Glossary ChatGPT is a generative AI chatbot interface built on top of OpenAI’s GPT-3.5 large language model (see below). ChatGPT (and ChatGPT plus, which uses GPT-4) allows users to interact with the underlying AI in a way that seems remarkably accurate and feels surprisingly human. You can ask it to explain a subject, write an essay, run a calculation, generate some Python code, or simply have a conversation. Generative AI is the umbrella term for the ground-breaking form of creative artificial intelligence that can produce original content on demand. Rather than simply analyzing or classifying existing data, generative AI is able to create something entirely new, whether text, images, audio, synthetic data, or more. Foundation models are complex machine learning systems trained on vast quantities of data (text, images, audio, or a mix of data types) on a massive scale. The power of these systems lies not only in their size but also in the fact they can quickly be adapted or fine-tuned for a wide range of downstream tasks. Examples of foundation models include BERT, DALL-E, and GPT-4. Large Language Models (LLMs) represent a subset of foundation models that are trained specifically on text sources. GPT-3, for instance, was trained on almost 500 billion words from millions of websites. 14 Its successor, GPT-4, can take image as well as text as inputs. Fine-tuning is the process by which foundation models are adapted for specific downstream tasks using a particular dataset. That can include everything from the hyper-specific (training a model to compose emails based on your personal writing style) to the enterprise level (training an LLM on enterprise data to transform a company’s ability to access and analyze its core intelligence). Data is the fundamental bedrock of generative AI. Not only in training foundation models themselves, but also in fine-tuning those models to perform specific tasks. In an enterprise context, examples might include everything from legacy code to real-time operational data to customer insights. References 1. ChatGPT sets record for fastest-growing user base - analyst note, Reuters, February 2023 https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/ 2. The Next Big Breakthrough in AI Will Be Around Language, Harvard Business Review, September, 2020 https://hbr.org/2020/09/the-next-big-breakthrough-in-ai-will-be-around-language 3. Accenture Tech Vision 2023 4. ChatGPT Is Coming to a Customer Service Chatbot Near You, Forbes, January 2023 https://www.forbes.com/sites/rashishrivastava/2023/01/09/chatgpt-is-coming-to-a-customer-service-chatbot-near- you/?sh=730eeab97eca 5. How AI Transforms Social Media, Forbes, March 2023 https://www.forbes.com/sites/forbestechcouncil/2023/03/16/how-ai-transforms-social-media/?sh=739221ca1f30 6. Large AI Models have Real Security Benefits, Dark Reading, August, 2022 https://www.darkreading.com/dr-tech/large-language-ai-models-have-real-security-benefits 7. OPWNAI: Cybercriminals starting to use ChatGPT, Checkpoint Research, January, 2023 https://research.checkpoint.com/2023/opwnai-cybercriminals-starting-to-use-chatgpt/ 8. Accenture Technology Vision 2023 9. CXO Pulse Survey, conducted by Accenture Research, February 2023 10. Accenture Technology Vision 2023 11. The Productivity J-Curve: How Intangibles Complement General Purpose Technologies - American Economic Association (aeaweb.org) 12. Uniting technology and sustainability, Accenture, May, 2022 Technology Sustainability Key to ESG Goals | Accenture 13. Pace Of Artificial Intelligence Investments Slows, But AI Is Still Hotter Than Ever, Forbes, October, 2022 https://www.forbes.com//sites/joemckendrick/2022/10/15/pace-of-artificial-intelligence-investments-slows-but-ai-is-still-hotter-than- ever/?sh=853d8124c76c 14. OpenAI’s GPT-3 Language Model: A Technical Overview, Lambda, June, 2020 https://lambdalabs.com/blog/demystifying-gpt-3 21 A new era of generative AI for everyone |