He said Large Language Models have resulted in an exponential efficiency boost, adding that programming tasks by junior developers are at risk with AI’s rise. Zerodha’s chief technology officer (CTO) Kailash Nadh, who has a PhD in Artificial Intelligence and Computational Linguistics, spearheaded the development of Kite, the company’s core trading platform and is leading the company into its tech future amidst rising competition. In an exclusive interview, he talks about using large language models (LLMs, or machine learning models that can understand and generate human language text from vast amounts of data) heavily to help with technical tasks, saving significant amounts of time. There is widespread decentralised innovation happening in AI technologies in the open-source world and there are new breakthroughs and improvements coming out on a weekly basis. Zerodha has been experimenting with self-hosting some of these open-source AI tools for making internal back office-related organisational tasks more efficient, he says. Excerpts:
It’s widely believed that Artificial Intelligence (AI) will impact the job market, and there will be severe redundancies. At the same time, humans have the creative power to tide over such a situation, and they have done it in the past when the machines threatened their jobs. At this point in history, where’s the balance at?
AI technologies are multi-dimensional, unlike other technologies. For instance, a student, lawyer, researcher, writer, and a software developer can all use the exact same LLM tool to seek direct solutions to different kinds of problems in their respective areas. This is very different from how generic tools like word processors provide means to problem-solving. This time, I feel it is different, when even the very idea of creativity in the context of this new set of technologies has become a hot philosophical debate.
Of course, we have to consider common sense. In the name of automation and efficiency we cannot sacrifice the right decision. For instance, in matters of insurance claims. Relying on AI, to make high impact decisions isn’t a good idea yet, and those should remain with humans who are accountable for them. Some guard rails should be in place for critical areas and regulations on this are a global debate. You had earlier said generative AI is a genuine breakthrough unlike most fads in tech. Why did you say that? Can you mention some of the tech that surprisingly turned out to be fads later?
These technologies work surprisingly well. Language, text, speech, imagery, videos, and tools powered by generative AI technologies have been commoditised in no time and have become widely available for daily use. Hundreds of millions of people use them directly on a daily basis. I personally have been using LLMs heavily to help with technical tasks, and they have been saving me significant amounts of time, which simply was not possible before.
Of course, there is plenty of hype surrounding these technologies, but there is significant substance underneath it as well. There are so many fads in technology. Remember blockchain, which was meant to revolutionize the world? Or ‘Big Data,’ which became a buzzword, where every organization was meant to reap untold benefits from massive amounts of data? What about 5G? It was meant to revolutionize everything from mobility to ‘smart cities’ and whatnot.
