Chennai-headquartered Vakilsearch, an online platform for legal, tax and compliance services, has raised an undisclosed sum from technology growth investor Sujeet Kumar, co-founder of Udaan. Prior to Udaan, Mr. Sujeet was president of operations at Flipkart. The start-up intends to use the funds raised for engineering, specifically in machine learning and AI (artificial intelligence). Hrishikesh Datar, CEO of Vakilsearch, told The Hindu that when it comes to business registration pan-India, his start-up has helped in incorporating 10% of all new private limited companies. He said, “Close to 70% of the companies we set up stay with us for ongoing GST, RoC, and accounting support. We see COVID-19 as an opportunity, with businesses increasingly going online to stay compliant and seek professional help,” he added. The start-up has earlier been funded by Kalaari Capital and investors including Rajiv Luthra, founder of Luthra and Luthra Partners, Delhi, and Sanjay Kamlani, founder of Pangaea3 among others. “We have raised over $3 million of capital to date,” Mr. Datar said. Vakilsearch helps businesses with registrations, incorporations, accounting, filing, annual compliance, and legal documentation. The start-up also offers services including tax filings, property agreements, and consumer rights protection.
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Definition of Artificial Intelligence from Wikipedia
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Leading AI textbooks define the field as the study of “intelligent agents“: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”.
Artificial intelligence was founded as an academic discipline in 1955, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an “AI winter“), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into sub-fields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning“), the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences. Sub-fields have also been based on social factors (particular institutions or the work of particular researchers).