Overview:
Over the last 18 months or so, there has been a lot of progress in what is known as “Generative AI” as the next frontier in the world of machine learning. The market size of this technology was valued at $10.8bn in 2022 and is expected to grow at a CAGR of 27% in the next 10 years.
Also known as GANs (Generative Adversarial Networks), this technology employs two neural networks, one generative and one adversarial, that collaborate to generate synthetic data that is indistinguishable from real data.
There is a lot of excitement in the tech world after OpenAI released ChatGPT in Nov 2022 – giving normal users a chance to test out the real power of AI in natural language processing.
While large scale commercial use is still a way off, generative AI is expected to drive the most significant change in business since the industrial revolution.
ChatGPT is the first step towards real disruption…
While versions of GPT have been around for a while, ChatGPT crossed a threshold: it is genuinely useful for a wide range of applications and takes powerful technologies out of the hands of experts and puts them in the hands of everyday users.
This democratization of access has huge implications and creates extraordinary opportunities. For example, the increasing popularity of “no code / low code” software will enable an increasing number of non-expert users to create their own powerful mobile and web applications.
Just as machines augmented muscle in the industrial revolution, AI can augment brainpower in the cognitive revolution. This is helpful to creative users such as copywriters, computer coders, scriptwriters, and artists among many others.
This also has big impact on areas as diverse as the automation of customer services, marketing material, scientific research, and digital assistants.
Large scale applications and path ahead:
From Google’s Deep Mind to Adobe’s Deep Filter to Amazon’s recommendation engine, generative AI has penetrated the world of high-resolution imaging, online shopping, and optimizing logistics routes.
While there are concerns over the AI’s impact on human jobs, these recent advancements in AI technology are paving way for a human-machine-hybrid workplace.
Most industry experts theorize that while AI will be able to learn and execute more complex tasks in the near future, a “human-in-the-loop” is essential to ensure that the output is relevant and useful.
Generative AI is expected to be transformative in the coming years as the limits of the current language model are completely unknown. Using the public mode, people have used ChatGPT to do basic consulting reports, write lectures, produce code that generates novel art, generate ideas, and much more.
We even tried writing this article through ChatGPT! The output was good, however, some of the relevance and context was lost. Hence, we will have to wait a while before our machine overlords take over.