3 Ways in Which Machine Learning Has Made 2018 into a Powerful Year
The idea of Artificial Intelligence, and robots that are eerily human-like, have always found a special place in the human imagination, and especially in the science fiction movies and literature. While it’s more of an AI bubble that the world seems to live, and that bubble does get burst time to time, there are scientists who have made significant breakthroughs in the file do ML and AI.
We are here with three major AI and Machine Learning trends that the year 2018 has been open to, because of the strides this technology has taken till now…
Human-Machine interactions have greatly simplified
NLP, that is Natural Language Processing has been fast growing branch of Artificial Intelligence which deeply focusses analysing and understanding human languages. The reason we think it has evolved so much, is because even the more fine nuances of speech, dialects, pronunciations, and context have found an understanding in NLP. Whether it’s customer service chatbots, or virtual assistants like Amazon Echo, Cortana, Alexa, etc, or even the recruitment portals in enterprises – NLP has sure been making its unique mark everywhere.
AI Tools can be seen unifying with Development Platforms
It’s a fragmented ecosystem where AI platforms and tools have had a number of vendors offering different capabilities, and therefore creating a competitive market. Even though most of the developments in the field of Artificial Intelligence are still their infant stages, and the business on the other hand have been maturing over the years, the technology still has a considerable hold. But, there is the more traditional computing services, like the cloud-based ones, which hold a bit of edge over many AI startups. The infrastructure and scale which a cloud service provider can give access to, is significant to develop AI platforms and Big Data for all kinds of businesses. ET Brain, that belongs to Alibaba Cloud, is case in point for the same, as it chooses to combine Big Data and AI capabilities to make powerful platform for business of all sizes.
ML models are finding a headway into various industries
The simple aim of machine learning is to make it possible for computers to learn from various data, and further make improvements on them without being dependent on any program commands. The concept has made its headway into many financial applications with Fintech startups challenging the traditionally used inefficient advisory and distribution methods. ML and Big Data has also helped churn the massive potential which the medical data in today’s world holds. Apps are being made which can successfully identify diseases, provide the correct diagnosis, and even help in clinical trials, gene sequencing, predicting any epidemic outbreaks, and other R&D processes. The ML algorithms are also greatly helpful in making industrial applications that cover everything that entails in a manufacturing lifecycle, including initial product design, production planning, optimizing the production, distribution, and so on.