The key Gen AI concepts

ChatGPT defines Generative AI as:

“a class of artificial intelligence models and algorithms that have the capability to generate new, original content. Unlike traditional AI models that operate based on predefined rules or patterns, generative AI models can produce novel data that resembles the patterns observed in the training data. Generative AI models can generate content in various domains, such as natural language, images, music, and more”.

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The diagram below describes the range of models, concepts and uses that are seen in discussions around Gen AI.

• Blue boxes describe the main models, architectures and concepts that underpin various Gen AI capabilities (e.g., large language models).

• Orange boxes describe the general capabilities of these models (e.g., natural language generation).

• Grey arrows show the main models used to create capabilities in an orange box, and smaller black arrows show where other models can also be used (e.g., diffusion models provide image generation capabilities).

• Red text gives some of the uses made of the capabilities shown in the yellow boxes (e.g., generation of novel text).

• Red boxes highlight some of the popular foundational models for these uses (e.g., ChatGPT).

Concepts in Gen AI

Source: Charlotte Patrick Consult

Definitions of terms in the graphic:

• Generative models create something new based on examples they are given.

• Foundational models introduce a significant breakthrough, a new architecture or a novel approach that paves the way for subsequent advancements in the field.

• Parallel dataset is a data set which provides exact translations of all words in one language to the other.

• Discriminative model is a type of machine learning or statistical model that classifies input data points into different categories or classes.

• GPT (Generative Pre-trained Transformer) is a foundational model which can generate text responses.

• LaMDA is a Google project to provide a language model designed to allow more free-flowing conversations.

• dALLe is an OpenAI system that creates realistic images and art from natural language.

• Whisper is an automatic speech recognition system with improved ability to understand accents, technical language and background noise.

• BERT (Bidirectional Encoder Representations from Transformers) is a transformer-based language model for text generation.

• PaLM is a Google model that works on advanced reasoning tasks including code, mathematical problems, classification and question answering.

Table of contents

• Executive Summary
  • After the hype of Generative AI (Gen AI)
  • The most compelling uses for Gen AI in telcos
  • How to scope a Gen AI project
  • 4 core recommendations
  • Next steps
• Introduction
• What does Gen AI bring to the telco?
• Gen AI use cases in a telco
  • 1. Content creation
  • 2. Human-machine interactions
  • 3. Human-human interactions
  • 4. Knowledge management
  • 5. Process improvements
  • 6. Data management
  • 7. Intelligence improvements
• Where is the value in Gen AI?
  • Important types of Gen AI
  • Use cases for Gen AI
• Conclusion
• Index

Related research

• Generative AI and beyond: Preparing for future A3
• Making the metaverse useful
• Network-as-a-service: APIs, AI and the open cloud
• The data-driven telco: How to progress
• Network APIs: Driving new revenue streams for telcos

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