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The Future Ahead With ML May 6, 2017

Posted by Rani Sebastian in Machine Learning.

“Machine learning is the next internet” -Tony Tether, Former Director, DARPA

This field of Artificial Intelligence where we get computers to program themselves is now making the news almost daily with novel findings and advancements in every day applications. I don’t even need to make a list of applications of ML to show how big a part it plays in our lives now.

ML is significant because it is changing the way we look at problems, gives us new insights about the problems we are trying to solve and in this process, discovers brand new applications as well. These applications can be further extended either by themselves or combined to be applied to other completely unrelated fields. Technological advancements in general and in other fields are also impacting further development of ML. New strategies to ML are being researched both in terms of hardware and software approaches. The hardware improvements in GPUs and others make large scale deployment of ML a reality. Latest ideas in software approaches gives more options to explore from the software side.

Personally, I am not a fan of Super Intelligence or AGI – nothing against it, but I still feel that a combination of human-machine will be much more powerful. “The repeated failure of autonomous cars has made one point clear – that even learning machines cannot surpass the natural thinking faculties bestowed by nature on human beings. If autonomous or self-guided machines have to be useful to human society, then the current Artificial Intelligence and Machine Learning research should focus on acknowledging the limits of machine power and assign tasks that are suitable for the machines and include more human interventions at necessary checkpoints to avert disasters.” [1] We may not even be able to reach the level of AGI in the immediate future, but the results we already have shown that we must invest in research in ML with reliable data and wise integration in mind. Also, I think it is important that we channel the ultimate goals of AI/ML into common beneficial applications rather than concentrating on corporate profit motives. Employed to the “right” purposes, AI-ML can be a powerful tool. AI ethics by itself is another topic, but it is time we addressed some of the ethics and accountability issues, for change is coming around at a rapid pace. Many well-meaning implementations have backfired, like Microsoft’s chat-bot Tay which had to be taken offline after it ‘learned’ to be racist. Dangers of AI is the other side of the coin. By ‘danger’, humans losing their jobs to AI is not the only concern. Many prominent figures including Stephen Hawking have quoted on the dangers of super-intelligence. Autonomous cars have been proved not completely immune to infiltration by now, will it happen with autonomous weapons too? Will AI be abused by governments or corporates to stifle out conflicts? Research communities work best when they include people with different views and different sub-interests, and AI research must stay grounded in reality. [2] My personal viewpoint is that we should focus on beneficial ML applications which are easily accessible to the common man. There is immense potential for ML in the fields of preventive health care, assistive applications, banking and so on that could make the world a better place. That is also another reason why ML/AI should be democratized and not vested to a single corporation.

Keeping the hypes aside, ML road ahead looks bright. With the current technology trends, we can expect cheaper but more powerful hardware, memory and storage solutions in the coming years. Advancements in cloud, IoT and smart apps fields will only pave a steady increase for ML applications. And that is exactly why Machine Learning is important – because of the endless possibilities it holds for us.

“A breakthrough in machine learning would be worth ten Microsofts” – Bill Gates



[1] http://www.dataversity.net/2017-machine-learning-trends/

[2] https://www.prospectmagazine.co.uk/britishacademy/the-ai-debate-must-stay-grounded-in-reality



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