Machine Learning is at present, the most trending topic in IT. The chief reason behind its unmatchable popularity are the unlimited use cases and machine learning serving from price prediction to fraud detection, and even self-driving cars. Machine learning is increasingly becoming more valuable as the technology matures, several businesses are likely to use cloud offering machine learning as a service (MLaaS). It will allow a wide number of organizations to enjoy benefits of machine learning without making large investments. Here we will have a discussion about the possible technologies and services to be a part of machine learning.
Quantum Computing: Machine-learning involves problems like manipulation and classification of huge number of vectors in a high-dimensional space. The standard algorithms that are currently used can be time consuming for solving such problems. Quantum computers are more likely to be excellent at manipulation of high-dimensional vectors in large spaces. All the development of quantum machine learning algorithms whether supervised and unsupervised hugely increases the vectors and their dimensions exponentially quickly than the classical algorithms. All this is likely to lead to a massive increase machine learning algorithms processing speed.
Collaborative Learning: Collaborative learning is all about using various computational entities to get them collaborate in producing better machine learning results than the traditional methods. For example, using IoT nodes sensor network, often termed as edge analytics. With the evolution of IoT, it is expected that a large number of discrete entities will be used for machine learning in numerous ways.
Better Unsupervised Algorithms: Unsupervised machine learning arises with no labels, given to the algorithm, and is left on its own to find a structure in the input data. Not surprisingly, unsupervised learning is a goal in itself, which includes the discovery of hidden patterns or a resource in data, often known as feature learning. Possibly, such advancements in unsupervised learning algorithms will be a leading factor in building smart and accurate outcomes.
Deeper Personalization: A deep personalization sounds great, but it can be quite annoying. Having experienced recommendations that holds no actual relation is of no use. In the forthcoming times, users are more likely to receive précised recommendations and adverts that is not only effective, but also more accurate. With such advancements, user experience will improve vastly.
Cognitive Services: Cognitive Services and technology includes kits like APIs and more, using which developers are able to create more intelligent applications. Machine Learning will allow the introduction of intelligent features such as, vision and facial recognition, emotion or speech detection or speech understanding into the application. The future of machine learning is likely to be the starter of deep personalized computing experience for every user. Things that can or should happen in machine learning’s future, is just like the introduction of a new disruptive technology that will result into a future, we could never have imagined.
But does all these fascinating terminologies holds a future? Is it going to take us anywhere? And most importantly what after that? Well, whatever the next great leap be, it will surely be a big surprise for all.
