Superintelligent machines – as new species – can hold tremendous advantages in mental capability, a vastly superior knowledge base, and the skills to multitask.

Interview:

Q: What did you work on?

A: My research paper reviews the current status of the methods – such as artificial intelligence, machine learning, and deep learning – and their automation’s result in superintelligence.

Q: Why is this work important to you?

A: Data is rampant in the Internet of Things (IoT) Age, during which the exponential growth of data has outpaced the capacity of traditional computing. It has reached maturity in some stages, but it is in adolescence in new stages. With the advent of Big Data, businesses are merging it with big compute and IoT for analytics using Artificial Intelligence (AI). After the raw input from the big data gets cleaned, structured, and unified, AI performs cognitive functions and outputs values for the business. With its ability to analyze massive amounts of data in milliseconds, it can now be processed in “real-time”. In data science, the “hypothesis-first” approach has been moved to “data-first” approach. In the near future, big AI will be ruling many different industries and also in software. It is already an emerging asset in health care, finance, management, education, transportation, and manufacturing, and it is revolutionizing the operations. Since computers can solve problems, they compare any information and decide what it signifies. The human brain consists of nerve cells or neurons, which constantly transmit and process information received from the senses in milliseconds. Likewise, deep learning architectures use multiple layers of artificial neural networks on input data to abstract and composite representation. Although mimicking the human thought process is far away, robotics is a growing field of research and design with the goal to recreate human intellect. Following that, the superintelligent machines – as new species – can hold tremendous advantages in mental capability, a vastly superior knowledge base, and the skills to multitask.

Researcher Bio:

Ankur Patel is a researcher with a passion for data science, motivation in healthcare, and ambition in business. He is currently a graduate student pursuing a M.S. in Data Science, and has previously graduated with a B.S. in Biomedical Engineering.

You can read Ankur’s paper here.

Thank you for sharing your paper with us, Ankur! If you are currently a student and also doing research in the field of AI, reach out to me at charmaine.lee@aiforanyone.org and let’s chat! We would love to feature your work.

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