Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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When Sahil Singla joined the social impact startup Farmguide, he was shocked to discover that thousands of rural farmers in India commit suicide every year. When harvests go awry, desperate farmers are forced to borrow from microfinance loan sharks at crippling rates. Unable to pay back these predatory loans, victims kill themselves - often by grisly methods like swallowing pesticides - to escape the threats and violence of their ruthless debt collectors.

Singla and his team are tackling this social injustice with one unexpected but powerful tool: deep learning. Recent growth of computational power and structured data sets has allowed deep learning algorithms to achieve extraordinary results. Computers can now recognize objects in images and video, transcribe speech to text, and translate languages nearly as well as humans can.

Using deep learning, Farmguide analyzes satellite imagery to individually separate farms and accurately predict crop yields. In the US, Stanford University researchers have shown machine-driven methods for crop yield analysis to be comparably accurate as physical surveys conducted by the USDA. Armed with this previously unattainable information, Singla and his team can build superior models for lending and insurance, leading to lower and fairer interest rates for at-risk farmers.

The promises of A.I. extend far beyond the problems of Silicon Valley. While Forbes 400 multinationals and Wall Street hedge funds see A.I. as a tool for superior profits, entrepreneurs and engineers around the world see machine intelligence as a path towards a better society.

Karthik Mahadevan, an industrial designer and engineer from the Netherlands, employs deep learning to grant visually impaired patients more independence. He's testing A.I. technologies that assist them in daily tasks such as "identifying items in a supermarket and identifying their clothes." Tahsin Mayeesha, a university student in Bangladesh, leverages machine learning to analyze media reports of violence against women. With her detailed analysis, she hopes to highlight otherwise overlooked cases in order to generate empathy and awareness.

Inefficiencies abound that can be tackled with machine learning, but acquiring the requisite knowledge and resources to apply A.I. is a huge challenge for those who don't live in the Silicon Valley and other major research centers. Many turn to massively online open courses (MOOCs) provided by companies like Coursera, Udacity and Fast.ai as their only options.

Rachel Thomas, a deep learning researcher with a math PhD from Duke, started Fast.ai with Jeremy Howard, formerly CEO of Enlitic and President of Kaggle. Fast.ai's mission is to make "the power of deep learning accessible to all." As passionate champions of diversity and inclusion, the two created international fellowships to enable students like Singla, Mahadevan and Mayeesha to receive the best possible practical A.I. education. Read More


Source: Topbots