How Generative AI is Transforming Digital Content Services

ChatGPT Sparks Public Awareness of and Growth Opportunities for AI Platforms, Start ups, Cloud Providers, and Dataset Vendors

From its conception in the 1950s to early 2023, artificial intelligence (AI) underwent a series of improvements, from machine learning (ML) to deep learning (DL), which enabled it to mimic human responses (conversational AI), identify images (computer vision), and generate digital text, images, audio, and video, among other content types (generative AI or GAI).

No technology in recent memory has captured the public's imagination as has GAI in the form of ChatGPT. Released by OpenAI in late 2022, ChatGPT is the fastest-growing consumer application that reached 100 million downloads in just 2 months after launch. ChatGPT serves as a chat-based interface for users to generate all manner of text-based media, such as code, essays, and reports, among many other response types. Other forms of GAI create audio, video, images, games, and 3D models, among other digital content.

The combination of AI algorithms, dedicated processors, cloud computing, and large, categorized datasets led to the tipping point of GAI with the release of ChatGPT. Writing responses to questions, essays, and reports is a fairly universal use-case. Using GAI to write code, craft marketing copies, and summarize legal contracts, among other media, will lead to use cases that will impact entire industries, such as integrated development environments for programmers, photography and image manipulation tools, video editors, and 3D modeling tools.

GAI will be integrated into such tools over the next several years. It can alleviate mundane work, and its integration into consumer applications and media creation tools will be like the integration of electricity into our daily lives. It will soon just be part of the functionality of the software- a digital assistant to create, inspire, review, and summarize work in the form of digital content. GAI transforms digital content through new use-cases that replace how consumers and enterprises currently create it. As models develop to provide new capabilities, enterprises will replace old workflows with new ones until they find which steps GAI and humans do best. This repeats as new model capabilities emerge.