The Rise of Machine Learning & Why We Need to Adapt Now

By Lexie AndersonTABS Score Marketing Team

I, Robot (2004)

It’s 2020 everyone… and we are living in an era straight out of a sci-fi movie (WALL-E and self-driving cars come to mind, where humans do little but sit back and enjoy the ride). However, we resist this mass automation because, quite frankly, it scares the sh#t out of us. While some advancements in this field are incredibly futuristic and somewhat frightening (have you seen Sophia, Hanson Robotics’ most advanced human-like robot? — it’s terrifying), countless aspects of our everyday lives are already dependent on machine learning technology. In layman’s terms, machine learning is the study of computer algorithms that improve automatically through experience. For the non-tech nerds, it’s a subset of artificial intelligence. As this field of advanced technology grows rapidly by the day, acceptance will be our first step to these increasingly important changes. News flash, we aren’t waiting for a world run by AI and machine learning; we’re already living in it. (Mic drop)

(Just kidding — *picks mic back up*). To illustrate the already current impact that AI and machine learning has on our society, we’ve decided to break it down and make it clear just how often you may utilize it in on a daily basis without realizing it:

· Virtual Personal Assistants (Alexa, Siri, Google). Do you find yourself frequently saying “Hey Alexa”, or “Hey Siri”? If so, then you’re already being bossed around by a machine. If a mistake is made when responding to your question, they will use the data from the original inquiry to automatically improve for next time.

· Traffic predictions (Waze, GPS). Massive amounts of people rely on traffic apps every day in order to find the fastest route to their destination. Waze, for example, monitors reports from millions of other wazers in order to provide real-time travel information for users. Because why not trust a random stranger with severe road rage?

· Ridesharing Apps (Uber, Lyft). Also, on the topic of transportation, countless people rely on ridesharing apps to get to and from locations without a personal vehicle. Ridesharing apps like Uber predict the times and locations of high demand to automatically set prices based on past data.

· Social Media (Face recognition, suggested friends). Today, social media controls our lives, even more than your mother. #IYKYK. Machine learning has integrated into social media through the use of features such as facial recognition, suggested friends and pages, advertisements and much more. So, your “little FBI friend” is always looking out for you and your next shopping spree via targeted ads.

· Investment Due-diligence (shameless TABS plug) Did you really think we weren’t going to add TABS to this list? The TABS Score algorithm automatically updates and improves with each new data set it receives. In return, investors, incubators, and founders, can use this information to make informed, science-backed decisions based on the most up to date recommendations.

· Online grading (Turnitin). For students, plagiarism has become next to impossible with the rise of machine learning in grading applications (Sorry, kids). Turnitin, for example, analyzes a student’s past work as well as compares it to other works on file to ensure original content.

· Automated transportation (Trains, airplanes, boats, etc.). While self-flying airplanes are still in the works, airliners are already utilizing machine learning in a variety of ways, from fuel consumption automation to real-time passenger feedback analysis.

· Medical Care. The medical field has been known to adopt machine learning practices early on as a way to streamline standard procedures. Today, machine learning is used to develop new medical procedures, treat chronic diseases, and handle patient records. In the future, it is likely that machines will take over the surgeon’s position as a more reliable and safe method of surgery (hopefully the robot doesn’t decide to turn evil mid-kidney transplant). In related news, the National Institute of Health awarded Florida International University $1M to develop machine learning algorithms to study proteins. This information is crucial in understanding and treating various diseases. In the past, the study of one protein could take months, if not years. The use of machine learning could cut this down to mere minutes or even seconds, enhancing our understanding of disease significantly.

· Home security. Smart home technology has become increasingly popular in recent years, with millions of users desiring an extra layer of security for their property. Smart home technology uses machine learning for object detection, sound analysis, speech recognition and more.

And this is only the tip of the iceberg. Virtually every industry has been affected in some way, and if you haven’t caught up….well you better get moving. Those who haven’t begun to adapt are quickly falling behind. The team at TABS has capitalized on this trend by using machine learning to provide companies with a holistic due diligence analysis of risks. Our algorithm constantly updates to provide users with the most efficient and personalized recommendations to ensure success for their early-stage ventures. As more data enters our system, the algorithm continues to grow more advanced and has the ability to provide sound predictions for better decision making. Welcome to the future. Are there even going to be any jobs left? Asking for a friend!



DaaS (Diligence-as-a-Service) platform providing a holistic & in-depth qualitative evaluation of an early-stage venture. Powered by FSLTD.

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DaaS (Diligence-as-a-Service) platform providing a holistic & in-depth qualitative evaluation of an early-stage venture. Powered by FSLTD.