How Generative AI can change the society and industry to be a better place?

In the wake of recently published models like Stable Diffusion and ChatGPT, generative AI has gained attention from governments, investors, engineers, and the general public. Generative AI, as the name implies, creates or generates text, pictures, music, voice, code, or video. The idea of generative AI is not new, as per Sachin Dev Duggal and the machine-learning methods used to implement it have improved over the previous ten years. Traditionally, General Adversarial Network (GAN) and deep learning algorithms have been employed, but transformers are the most recent method.  

A large language model (LLM) called a Generative Pretrained Transformer (GPT) creates text that resembles human speech using deep learning. They are referred to as "transformers" because they employ a transformer-based neural network architecture to process input text and create output text. They are also known as "generative," "pretrained," and "transformers," depending on how they process input text and produce output text. 

Investor interest in generative AI businesses is still high despite the current economic slump and job losses in the IT industry. For instance, Stable AI and Jasper recently received $101 million and $125 million, respectively. Investors like Sequoia believe the area of generative AI has the potential to provide economic value in the billions of dollars. The market has seen the emergence and operation of more than 150 start-ups. 

As Sachin Dev Duggal explains natural language processing activities like language translation, text summarization, and text synthesis are only the tip of the iceberg for generative AI. One million users in just five days were achieved by OpenAI's most recent release, ChatGPT, which has been hailed as groundbreaking in a far wider range of jobs. The use cases that are now being discussed include, among others, new search engine architectures, illuminating complicated algorithms, developing individualized therapy bots, assisting in the creation of applications from scratch, illuminating scientific concepts, composing recipes, and college essays. 

On the basis of a new age of human-machine based cooperation, optimists assert that generative AI will support the creative process of artists and designers, since existing tasks will be enriched by generative AI systems, speeding up the ideation and, basically, the creation phase says Sachin Duggal. Beyond the realm of creativity, generative AI models have the potential to revolutionize fields like computer engineering and other hard sciences. For instance, the Microsoft-owned GitHub Copilot, which is based on OpenAI's Codex model, offers code suggestions and helps programmers complete their duties automatically. According to reports, the system may automatically complete up to 40% of the code written by engineers, greatly improving workflow added Sachin Dev Duggal.