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What is generative AI and why does it matter? (1/3)

What is generative AI and why does it matter? (1/3)

Although artificial intelligence is dominating many conversations in business today, it’s important to remember quite how recent an innovation open access AI still is. The conversational robot ChatGPT – the Generative Pre-Trained Transformer from OpenAI – has only been widely available since the end of November 2022, with the updated GPT-4 accessible since just the middle of March this year.

Date : April 28th, 2023

Category : Thought Leadership

GPT-4 (and its short-lived predecessor GPT-3) are examples of Large Language Models (LLMs), generative AI algorithms that create new content based on existing information and frameworks and on which they are trained. In the case of ChatGPT, this means online content created up until late 2021. This deep learning method is a subset of machine learning, itself a subset of data science.


A significant leap forward

Until recently, the power, speed, and wide applicability of AI tools had been held back by the recurrent neural networks on which they were based. The leap forward made possible by ChatGPT is based on the technology of transformers. These are distinguished by both the sheer number of parameters they can take into account – 175 billion for GPT-3, a trillion for GPT-4 – and the greatly increased volume of textual data on which they are trained. For GPT-4, this means 500GB of text from the web, compared with all of Wikipedia, which represents barely more than 20GB of data. Because ChatGPT learns at such speed from so many more parameters and from so much more training data, the answers it generates to user requests are naturally much better informed and structured.

As a result, ChatGPT has become the fastest-adopted software platform in history, taking fewer than five days to reach a million subscribers. That compares to two-and-a-half months for Dall-E – the AI-driven image generator, also developed by OpenAI – ten months for Facebook and two years for Twitter. In less than six months, ChatGPT had attracted more than 100 million active users and today welcomes one billion visitors a month.


Big Tech bets big

The established major players in tech are investing significantly in generative AI. Microsoft has so far invested US$11bn in OpenAI, ChatGPT’s parent company, and could end up owning three-quarters of the company’s shares in the long term. It has integrated OpenAI’s services into both its Bing search engine and its suite of Office tools. In so doing, it has stolen a march on Google, which launched its own conversational AI chatbot, Bard, some months after ChatGPT, and to less than universal acclaim. In recent months, interest, activity, and investment has lurched from Web 3.0 and the metaverse, NFTs and cryptocurrencies, to focus squarely on generative AI.


Use cases for business

ChatGPT enables users to manipulate, summarize, or repurpose large volumes of text. This makes it ideally suited to assignments where humans and machines share the load, increasing productivity by simplifying and accelerating tasks that require writing and synthesizing text. These include:

  • Writing and producing code
  • Retrieving high-level information and extracting concepts and entities from multiple different narrative sources
  • Summarising textual content (typically up to ten pages) into the most salient points
  • Creativity and ideation, at least idea generation that depends on convergent thinking
  • Advanced interaction tools such as chatbots for learning and information transfer.

Additionally, ChatGPT can help businesses with human-machine-human tasks in which existing textual content is reformulated. These include writing articles, media, and social media posts, as well as simplifying and popularizing content between different specialist business functions. By asking ChatGPT to write progressively more straightforwardly and with less jargon, it can help to make the impenetrable both understandable and useable across traditional silos in a business.


A revolutionary assistant

There are four reasons why ChatGPT can be seen as revolutionary as a business tool and assistant.

  • Performance – ChatGPT already outperforms many state-of-the-art models, over an exceptionally broad range of topics
  • UX/UI – as a live interface which generates text as it goes, ChatGPT allows users to experience the process of content generation without becoming frustrated or feeling like they’re being lectured or presented with a non-transparent fait-accompli
  • Scale – it is the only model today capable of handling millions of users with such power. Established leaders in search and social media, Alphabet and Meta, are lagging the field
  • Code generation – the fact that ChatGPT can generate not only text but also code means that it is much more than just a natural language processing tool for summarizing textual data.


Impact on the future world of work

According to a March 2023 report by investment bank Goldman Sachs, up to 300 million jobs worldwide could be eliminated by generative AI tools such as ChatGPT. The report concludes that as many as two-thirds of knowledge economy jobs in the U.S. and EU could be simplified and accelerated by some degree of automation through AI, with legal, administrative, and customer support-related roles in the forefront for the U.S.; management and administrative jobs in Europe.

The true impact on the workforce will almost certainly be significantly less  than the Goldman Sachs report suggests. The automation of some tasks – such as information gathering and synthesis – will likely free up time and capacity for knowledge economy workers to focus on working with these new technologies and so enable them to do more with less. And, indeed, do completely new tasks. Content development roles could shift, say, from editorial to moderation roles, while data scientists could find themselves spending more time engineering the data they work with – briefing and refining the work of generative AI tools – rather than preparing and running the analyses themselves.


In summary

It is these kinds of shifts that have led involved, invested advocates of generative AI – including such significant figures as Bill Gates – to declare that the age of AI has finally begun. For Gates, the world of technology has not experienced such a revolutionary leap forward since the widespread adoption of the graphical user interface more than 40 years ago.


To find out more, see our article on the limitations and watch-outs surrounding generative AI  and our separate piece titled “Putting the opportunities of generative AI into perspective.

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