As anyone can tell simply from looking around on the street or going online for a few minutes, technology is rapidly progressing. While those born only a few decades ago never imagined something like smartphones being in everyone’s pockets, those born today take for granted the ubiquitous quality of these mobile devices and the knowledge they have access to. No technology is a better representative of the digital future we live in more than recent advancements in Deep Learning and artificial intelligence.

Since these two technologies and areas of study do seem to be straight out of a science fiction novel, we decided to take time to give a brief overview of them in this beginner’s guide. Our hope is that with this knowledge, you will be better prepared for an uncertain, yet exciting future. With this in mind, let’s first take a look at some definitions.

deep learning

What is Artificial Intelligence or AI?

Artificial intelligence is defined as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” Already today we see the beginning of AI entering our everyday lives, but soon it could be a fundamental part of our society.

While today AI helps us to decide the best course of action when it comes to traffic or which shoes to purchase, proponents of the technology believe that with advanced enough systems we may be able to soon identify diseases before even the best doctors can. This is an exciting thought and could explain why 80% of enterprises today are investing in AI in some form.

However, as with anything there are those who fear the progress of AI. Before we look at why this discussion is so important to be having at 2018, let’s take a look at deep learning, a more advanced form of artificial intelligence that is picking up steam in the tech industry.

What is Deep Learning?

Deep Learning is a subset of machine learning or Artificial Intelligence, that “has networks capable of learning unsupervised from data that is unstructured or unlabeled.” In other words, an AI software can perform specific functions at a high speed, but a Deep Learning software can come across a new problem and create its own solution with comparable efficiency.

So far, ventures into both Deep Learning and AI technology have been built around the use of Big Data and database management. While this has been beneficial to some, with Google leading the charge on creating these AI devices and technologies, others believe that we need to move past data and create something closer to a human brain than we are currently capable of.

No matter which camp you fall into, it seems as if there is no stopping the inevitability of machine learning and the continuous advancement of artificial intelligence. With this mindset, looking to the future we need to start thinking about the why of AI and deep learning as much as the how.

Why this is important

Thanks to the likes of Philip K. Dick and shows like Black Mirror, many have apprehensions surrounding the world of AI. After all, what happens when a machine surpasses a human in regards to intelligence? Some might view this creation as something closely related to a god, while others will see it as a threat. As technology continues to be pushed forward, we need people on both sides asking the right questions in order to ensure something closer to the middle of this equation takes place instead.

Now that you have a better understanding of the basics of Deep Learning and AI technology, as well as allowed me to get on my soapbox for a minute, let’s take a look at the uses of AI in digital processes and the future of the industry as a whole.

Uses of AI in digital processes

When you begin to look at the use cases that are quickly cropping up for AI, you may start to think that AI can solve just about anything. From advanced collaboration to predictive insights, Deep Learning does have the potential to radically change the way we interact with our digital world. By making things more efficient and ‘smarter,’ we can save time that would otherwise be spent with these process and put it towards something more productive.

Or at least, that is the hope. Unfortunately, some believe that if AI is used for the wrong purposes, it can lead to further subjugation and control. In order for these best practices to be taken seriously, we need to use what we know about Deep Learning to create even better systems that take the human aspect of things into consideration. In this way we can use AI to improve the lives of all, not just a select few.

Beyond neural networks

In order for Deep Learning and AI technology to improve further, data scientists and AI developers will need to move beyond neural networks and establish a system that can both think for itself and operate off of large amounts of data. Currently, large, complex neural networks can only grow as large as the computers they operate on and as fast as those computers work. Even with all of the AI advances we have already had, we are still far from the artificial intelligence that we have come to see on screen.

Even with all that being said, there are instances of AI that give us hope for the future. IoT and wearable devices are becoming more popular, algorithms dictate large parts of our social interactions, and Deep Learning has already been helping doctors with diagnosing disease. As long as we continue to push forward in the right direction, even those who oppose Deep Learning will likely see the merit in AI and an automated future.

The future of intelligent systems

Which brings us to our final thoughts: the future of intelligent systems and our place within them. In the same way that customer-centric marketing and UX design have become popular recently due to their human-centered approach, we should also keep the human component at the center of AI. How can these advances better serve us and our world? Instead of focusing on what we can do, we need to talk about why we are building it and what it is capable of.

In order to truly build a better world for us all, these are the values that Deep Learning and AI developers need to construct their technologies upon. Our hope is that as the future becomes more clear, we will have put the right foot forward and made strides towards creating a better place to live. We remain optimistic that AI is a capable of helping us get there.