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Big data is undoubtedly necessary, but clean data matters more, according to Nilanjan Dey of Techno International New Town, a prominent AI technology expert. Delivering a special address at the Quantum Enhanced Sustainable Technologies for AI Systems (QUEST-AI), an international conference being held under the auspices of the AU College of Engineering, he said: “The nature of all machine learning algorithms is completely data-dependent.
The more data we give, the better the point estimate is likely to be, and the more generalisation we go for, the better the results will be. This is a traditional approach, but if we don’t provide the right data, the results will be the same. If the data is not scientific, the final results will also be flawed. There are no algorithms that can completely clean the data.”
“We need more data, and at the same time, it is very important to have very clean data,” he said, explaining with many examples that better results can be achieved if diverse data is provided.
A recent report said that on average, a doctor in India spends 2.8 minutes per patient, while in Bangladesh it is only 48 seconds. He stressed the need to make technology useful for them right now. He said that in India, only one doctor is available for every 366 patients.
He said: “Even if we have data, if it is not properly benchmarked, it will have no value.” He suggested the focus should be on ‘big data’ and ‘clean data’, not ‘variable data’.
Nabil Mohammed, a lecturer in the Department of Electrical Engineering at Federation University, Australia, delivered his keynote address on alternative energy sources. He explained the challenges of using and producing solar and wind power, and the role of technology. He discussed the challenges of convincing people, coordinating and managing them, and informing them about the issues that arise when setting them up.
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This article is written by Senior Journalist Lakkoju Nagesh Babu






