What problems can we solve using AI?

In this article, we are going to go through what are some of the problems humanity in general and business is facing that we can solve leveraging AI.

If you made it this far with me you must be motivated to start a project and actually solve some real-life problems; humanity is currently paying the price of evolution, we crippled our giant blue marble and displeased immensely mother nature. But honestly, we had no choice!

Had we not done what we did, we would not have evolved as fast as we did and we would not have gotten where we are at the dawn of a new era where we will tireless AI-powered agents doing all the heavy lifting for us and in the process pushing the boundaries of what is possible faster and further than ever before giving us the time spared to be what we truly are, humans.

How can a fairly newborn technology like AI solve these complex problems that have been around for millennia?

One of the advantages of artificial intelligence is faster technological advancements. The more AI is used to research the faster it will learn to find patterns and results for many of the questions that the world is exploring. Imagine having artificial intelligence that runs through thousands of simulations electronically in order to find cures for many of life’s ailments. This would free up researchers to devise new parameters and objectives. Who knows someday with the help of artificial intelligence we might find the cure to cancer as well.

What problems is humanity facing currently & can AI help to solve them?

I’m not going to list all of them.

Most of the problems that are listed below are resource management and allocation problems; leveraging AI we could monitor the usage resource, availability resource and have custom-fit solution to many of this problem.

Furthermore, we have some problems that are directly linked to the technology available at the moment. Let’s take energy, for example, there is only a hand full of people in the world that can finance a large scale natural energy project like the Gigafactory or rooftop solar panel tiles and the reality is that we need to democratize those solutions and make it available worldwide especially in developing countries — the only solution is AI, because it can help us figure out how to produce it in a cheap and an efficient way.

  • Energy
  • Environment
  • Food and water
  • Disease and Human Suffering
  • Education
  • Population

I believe that all of this problems can be tackled using AI.

Some ideas on how we can apply AI to the real-life problems?

AI is here to stay and what I mentioned in the previous paragraphs is a way of showing what kind of problems we can tackle leveraging AI at the moment.

Let’s do this !!!

I’m not going to talk about AI application in the broad spectrum, I’m going to talk about some applications that will inspire you as an individual or small team to build some amazing AI-powered projects for fun, business or research.

First of I’m going to talk about problems that have been solved leveraging exactly two subfields of AI namely: ML and DL

Machine Learning (ML)

Is it the traditional way of doing AI but don’t be fooled ML is still a very powerful field such that big companies like Amazon, Apple, Google and amongst others still use to automate services and systems.

They also provide ML and other subfields of AI as a service to customers.

Let me give you an example:

  • E-commerce has become a multi-billion dollar industry and most of us make online purchases of items.
  • Following that train of thought when we are about to a purchase; sometimes we are shown this option that says that other people who bought this item ( let’s say white shirt) also bought this item( black trousers). This is an example that illustrates a Recommendation system in action.

The recommendation system is a system that recommends items to shop based on your buying habits or others who have bought the same item and their ratings.

Are we on the same page here?

If not, here is a scientific answer for it.

Recommender system or a recommendation system is a subclass of information filtering system that seeks to predict the “rating” or “preference” a user would give to an item.

Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general.

Deep learning

Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.

Deep learning has become the single hottest topic at the moment, every company, group or individual involved in AI is talking about it, learning or implementing it. The giants also kneeled before its might and are investing billions on better hardware so they can leverage its full potential.

Many businesses use DL internally for Dev ops and also offer it as a service. One example of DL in action is Autonomous systems they rely on object detection and other sensor data that only DL can make the complex mapping and give the right output.

Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new “superpower”.


We now have a foundation which we can further improve our human lives and advance deeper and in a pace never seen before in the history of mankind.

My question to you is the following :

Do you want to be a part of this new era or not?

Thank you for reading. If you have any thoughts, comments or critics please comment down below.

If you like it and relate to it, please give me a round of applause 👏👏 👏(+50) and share it with your friends.

There is so much more coming… I’m going to make a series of topics in relation to the project I’m working on.

Follow me if you want to join me on this adventure on data jungle. :D

Source: Deep Learning on Medium