India ranks 10th with $1.4 billion private investment in AI, US tops Top 10 league
India ranks 10th with $1.4 billion private investment in AI, US tops Top 10 league
India has ranked tenth in terms of private investment into artificial intelligence (AI) with a $1.4-billion inflow, according to data from Bond Capital. The US has topped the league with investments over $67 billion, the global technology investment firm said in a release.
The data comes at a time when the government’s thrust is on AI with initiatives such as the IndiaAI mission and Global IndiaAI Summit.
On the list, China is a distant second at investments of nearly $8 billion, trailed by the UK at almost $4 billion. The other countries that have received maximum private investments include Germany, Sweden, France, Canada, Israel, and South Korea, in that order.
These AI investments underscore the US’ ability to attract capital, talent, and the overall ecosystem to push for the nascent system, which promises to revolutionise the world of technology.
The data published in Bond Capital’s report, Will Master’s of Learning Master New Learning, shows that out of the 17 global publicly listed companies whose market capitalisation exceeds $500 billion, 14 are domiciled in the US.
Nine out of these 17 companies are into the tech and AI space, with all of them based in the US, such as Microsoft, Nvidia, Apple, Alphabet (Google), and Amazon.
The report highlights that new-age internet companies reach 100 million users much faster than those founded in the early 2000s. For example, companies like Netflix and LinkedIn took nearly a decade to achieve this milestone, while newer platforms such as OpenAI's ChatGPT did so in less than six months.
The US dominance is not limited to investments alone, it is also home to over 60 machine learning models, with China far behind at 15 models. India does not appear on the list.
A machine learning (ML) model is a system that uses data to identify patterns and make predictions or decisions without being explicitly programmed to perform the task. It learns from examples and improves its performance as it processes more data.