Machine Learning raises many questions: is it a complicated word to describe the same computer programs that we have been using for decades? Or is it a mystical computer capable of learning everything? More importantly, why is this of interest to your business? Light on this small revolution at the crossroads of big data and artificial intelligence
The most concrete way to define machine learning is to compare it with traditional computer programming. In traditional computer programming, specific instructions are written and executed by the computer to process the inputs supplied to it and produce an output. For example, an input could be a credit card request and the program would be an instruction to process that request, extract useful information, compare it with other data, and produce output.
Conversely, a machine learning program would not have a specific set of instructions for accepting or rejecting requests, but would learn from the data provided as input and would gradually and automatically improve its performance thanks to the experience acquired.
Machine Learning – a subset of artificial intelligence – improves its performance by analyzing a very large amount of data. It can fine-tune its parameters to adjust to the new data it receives, gradually improving its performance.
In the automotive sector, machine learning combined with ever-increasing computing power makes it possible to identify in real-time any obstacles that arise on a road, an essential skill for developing autonomous vehicles. This technology also allows predictive maintenance to be carried out on cars and other trucks in order to minimize accidents.
In factories too, machine learning makes it possible to adjust the maintenance schedule according to the data collected directly on the equipment, to avoid as much as possible breakdowns and the significant loss of profit that they generate for the company. Data analysis also makes it possible to optimize the complex production cycles of certain factories.
By dissecting data collected in-store on consumer behavior, supermarkets can, through machine learning, reorganize their shelves to boost sales. Machine learning also gives distributors the opportunity to optimize their inventory management.
In finance, this technology makes it possible to flush out fraudulent transactions by sifting through the bank data of buyers, but also to offer them ultra-personalized financial products, by compiling information collected through different channels.
Through machine learning, farmers begin to customize their cultivation techniques based on weather data and the unique characteristics of a given portion of their land. The objective is to produce more while polluting less.
Using sensors installed on their infrastructure and machine learning technologies that process the data collected, energy companies can predict in advance when their wind turbines (for example) are at risk of breaking down and send a maintenance agent.
Some software is able to diagnose a disease by analyzing the results of a scanner, a biopsy, or other types of medical tests. In the pharmaceutical sector, this branch of AI makes it possible to optimize clinical trials by selecting patients in a more relevant way. Laboratories will also be able to optimize their product launch strategies by combining a large amount of market data with the results of previous marketing operations.
Optimization of the allocation of resources for a harmonious urban development which maximizes the quality of life, improvement of public policy decisions thanks to the analysis of large datasets. The State also has advantages to be drawn from the use of machine learning.
The media can, thanks to this technology, compile data from different sources about their audience and offer their advertisers more personalized and therefore more lucrative advertising space.
Telcos will be able to optimize the very heavy investments they have to make to maintain their infrastructure by analyzing the data collected in the field by sensors. Machine learning will also allow them to create intelligent voice assistants, capable of handling the majority of calls that are now managed by employees in their call centers.
Machine learning allows players in the transport world to optimize their pricing thanks to a real-time analysis of demand, as shown in the graph below. In the world of travel, this software enables tour operators to offer tourists ultra-personalized offers.
The Volume of Data: More than ever before, we have access to very large amounts of data – structured but also unstructured (text, audio, images, and video). We can use this data to build systems that can learn from data.
Processing Power: The accelerated development of computer technology, including the massively parallel processing of GPUs (Graphics Processing Units) and cloud computing, has made processing large amounts of data faster and cheaper.
Open Source Software: open source communities focused on the development of machine learning programs and the provision for the learning of large amounts of data in open data contribute to the acceleration of the development of machine learning. For example, it is possible to use open source machine learning packages to process large amounts of image data to recognize specific images.
Machine Learning carries immense potential for creating products and services that are useful to society. Here are a few examples:
Machine Learning is not a miracle recipe but has the ability to help companies develop effective products and solutions to generate new sources of income. It opens up many horizons to better understand the data and make actionable recommendations that are more relevant than those resulting from human intuition alone.
As a Machine Learning and Artificial intelligence app development company, OneClick offers a massively parallel platform capable of delivering the performance and extreme speed of 100% flash technology to billions of objects and files. This can help speed up obtaining strategic information. Connect with us to leverage the benefits of Machine Learning for your business.