The potential of generative AI: creating media with simple text prompts Premium

While generative artificial intelligence has the potential to enable efficiency and productivity across multiple industries and applications, it can also create harm and adversely impact society through misuse, perpetuating biases, exclusion, and discrimination 

Generative AI is a cutting-edge technological advancement that utilises machine learning and artificial intelligence to create new forms of media, such as text, audio, video, and animation. With the advent of advanced machine learning capabilities like large language models, neural translation, information understanding, and reinforcement learning, it is now possible to generate new and creative short and long-form content, synthetic media, and even deepfakes with simple text, also known as prompts.

Top technology companies, like Microsoft, Google, Facebook, and others, have commercial AI labs researching and publishing academic papers to accelerate these AI innovations. In recent years, we have seen investments in GANs (Generative Adversarial Networks), LLMs (Large Language Models), GPT (Generative Pre-trained Transformers), and Image Generation to experiment and, in some cases, create commercial offerings like DALL-E for image generation and ChatGPT for text generation. For example, ChatGPT can write blogs, computer code, and marketing copies and even generate results for search queries.

For example, the prompt “What is Generative AI” in the ChatGPT1 tool generates the following text:-

Generative AI is a type of artificial intelligence that involves creating new, original content or data using machine learning algorithms. It can be used to generate text, images, music, or other types of media. Generative AI works by training a model on a large dataset and then using that model to generate new, previously unseen content that is similar to the training data. This can be done through techniques such as neural machine translation, image generation, and music generation. Generative AI has the potential to revolutionize many industries by automating the creation of content and enabling the generation of new ideas and concepts. However, it also raises ethical concerns about the potential for biased or inaccurate content to be generated and disseminated. It is important for developers and users of generative AI to consider the potential impacts and ensure that the technology is used ethically and responsibly.

Similarly, the prompt “futuristic athletic sneaker, digital art, 3d render on a yellow background with paint splashing in the air” in Microsoft Bing Image Create, generated the following image.

Below are some interesting use cases for generative AI; this is not an exhaustive list but offers a sense of the varied possibilities.

Generative AI can craft sales, marketing, and brand messaging. Agencies can generate personalised social media posts, blogs, and marketing text and video copies by providing a text prompt to a Generative AI service, like ChatGPT. In addition, the service can quickly iterate different text by simply tweaking the prompt to effectively communicate with the audience. DALL.E, a generative image generation service, can also generate original imagery to align with the branding. Many startups are exploring services like DALL.E2, Bing Image Create, Stable Diffusion, and MidJourney to create their brand logo and to align the same with Generative AI text messaging. Instoried is using Generative AI for marketers to become better copywriters.