Artificial Intelligence (AI) has become dramatically popular over the last few years with Google and Amazon investing large amounts of funds into research and development of new systems using AI. With large companies adapting to the new shift towards AI, does that mean you as a startup should as well? Questions like, “Can I build a startup that leverages AI?” or “Where and how do I start using AI?” are going to be answered in this article.
Basic Understanding of AI
AI is often thought of like a robot that can perform tasks for you without you having to say or do anything. This is true to an extent, but an actual description of AI is, a software that you can input data into, it recognizes it and then it outputs some other form of data. This software can be in a microchip (something that you can put into your phone) or it can be software in a robot (like one of those automatic carpet cleaning robots).
The only difference between software for AI compared to other software is that for AI you do not have to write a code of steps that need to be performed in order to go from input to output, rather it is automatically determined by recognizing patterns from the input data. So in a way, it takes in certain information, looks for patterns and then based on the patterns recognized, it outputs a different form of data.
There are two broad categories that AI can be divided into (1) Existing AIs (can do common tasks that are needed in many different contexts and (2) Custom AIs (used for very specific tasks).
These AI software is focused around common problems or situations that have been solved with AI, for example, face detection in photos or speech recognition. Since these are common issues, they have been solved by a variety of different companies, each with its own AI software, which you can use by a “pay per use” method. For example Amazon’s Rekognition, Microsoft’s Face API and Google’s Vision API.
Custom AI software is based on specific niches designed to tackle problems that are very unique. An example would be detecting changes in the heartbeat of a patient and determining whether their condition is becoming better or worse based on the treatment given to them. In these situations, creating your own AI software is essential as there most likely won’t be something similar in the market. Creating your own AI software can seem fun in the beginning but as time progresses into development you realize relatively quickly the complexity associated with it.
There are many different technical approaches to AI, however, currently, the one that is getting the most attention is neural networks. Neural networks is based on the brain and how a bunch of neurons is connected together and if one is stimulated it causes a chain-like event to occur in order to stimulate certain corresponding neurons. Similarly, this idea is introduced into AI when it comes to taking in the input (from a series of data) and then resulting in a specific output, based on the initial data and the patterns recognized from it. An example of this could be the input being a bunch of photos with multiple different faces present in it and the output could be only those photos with a specific face present in it.
There are two steps to creating a neural network: creating the network (number of neurons present and connections between them) and then you also have to train it. Training a neural network is assigning a mathematical function to each node, so it can determine whether or not to pass the signal to the corresponding node or not. Training of a neural network is done by using a training framework, which feeds the network a large amount of data with the correct output in order to determine the math functions of each neuron. The combination of the size of the neuron and its connection is called a model.
When thinking about AI from a business context, the biggest problem you will face is: what data do you need and where can you get it from?
Four Essential Steps to Building an AI-Based Startup
Test Your Problem-Solution Fit
Like with any startup or business, if you are not solving a problem that people are willing to pay for then you don’t have a startup. Before you invest thousands of dollars into creating something, be sure that the problem you are trying to solve is a problem that people are willing to pay for, and that this is something that can actually be created. Also, the majority of the time you don’t have to go out and create an AI solution completely from scratch, you can use different parts of Googles or Amazons AI software, along with a mix of your own, to create a simple working prototype of the AI software that you wish to create. Then, after it has been validated and accepted, you can then go into investing large funds in order to customize it and further develop it.
Play the Data-Gathering / AI Building Game
Once you have reached the stage that you know there are customers out there willing to pay for your solution to their problem and you have created a base-level model of the AI software that you can solve this problem, then now it is time to test it out. This is often the most time-consuming and difficult part of building an AI-based startup. Determining where to gather the data, curate it to make sure it is useful and then design a model and train it is going to be the most challenging part since this takes a lot of time and determining the right data to actually use can be tough.
Build Your Product
By this point, you should have a working AI software, that if you use some trained models, it will generate the correct output for you. However, the use of trained models is not what the general public is interested in. Rather they want a software or an app that they can download on their laptops or phones, with a clean and easy to use interface, which can help them solve their problems. The next part of building an AI startup is focusing on the user experience of the product and creating it with the user in mind. Customers are not interested in the way the product works, instead, they are solely interested in learning something simple and quickly (such as how the app works) and then using it to solve the problem that it is designed to fix. So now it is time to package up your AI software into a product that users can easily use in order to solve their problem.
Improve your AI
The better data you can give your AI, the smarter and faster it will be. Once you have your product ready and people are using it, you will be flooded with data that you did not have before. In order to continue to grow your AI-based startup, it is essential that you use the new data being brought in to further train and develop your AI software. This will allow your product to become better and faster for users to use.
In conclusion, there can be many benefits associated with creating AI software for your business or creating an AI startup designed to solve a problem that customers have. The top AI companies in Toronto, are all focused on creating a user experience that is easy to follow, along with something that customers actually want and something that solves their problem. Here at IT Action Group, we have our team which is composed of 7 high-end developers in artificial intelligence and machine learning. We are an AI-based company, that helps build custom AI software for large and small companies, along with testing and data generation. We have been in business for the past 15 years and in the past few years upgraded our team with new members, in order to take on new AI-related projects. If you are a company looking to start something new with AI in mind, feel free to reach out to us and we help turn your idea into a reality.