AI is one of the key technologies set to transform both our personal and professional lives in unprecedented ways. According to a recent study from Stanford University, in the last 20 years there has been a 14-times increase in the number of AI startups, while in the UK, funding for AI developers from venture capital increased more than 200 per cent in 2018.
At the same time, the AI space has seen a growing number of technology giants – including Microsoft, Salesforce and Uber – open-sourcing their AI research.  Investing, or “giving back,” to the open source community has helped developers worldwide create and improve AI & Machine Learning (ML) algorithms faster. Open source software is now crucial to driving fast, reliable, and secure development in the AI space. But why did both industry giants and start-ups alike decide to embrace openness, and how will it affect technology and science moving forwards?
Why enterprises are turning to open source
Open source software started to play a significant role in IT development across industries following the launch of Netscape Navigator, the first open source program, in 1998. The strategy Netscape chose was to emphasise the business potential of sharing the software’s source code. As with science, if all researchers kept their methods secret, progress and innovation would take place much more slowly. With developers racing to deliver “the next big thing”, secure and easy-to-deploy software frameworks are essential to supporting this.
The high costs of AI and ML model development are usually driven by the computing power required, as well as having enough data in place to build and train an advanced model. Additionally, the skills gap is usually a big challenge for enterprises – according to recent reports, despite the availability of millions of AI-focused roles globally, there are only 300,000 professionals able to

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