The future of machine learning is here. This is the future of technology, and possibly the future of work. It’s hard to say what the future holds for these programs, as nobody can actually tell how things will evolve. Will we have computers that can remember everything that we have done? Or will we be stuck in a single world, with machines creating our every wish? No matter what the future holds, one thing is for certain. There will always be people who will use this technology to benefit them in one way or another. Those who see the future for themselves will undoubtedly agree with those who predict that machine learning will become the predominant method used in society in a decade from now.
- Quick Learning
- Unsupervised Learning
- Shift from Traditional to Modern methods
- Data Collection & Sharing
- Automated Engineering
Machines are fast learners. They can learn and memorize extremely quickly, thanks to their highly efficient artificial intelligence. Humans, on the other hand, are not so efficient when it comes to learning. We are not natural computer hardware. We are still very much humans, with all the awkward tendencies and natural hesitations that come along with our inherent personality.
Humans are also one of the slowest learning machines out there. We tend to get frustrated if something doesn’t work the way we expected it to. In addition to this, we aren’t good at replicating our mistakes. If there is to be a future of machine learning, then it is only logical that we as humans would have to adapt a bit to deal with the software that makes the system work. The current methods, if extended to the entire machine learning field, will become extremely complicated.
Shift from Traditional to Modern methods:
Luckily, the future of machine learning does not entail a massive shift in how we do things. We are still able to utilize a few basic methods in machine learning, which have been around for years. These methods may be a bit clunky for some new users, but they can usually be worked around. Most people are simply unaware of how simple they really are. After all, these methods have been utilized for decades! What’s changing?
Data Collection & Sharing:
One of the biggest things that will be changing is the way that data is captured and shared. Currently, it’s fairly easy to capture information from a human using a voice or text message. It becomes a bit more difficult to capture the same data, say from an artificial intelligence system. How will this impact the future of machine learning?
Consider this scenario: One day, a machine is built to recognize faces. After months of research, it is able to tell the difference between a human and a monkey. This is fantastic! But imagine that after several years of development, this technology is available for anyone who wants to buy it. Suddenly, everyone around the world could have a super intelligent, artificially intelligent machine that everyone wanted to talk to! Can you see where this could go?
How about self-driving cars? In the near future, self-driving cars will be the normal norm. Your car will communicate with you and the computer in your garage. It’ll tell the car owner how hard they should drive, and what speed they should be at. They will never crash or break down, and you won’t have to sit in the driveway worrying about the safety of the machine behind you.
What about self-piloted planes? Well, if you programmed a machine to fly without piloting it, would you be comfortable with that? You betcha! Why, just think about all of the benefits of controlling your own plane by hand – wouldn’t that be great!
It’s going to be exciting in the future when artificial intelligence machines are able to do many different types of work. Of course, humans are still needed for the beginning stages, but after that point it’s a machine full of data and knowledge, a machine learning system, which can learn on its own and provide solutions to customer problems. Will there be a place for the average person in this future? Probably not, but it certainly will be interesting to see over the next decade or so. Who knows?