Once your company has decided to leverage AI, you must find the right tools to implement it. Fortunately, data science and AI have become more accessible, thanks to many new services:
- Open source libraries such as Tensorflow and Keras, based on Python and proposed by a growing community of developers, offer a quick way to develop AI-based proof of concept. More and more companies are moving towards these open sources technologies, which are now backed by strong communities, reducing the cost of licences of proprietary tools and software.
- Cloud platforms such as Microsoft Azure or Amazon Web Services offer ready-to-go AI modules, designed to fit models very quickly. For example, Microsoft Azure proposes a visual interface to drag-and-drop data tables and quickly try out different machine learning algorithms.
- Training for AI is easily accessible through MOOCs, such as Stanford Professor Andrew Ng's Deep Learning course on Coursera. This explains (for those with a good math background), how to implement facial recognition, speech recognition and more AIbased services.
It is essential to make sure that your company has the right internal resources, e.g. data scientists that have received AI training, in order to properly implement AI for your business.