EarlyBirds Is Leveraging Machine Learning To Help Entrepreneurs Change The Future Of Business
EarlyBirds, a global open ecosystem for innovators, early adopters and subject matter experts is encouraging its members and other interested parties to use machine learning technologies to stand out in the competitive business landscape.
Though machine learning as a concept has been around for decades, the recent jump in raw computing power has opened up brand new avenues for harnessing its capabilities. It has found use in a variety of industries such as manufacturing, personal electronics, transport, automation, security, and many more. The scientific literature surrounding machine learning and deep learning (a subset of machine learning) is being updated every single day as new discoveries unlock the potential for newer, previously unthinkable solutions and applications.
The biggest area where machine learning shines is in the domain of data processing and analysis. Machine learning is particularly suited to the task of extracting hidden, not-so-apparent conclusions from a large dataset. The ubiquity of data-collecting sensors thanks to the Internet of Things (IoT) and the capability of storing vast amounts of data create a fertile ground for applying machine learning techniques to realize patterns that until now lay invisible to business leaders.
An example of leveraging the analysis of large quantities of data made possible by recent developments in machine learning is in the domain of fraud detection. Bank systems can be trained on historical data of credit card fraud to detect similar patterns in incoming transactions. If the system detects a fraudulent pattern, it can raise an alarm and potentially save the bank and the account holder thousands of dollars.
Another distinct advantage of machine learning is the ability for software to make decisions on its own, based on how it gets utilized by the end-user. Usually, programmers would be tasked with documenting and accounting for all the edge conditions that a piece of software might have to deal with. Machine learning cuts through this process and gives a system the ability to gain feedback for its actions and “learn” from its mistakes. This leads to more robust systems that can adapt to the way the user chooses to apply them.
An example of a “smart” system that uses decision-making to benefit the end-user is that of a home electrical grid. A smart house that has been equipped with sensors can monitor a home for readings such as temperature, time of day, occupancy, and more. The system can then modulate electricity consumption in a home, based on the measured parameters to create a comfortable environment for its residents while at the same time saving on energy costs.
A spokesperson for EarlyBirds talks about the future of machine learning by saying, “We are standing on the cusp of a large upheaval that will forever change the way software is programmed and implemented. Every industry that was thought to be mature and grandfathered is learning of new ways that it can stand to be optimized. A lot of research money is being poured into devising models that push the efficiency of current systems higher, ever so slightly. Even tiny improvements in model accuracies are yielding dividends to companies to the tune of millions of dollars because of the sheer scale of their operations. There has never been a better time for a business owner to take advantage of the data its system is generating to squeeze out the last bits of efficiency. The technology not only increases profits but also improves the user experience.”
EarlyBirds has created a an open ecosystem and platform where innovators who have a finger on the pulse of their domains can network with business leaders and subject matter experts who hold the keys to the kingdom. It is a mutually beneficial setup where upstarts get a chance to reap the rewards from their innovations while business owners get to benefit from cutting-edge research before their competitors get an inkling of the progress that is being made. EarlyBirds also has subject matter experts with deep industry and domain experience available to assist early adopters and innovators to take advantage of machine learning. Innovators and decision-makers can find out more about the platform and its advantages by heading over to its website at https://earlybirds.io.
For more information about EarlyBirds, contact the company here:
Mr Kris Poria and Mr Jeff Penrose
+61 401 287 060