If you're a talented machine learning engineer you should never have any issues getting employed.
Let’s examine some important data to back this audacious claim.
Machine Learning Engineer was rated at the number one best job of 2019 according to a popular job seeker site .
Figure 1: Best jobs of 2019 - indeed.com.au
As you can see in the table above, the number of job postings for machine learning engineers increased by an incredible 344%!
With such a high demand it’s no wonder why the average base salary of a machine learning engineer is $146,085.
Future applications of machine learning
Vehicles that ask for help.
While the application of deep learning in vehicles is not a novel concept, the US military is promising to take it to a whole new level by using machine learning to alert users about possible breakdowns and damage before they even occur.
This innovative application of machine learning is the brainchild of Chicago-based tech company Uptake .
To help you appreciate the genius behind this innovation, it's important to understand the key differences between planned maintenance and preventative maintenance.
Think of planned maintenance as your general motor vehicle maintenance. You do it every month in order to (hopefully) prevent damage due to wear and tear.
Predictive maintenance on the other hand would alert you of any damage that is likely to occur.
For example, with this technology embedded into your gearbox, sensors would warn you if any particular component of your gearbox was in danger of failing.
We know of many seniors who would love this technology embedded onto their forehead!
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Machine learning is making its way into the medical space in order to help doctors predict the likelihood of an individual dying prematurely.
A comprehensive study compiled data from mortality logs as well as lifestyle factors affecting health from over half a million people aged between 40 and 69.
Machine learning algorithms were then used to create a model capable of predicting the premature death of a middle aged individual due to chronic disease.
These machine learning algorithms produced the most accurate results to date!
But it’s not all doom and gloom. This area of innovations opens the doors to an exciting new field of preventative medicine.
If scientists are capable of accurately predicting the death of an individual well in advance, they can also implement the necessary steps to prevent it from even happening.
No, this doesn’t mean that you will grow Wolverine claws and live forever, but what this does mean is that eventually all death will only be due to natural causes.
Thanks to machine learning, the future of medicine will be personalised treatment specifically tailored to your unique requirements.
This is quite groundbreaking, we are on the forefront of a thrilling technological renaissance.
Machine learning applications are no longer only limited to the field of specialized robotics. We're now living in an age where machine learning is becoming a natural integration of every aspect of our lives.
Since there's a generous overlap in the application of machine learning and artificial intelligence, the demand for AI technology is also expected to increase aggressively in the upcoming years.
So if you never want to worry about being out of a job, definitely pursue a career in either machine learning or data science
The promised future applications of AI almost seem like a projection from a science fiction novel.
Future applications of artificial intelligence
If you thought Siri’s response to the question “what is zero divided by zero?” was impressive, you haven’t seen nothing yet!
With AI’s application to the field of online assistance, you'll soon be unable to distinguish a human conversation from a robot one.
Just take a look at this AI powered virtual assitant created by Soul Machines .
But AI powered virtual assistants won't only be limited to the virtual world. Pretty soon every new vehicle will come integrated with its very own personal assistant.
BMW has promised to integrate an AI assistant in their new line of vehicles.
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Simply telling the vehicle that you're feeling too hot will prompt the air conditioner to start blowing cool air.
Not only will an AI assistant give you access to your vehicle via voice commands, but it will also keep your vehicle secure.
There will be a time in the near future when your face will be the only key you need for your car.
With specialized sensors, and a whole heap of fancy math, prospective drivers will need to pass biometric authentication before being given access to a vehicle.
Great news for anyone prone to losing their keys. Unless you’re Joan Rivers, you will never lose your face!
But it doesn’t stop there. By having the ability to recognize who's driving, this technology will be capable of providing each driver their own unique, personalized driving experience!
So after scanning your face, your vehicle will know your ideal seat setting, your preferred temperature setting, etc.
Byton , an electric vehicle startup, is pioneering this audacious venture. They've promised to release their first electric vehicle with this technology by 2020.
Perhaps in the future, your car may even have the ability of cheering you up with the perfect song if you’re looking a little down.
Natural language processing
Since AI and machine learning technology is quickly becoming a natural integration of our day-to-day activities, there's a growing demand for perfecting natural language processing.
To give you an idea of the incredible scope of this demand, the Natural language market is expected to be worth more than $16 billion by 2021 .
Natural language processing (NLP) is a computer’s ability to understand what humans are saying.
In other words, the transformation of speech into computer commands.
Alexa and Siri are far from perfect, and we still have a long way to go before a computer is able to effectively carry out all of our requirements flawlessly via voice commands.
The reason for this is that the human language is VERY complex.
Syntax and semantics are incredibly difficult concepts for a computer to understand.
In order for NLP to really start taking off, a computer needs to effectively understand inference rather than just literal meaning.
The future of machine learning and Artificial Intelligence is an incredibly exciting one.