Supervised Learning and Artificial Intelligence

Artificial Intelligence has gained tremendous momentum in recent history, whether it be through autonomous cars, the emergence of Amazon’s Echo, or applications that predict consumer behavior. However, through the hype generated by emerging applications has further blurred the expectations and the possibilities of Artificial Intelligence. Not to mention, the ethical aspects of Artificial Intelligence has further raised controversy. Regardless, the insights gained over the past five months has significantly shaped my view of Artificial Intelligence. Aspects like using Artificial Intelligence to cure some of the major issues in the world today like cancer and even using AI to make better decisions whether it is through supervised learning or unsupervised learning makes Artificial Intelligence a technology with a high ceiling.

It was barely a little over a decade when the frenzy of mobile devices gained traction in the technology world as Apple and Android competed with Blackberry to break into the market. This was significant as it was probably the genesis of the concept of Internet of Things. As more data became more available, Artificial Intelligence was being re-shaped through supervised learning. For example, data gathered from mobile devices allowed Google Maps to provide real-time traffic updates. This was probably one of the most revolutionary mobile applications at one point and the truly an example of how much data could potentially be gathered. This has also further shaped supervised learning. Based on the input gathered, advertisements became more catered to the user, businesses were able to further study consumer behavior. In summary, long gone are the days when a user has to manually enter information for a model to shape and provide insight.

Today, supervised learning continues to shape in a manner where image recognition is an area that is well invested in. This is largely due to the returns that it could potentially offer, whether it be in regard to security, image search, or tagging. As discussed in the article, Machine Learning Opens Up New Ways to Help Disabled People by Simonite, it is only a matter of time where similar to subtitles, a mechanism will exist on every YouTube video where speech to text will be automatically captioned. Similarly, Facebook continues to invest in Image recognition to automatically tag pictures. This would be beneficial for people with Autism. It provides an opportunity for active training as it clarifies misconceptions for Autistic patients. [1]

The future of unsupervised learning is something that is quite intriguing. Much research has been invested in research regarding this topic where approaches include clustering, anomaly detections and neural networks [2]. The future lies where Artificial Intelligence will allow diagnose the potential of being stricken by Cancer whether it be through image detection or through genetics. For example, a recent article published by BBC was title Artificial Intelligence “as good as doctors.” The article discusses the potential of having smartphones act like cancer scanners. This was based on software developed by Google, which was able to differentiate between cats and dogs. Similarly, the repurposed application is now able to some of the major types of skin cancer like carcinoma and melanoma. Similarly AI initiatives are taking place, which will be able to detect when the heart is likely to fail [3]

Finally, it is critical that the technology is used to benefit humanity rather than eventually replace humanity. Several highly regarded figures in science and technology have expressed concerns regarding the growing dependence on technology and the emergence of Artificial Intelligence. In addition, it is important to determine whether Artificial is generally hyped or if it is practically becoming a force. It has made strides in academia and research over several years but as it continue to gain traction and momentum in the eyes of the general public, it opens more doors of opportunity. In essence, time will be the judge.

[1] https://www.technologyreview.com/s/603899/machine-learning-opens-up-new-ways-to-help-disabled-people/?utm_campaign=add_this&utm_source=email&utm_medium=post

[2] https://en.wikipedia.org/wiki/Unsupervised_learning

[3] http://www.bbc.com/news/health-38717928