: Chatbots powered by the ChatGPT model could be used to facilitate communication and interaction between users on social media platforms.

GPT’s Practical Commercial Applications (By Chat GPT 3.0)

As a language model, GPT (Generative Pre-trained Transformer) has a wide range of practical commercial applications, particularly in the field of natural language processing (NLP). Some of the current practical commercial applications of GPT-based chatbots and conversational AI systems include:

Customer service chatbots: Companies are using GPT-based chatbots to provide customer support and assistance to customers. These chatbots can handle a wide range of customer queries, provide personalized recommendations, and help resolve issues quickly.

Personal assistants: GPT-based personal assistants can help users manage their schedules, set reminders, make appointments, and perform other tasks. These assistants can be integrated into mobile apps, smart speakers, and other devices.

Language translation: GPT-based NLP models can be used to translate text from one language to another. These models can be integrated into websites, mobile apps, and other software applications to provide real-time translation services.

Content creation: GPT-based models can be used to generate content for social media, blogs, and other online platforms. These models can generate text in a variety of styles and tones, making them useful for marketing, advertising, and other content creation purposes.

E-commerce recommendations: GPT-based models can be used to provide personalized product recommendations to customers based on their browsing and purchase history. These recommendations can help improve sales and customer engagement.

Voice assistants: GPT-based voice assistants can be integrated into smart speakers and other devices to provide users with hands-free access to information and services. These assistants can perform a wide range of tasks, from playing music to ordering food.

Overall, GPT-based NLP models have many practical commercial applications, and their use is likely to continue to grow as businesses seek to improve their customer engagement, automate routine tasks, and provide personalized services to users.