Published on October 16, 2023, 2:55 pm

Generative AI is a powerful tool that can write essays, debug codes, and explain complex subjects. It is being explored for applications in data augmentation, product development, and risk management. The technology has evolved to generate new content based on user text input, including text, code, images, simulations, and videos. However, there are potential drawbacks such as its energy-intensive nature and inherent biases. Proper governance and regulatory mechanisms are needed to harness the full potential of generative AI. While it presents new opportunities for businesses, caution and responsible use are crucial.

Generative AI, with its capabilities that surpass simple chatbots and query-answering features, has proven to be a powerful tool. It possesses the ability to write essays, debug codes, and explain complex subjects. This technology has caught the attention of investors who are eager to explore new applications across various sectors such as data augmentation, product development, and risk management, according to GlobalData.

Kiran Raj, the practice head of disruptive tech at GlobalData, explains that Generative AI has expanded beyond its conventional uses in tasks like malware detection, recommendation engines, and forecasting models. It can now generate new content based on user text input (text-to-x), including text, code, images, simulations, and videos. This versatility opens up a wide range of use cases in different industries.

Saurabh Daga, associate project manager of disruptive tech at GlobalData, adds that the generative AI space is experiencing two-pronged growth. Firstly, there is an evolving application landscape across sectors. Secondly, there is continuous improvement in AI models with a shift towards multimodality. He highlights OpenAI’s latest release – generative pre-trained transformer 4 (GPT-4), which goes beyond its predecessor GPT-3.5 by accepting images as part of the input prompt.

The GlobalData report titled “Text-to-X: how ChatGPT and generative AI can transform the future of business” emphasizes the transformative potential of generative AI for enterprises through key use cases like advanced search, content generation, customer management, and data augmentation.

However promising generative AI may be for businesses though it does have potential drawbacks that need to be considered. Saurabh Daga warns about its energy-intensive nature and notes that it’s not suitable for tasks requiring understanding, planning, and problem-solving. He also points out that generative AI models are prone to inherent biases. To harness the full potential of generative AI, there is a need for proper governance and regulatory mechanisms.

Generative AI presents new opportunities for businesses to automate tasks and create valuable content. Eager investors are exploring its potential applications, but it’s crucial to exercise caution and implement proper controls to avoid misuse. As Generative AI continues to advance, enterprises need to evaluate its capabilities and limitations while ensuring responsible use.

To learn more about the latest developments in Generative AI and its potential uses, you can read the full article “New use cases for Generative AI” on FutureCIO.

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