This Is the Year of the Machine Learning Revolution To predict the future, we look at the data we have about the past.
By Aytekin Tank Edited by Dan Bova
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In San Francisco, self-driving cars roaming around and people having conversations with Siri have become common sights. Just yesterday, Alexa told me that the meaning of life is 42. As machines become even more woven into our daily lives, we're witness to a new revolution that's taking over the world.
The AI revolution has clearly arrived, and it's here to stay. Just like past revolutions, the entrepreneurs who go all in will become tomorrow's giants. Henry Ford of the Industrial Revolution and Jeff Bezos of the Internet Revolution grew their companies because they envisioned a future that was very different from their present. They lived in the future.
Related: Has Artificial Intelligence Arrived At The Sales Function Yet?
Machine learning became mainstream in 2016. For the first time in history, machine learning is not only available to big companies like Google, Amazon or Apple. Startups have started building products and services using machine learning.
So, what is machine learning? Machine learning is learning from data. To predict the future, we look at the data we have about the past. Statistics and predictive analysis have been around for a long time. What's different today is that we now have the tools to use them for practically everything. For example, we have new specialized machine learning programming languages that can enable a junior programmer to build amazing things. We can now easily use machine learning for things like speech and facial recognition, language translation, data classification and object detection. Many tasks that previously could only be done manually, can be automated today using machine learning.
When Bezos started Amazon in 1994, he wasn't an expert on everything internet. He left a well-paying job on Wall Street, and he bet on the internet -- what he considered to be the future. He was a businessman, not a technical person. However, he took great efforts to understand the internet, and he used his business knowledge to find ways to take advantage of it.
Related: Tech Moguls Such as Musk and Bezos Declare Era of Artificial Intelligence
In the same way, you don't need to be a computer science expert to build your own machine learning startup. In fact, it is probably better to be knowledgeable in another industry and then solve problems in your industry by utilizing machine learning. You are more likely to be very familiar with the biggest problems in your industry that could benefit from machine learning in a major way.
Startups building on machine learning.
Companies are taking advantage of machine learning to create more powerful experiences. There are hundreds of them but let's take a look at some concrete examples.
- Forkable uses machine learning to figure out what you want for lunch before you know it -- automatically delivers it.
- Dark Trace listens to your company's network traffic and uses machine learning to detect emergent security threats.
- Nova uses machine learning to write personalized sales emails. It knows which emails performed better and suggests changes to your sales emails.
- Blue River Technology creates equipment for farmers that uses machine learning and computer vision to diagnose and treat each plant individually.
- Sift detects online fraud and prevents chargebacks using machine learning.
Machine learning as a competitive advantage.
Machine learning can also be a competitive advantage for your company. Let me give you an example from my own company. We are in the online forms industry. Our industry is in deep trouble with phishers. These criminals attempt to use our product to create phishing forms to trick people into entering their credentials for other websites. Our machine learning-based tools allow us to detect who should be banned and who should have access to our product. As a result, we"re able to continue to serve our legitimate users while our competitors embarrassingly block their websites to entire countries. Using machine learning to detect possible phishing activity allows us to continue to provide our free service all over the world, while keeping the bad guys out.
Another area where we use machine learning is marketing. We classify our users by looking at individual words and phrases used on their forms. Using this classification process, our marketing team sends customized email campaigns to different segments of users who haven't personally provided us with demographic information.
Related: 4 AI Technologies Impacting Business Operations Right Now
The revolution.
Look carefully at each thing that is currently being done manually in your industry. Every one of those tasks will be done tomorrow using machines. Entrepreneurs who disrupt their industries with machine learning will be the big winners of tomorrow. The machine learning revolution is here to stay. Join the revolution.