Deep learning is a broad field of research with the objective of creating artificial intelligence that is capable of instructing itself to perform tasks rather than relying on algorithms. In theory, this would allow AI to succeed at tasks that would be prohibitively difficult, resource intensive, or time-consuming for a human developer to work on. However, deep learning requires dedicated experts to oversee and develop the AI, undermining some of the intent behind having AI that can self-teach. If you need an expert on hand regardless, why do you need an AI capable of deep learning? AWS and Microsoft seek to change that.
In October, AWS and Microsoft announced that they were working together to create Gluon, an open-source deep learning library. Gluon brings together training algorithms and neural network models, critical components of deep learning. With these in place, developers at a wide range of skill levels have access to the essentials of deep learning development and can begin to make their own inroads.
The companies have stated that Gluon is currently intended to assist with creating machine learning models for cloud-based applications, mobile apps, and any dedicated devices that may need AI. The crucial detail is that it is open-source, making any progress easier to share and improve upon. If Gluon proves successful, it could represent a major step forward not merely for Microsoft and AWS, but the entire development community.
This isn’t the first effort from these two companies to improve AI. Indeed, Syncfusion has discussed Microsoft’s efforts to work with AI and the open-source community several times before when Microsoft unveiled the Zo chatbot, open sourced Powershell, and joined the Linux Foundation.
But it does represent perhaps most clearly the intention to open up AI development to a wider audience. With any luck, we’ll all benefit from more and better AI as a result of initiatives like these. If you’re interested in AI, be sure to check out Machine Learning Using C# Succinctly and Microsoft Bot Framework Succinctly.
