'Generative AI will revolutionise how businesses function': Experts

Why you are reading this: Generative AI is capable of producing various types of content. This is also one of the most widely discussed aspects of AI.  The apprehension around Generative AI taking over jobs is still a much discussed topic and cannot be ignored. ChatGPT, DALL-E and Bard are all recent models which have proven the potential for image generation, text generation and music suggestions. Experts believe Generative AI can revolutionise businesses.

3 things you need to know:

• Generative AI is not a new term, it has been used in the industrial application since 2014.
• Industries across the globe ranging across industries like Media, IT and Healthcare are gradually enhancing their operations with the use of Generative AI.
• The entire concept of Generative AI is based on GAN (Generative Adversarial Network) which is a machine learning model and is the framework for Generative AI.

Various new emerging applications are fuelled by the concept of Generative AI. Tech giant Amazon has announced that it plans to use Generative AI to summarise reviews whereas Meta has also announced plans to use Generative AI in almost all its products. Content management system 'WordPress' has said it would be using the concept to enhance content writing. Experts are enthusiastic about its potentiality.

"The potential of generative AI is seemingly limitless. It will revolutionise businesses, take them in new directions, and open new opportunities. The impact it will have on our daily lives can only be envisioned, but impossible for anyone to grasp the reality of the changes to come," Spiros Margaris, Venture Capitalist and founder of Margaris Ventures told Republic. 

“By harnessing the power of Generative AI and automation, we are reshaping the way businesses operates in an era of competitive landscape. This synergy brings about unparalleled innovation leaps that benefit businesses across industries from healthcare to manufacturing and financial services. By streamlining operations, the Automation Success Platform has improved customer service, enhanced overall efficiency and ensured that businesses’ stay ahead of the competition while upholding their ethical standards," Prince Kohli, CTO, Automation Anywhere told Republic.

"Companies are investing heavily in Generative AI capabilities and have aggressive roadmaps for building more customised applications and making products easier to use. At Intuit, we are building on our rich data foundation and existing AI platform, and recently unveiled the Intuit Generative AI operating system (GenOS). GenOS is a proprietary capability we developed to build and run GenAI based applications, making it simple to create GenAI experiences" Radhika Kanan, Principal Technical Program Manager, Intuit AI told Republic.

5 popular applications of Generative AI

1. Content generation: ChatGPT and Bard have been the most discussed products of Generative AI. One can search for any generic information and the algorithm helps generate information. It is widely used in the marketing, gaming and communication sectors to generate conversations, headlines or advertisements.

Limitation 

• Lack of information in the AI system would not provide accurate results always.
• There have been concerns about the wrong and biased information being passed on by the system.

2. Image generation: This can be called an approach to turning words into images. The algorithm in the image generation system analyses the text and the description given by the user to generate real-time images which would be used in the media, design, manufacturing, marketing and education domain. 

Limitations 

• AI can not be accurate to represent correct human forms. 
• Copyright issues persist as the algorithm finds it hard to identify images that are free.

3. Music generation: AI systems can generate music based on the text description it has. This can generate short clips of songs and can also work on existing melodies, or any note played by an instrument. 

Limitation 

• Copyright violations
• Apprehensions around training data that is scraped from the web without the creator's knowledge.

4. Coding: A trait which has been exclusively handled by the IT industry, a Generative AI model will help everyone who wishes to write a programming code. It is beneficial to those working in startups who rely on websites and applications for running their businesses. 

Limitations 

• Understanding multiple programming languages is a concern.
• AI is not at present trained to handle complex issues in the coding domain which will gradually need manual intervention.

5. Text-to-speech generation: This can be done for students who are visually handicapped. Businesses can take benefit from this because of the wide range of linguistic options as it can also eliminate the barriers of language across borders. 

Limitations 

• Different languages in the world need to be added to the AI model.
• There can be errors in the interpretation techniques used by the AI model.