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Chennai-based start-up raises funds to focus on Artificial Intelligence

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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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IAM Platform Curates Today’s Trending Topics | Artificial Intelligence

iam platform curates today’s trending topics | artificial intelligence

IAM Platform Professionals get the research done to present the content you need to stay fresh and relevant. These sources are carefully curated for you by hand to allow you to stay at the cutting edge of Artificial Intelligence. Enjoy!

Definition of Artificial Intelligence from Wikipedia

In computer scienceartificial 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.[1] 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”.[2]

As machines become increasingly capable, tasks considered to require “intelligence” are often removed from the definition of AI, a phenomenon known as the AI effect.[3] A quip in Tesler’s Theorem says “AI is whatever hasn’t been done yet.”[4] For instance, optical character recognition is frequently excluded from things considered to be AI,[5] having become a routine technology.[6] Modern machine capabilities generally classified as AI include successfully understanding human speech,[7] competing at the highest level in strategic game systems (such as chess and Go),[8] autonomously operating cars, intelligent routing in content delivery networks, and military simulations[9].

Artificial intelligence was founded as an academic discipline in 1955, and in the years since has experienced several waves of optimism,[10][11] followed by disappointment and the loss of funding (known as an “AI winter“),[12][13] followed by new approaches, success and renewed funding.[11][14] For most of its history, AI research has been divided into sub-fields that often fail to communicate with each other.[15] These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning“),[16] the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences.[17][18][19] Sub-fields have also been based on social factors (particular institutions or the work of particular researchers).[15]

The traditional problems (or goals) of AI research include reasoningknowledge representationplanninglearningnatural language processingperception and the ability to move and manipulate objects.[16] General intelligence is among the field’s long-term goals.[20] Approaches include statistical methodscomputational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimizationartificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer scienceinformation engineeringmathematicspsychologylinguisticsphilosophy, and many other fields.

The field was founded on the assumption that human intelligence “can be so precisely described that a machine can be made to simulate it”.[21] This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. These issues have been explored by mythfiction and philosophy since antiquity.[22] Some people also consider AI to be a danger to humanity if it progresses unabated.[23][24] Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.[25]

In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.[26][14]

ATTRIBUTION: Wikipedia contributors. “Artificial intelligence.” Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 17 May. 2020. Web. 19 May. 2020.

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