About AI
What is Artificial Intelligence?
The big difference between traditional software and AI is in the word “intelligence” itself. Traditional software does not contain any intelligence, it can process a lot of data quickly in the same way. AI contains intelligence with which it can interpret, classify, visualize the data, … these were previously human tasks that can now be transferred to the AI. So you could say that AI is further automation of what used to be a (simple) human task. Further automation enables us to do even more as humans than was previously possible.
AI thus opens up a wide spectrum of new opportunities that were previously not possible due to physical or technical limitations.
What is Machine Learning?
Machine learning is an application of artificial intelligence (AI) that allows computers to learn autonomously from data and input using algorithms. Computers learn on their own and thus continuously improve their algorithms. Machine learning is used in self-driving cars, spam checks, medical diagnostics and, for example, facial recognition on your mobile phone. Not everyone realizes it, but we are actually confronted daily with devices and services that are possible thanks to machine learning.
It is therefore becoming increasingly important for enterprises to understand what machine learning is, what the possibilities are and what impact this technology will have in the future.
What is Deep Learning?
Deep learning is in fact a part of machine learning. It can handle a wider range of data sources, removes the need for feature engineering but requires large collections of data. In deep learning, interconnected layers comprised of “neurons” are stacked to form a ‘deep neural network’. The network can absorb and process massive amounts of input data through multiple layers that learn more complex characteristics of the data at each layer. The network can then make a decision about the data, knowing whether the determination is correct and using what it has learned to make decisions about new data. For example, if it learns what an object looks like, it can recognize the object in a new image.
Deep learning is used, for example, in medical image recognition and speech recognition on your mobile phone. Or think of AlphaGO from Google Deepmind.
AI is above all a cultural change
The most important change has to take place in the culture of the company. Inter-departmental collaboration and information sharing must be encouraged to make the adoption of AI successful.
It is therefore also essential that the strategy around the implementation of the AI is supported by the entire company.
If you were to ask any person on the street today if they ever use machine learning, the answer would probably be negative. In that case, your conversation partner has no idea that this is indeed the case. Someone who asks Apple’s Siri for a weather forecast is dealing with machine learning. Google’s ever-improving search results? That’s machine learning. Less spam in your inbox? Also machine learning.
The fact that most users do not realize they are dealing with the technology is one of its most powerful aspects. The technology works unnoticed in the background and achieves results that speak for themselves.
But what can machine learning do for your business? In this white paper, we discuss definitions, different techniques and the opportunities that machine learning offers you.