Machines in the technological era of today are becoming extremely ‘self-aware’. In every walk of life, technology is replacing manual labor, thereby, contributing more towards the productive output. Advancement in technology based on a complex algorithm, integrated with greater computing and processing power, has removed many constraints.
Machine learning, in a way, a driving force of Artificial intelligence whereby a machine is programmed with the ability to self-teach and improve its performance. Data is the new oil and machine learning is all about analyzing Big Data- automatic extraction of information and using it to make predictions. Applications of machine learning, algorithms and platforms are helping businesses find new models, improve product quality, efficiency and optimize operations.
Machine learning is a part of the pie – Artificial Intelligence. Although similar, but different; both are revolutionizing global industries in stunning ways.
The idea of robots replacing teachers may sound farcical, but robots assisting in the education sector is no longer a distant dream. Although technology has already moved into classrooms with interactive smart boards, laptops, Wi-Fi, etc. artificial intelligence will further improve a student’s learning experience by providing differentiation on a level beyond manual teaching. Designed by a program using machine learning, such applications will help a student receive an individual learning plan which addresses their unique learning style and needs. Certain algorithms can analyze test results, thereby reducing the time spent by teachers on grading. A student’s academic history will help determine lacunae in their knowledge, grasping power and learning disabilities. Machine learning will facilitate the learning environment to enhance productivity and outcomes on both teacher and student.
Machine learning is taking an important part in our everyday health and is being used for faster patient diagnosis. We can term it as a game changer in the healthcare sector. With predictive healthcare gaining momentum, prevention of illness is aided by forecasting potential health problems a person may be susceptible to, based on gender, age, socio-economic status, genetic make-up, etc. Usage of programs to analyze and refer against databases containing gazillion other cases and illness has led to faster diagnoses of illness, thereby ensuring effective treatment. Researchers are using AI algorithms to detect tumors accurately in radiology scans, and machine learning is being adapted to enhance further research towards curing cancer. Machine learning systems are making personalized healthcare a reality today.
The financial industry is the hub of data- it’s renowned for a large amount of data it holds- from transaction data to customer data. This ever-increasing volume is unlikely to decrease in the near future. Financial institutions are using complex algorithms to assess loan risk, make real-time portfolio adjustments based on market fluctuations. Not just this, the finance sector would rely heavily on these technologies to detect fraudulent transactions and pave the way for a safer and more secure online transaction. Since AI and machine learning software processes humongous data, it will also help evaluate decisions while making investments and help financial advisers with ideal investment plans.
The most renowned and popular application of machine learning is in driverless cars technology. Connected cars are the talk of the town and an in-thing in the automobile industry right now. Predictive mechanisms have been accurate in telling the drivers about the probable malfunctioning of parts, help with routes and directions, emergency and disaster prevention protocols and much more. The future will witness cars responding to real-world conditions via machine learning and intelligence. The future is not far off where AI and machine learning will become an integral part of the aviation sector too. Imagine a 13-hour flight without a pilot!
Just like the financial sector, the manufacturing industry collects a huge amount of data from sensors and applications attached to every aspect of the production line. AI and machine learning now form an inevitable part of the manufacturing sector as a whole. The most widely used application of machine learning in the manufacturing sector will be in anomaly detection. Also, AI-based bots and machines will help in solving supply-chain concerns and inefficiencies over a wider geographical area, thus helping in minimizing shipping and delivery timing of products.
Technology is like an octopus which has its tentacles in every industry. With advancements happening rapidly day-in-day-out, machine intelligence is no longer a science fiction fantasy.