This is the fourth installment of a six part series from our recently published whitepaper; A fundamentally different approach for building intelligent industrial systems. You can download the complete paper here.
The Bonsai Platform
Underpinning the complete Build-Teach-Use lifecycle of an AI model, the Bonsai Platform abstracts away the complexity of machine learning libraries like TensorFlow. Using Bonsai, developers, data scientists and subject matter experts can more effectively program and manage AI models.
Key benefits from using Bonsai to program your AI models include:
AI-enable your development team. Bonsai allows developers to focus on programming concepts unique to a specific problem domain, leaving the management of complex, low level AI mechanics to the Bonsai AI Engine
Reuse and share your code and models. Programming of intelligence at a higher level of abstraction enables code and model reuse. System libraries and shared models can be leveraged across development teams.
Debug, inspect, and refine your AI. The high level models produced by Bonsai enable you to understand what contributed to a prediction, identify conceptual gaps and bugs, and constantly refine your models.
Build models independent of underlying algorithms. As machine learning and deep learning algorithms evolve, your Inkling code can be recompiled and retrained to take advantage of low-level technology advances.
Host and collaborate on existing models. Interoperability with existing machine learning models allows data scientists to expand the functionality of the platform, and extend these capabilities for use by your development teams.