Today, great minds are already wondering about the implications of AI, with experts like Elon Musk and others even petitioning against the use of AI in warfare. While many organisations continue to look at AI as a science fiction concept, the truth is that the future is already here. We needn’t wait around for humanoid robots to begin preparing for the business of tomorrow.
Today, everything from drones to self-driving cars are showing us that Artificial Intelligence is very real and very present. Though it might be tempting to wait for something like the “Turing” test to inform us that the next generation has arrived, AI is actually emerging in more of an invisible way. It’s appearing behind the scenes, automating huge data sets and making decisions on the behalf of your company. So, the question becomes, how do you prepare for the changes now?
1. Get Plenty of Data, and Data Scientists
First, AI needs huge amounts of data to learn and thrive. You need to figure out exactly how much data you need to gather depending on how much AI you want to implement. If you’re doing statistical forecasting, for instance, then you’ll need less information than you would for deep machine learning.
At the same time, you need someone with enough experience in the world of technology to understand how to put all the statistical models required for AI into account. In other words, you’ll need to think about hiring efficient data scientists to help you get the most out of your new technology.
2. Track and Analyse the Right Factors
Even with all the data, you could want, and the experts you need to assess that data, you might not have the right information for all the variables that matter. Take the time to think about exactly what you need to measure in your AI solution before you get started.
At the same time, make the decision to step back and perform statistical analysis on the data you gather once you’ve received it. Clean up the data that you receive, and implement a process that will help to ensure that the answers you get from your AI are accurate and intelligent.
3. Make Sure You Have Enough Power
Finally, the bigger your data set is going to be, the more layers you’re going to need in your business to manage your AI development. Having a lot of data will help you to train a better AI model, but it also means that you’ll need a lot more training time. Make sure that you have the right budget, time, and computing capacity to train the models that you need.
As you progress into the future, you’ll need to make sure that you can also update your models periodically, and enjoy the benefits of the trial and error tests you implement. Remember, AI is complex, but if you want to take advantage of it, the best time to start is now.
Rob is Founder & Publisher of UC Today, a leading news publication specialising in Unified Communications & Collaboration technologies.