Google has created a cloud-based service that enables users to train their own artificial intelligence (AI) systems without having to resort to writing code.
Google's Cloud AutoML - the ML standing for machine learning, of course - enables AI systems to be trained in image recognition using a drag-and-drop interface, rather than arduously coding the intelligence in.
The AutoML initiative was originally publicised by Google last year at its I/O conference, where it discussed the concept of creating machine-learning software that can create its own machine learning software, removing error-prone puny humans from the equation.
However, Cloud AutoML isn't quite as advanced as that initial vision touted by Google, but it does give organisations the option to start training their own AI models, based on Google's platform.
Only a handful of businesses in the world have access to the talent and budgets needed to fully appreciate the advancements of ML and AI
Previously, Google has offered pre-trained AI models for developers to tap into through application programming interfaces (APIs), but Cloud AutoML allows them to train their own AI models from scratch.
"Currently, only a handful of businesses in the world have access to the talent and budgets needed to fully appreciate the advancements of ML and AI. There's a very limited number of people that can create advanced machine learning models.
"And if you're one of the companies that has access to ML/AI engineers, you still have to manage the time-intensive and complicated process of building your own custom ML model," explained Fei-Fei Li and Jia Li form Google's Cloud AI division.
Cloud AutoML will make AI experts even more productive, advance new fields in AI and help less-skilled engineers build powerful AI systems
"Cloud AutoML helps businesses with limited ML expertise start building their own high-quality custom models by using advanced techniques like learning2learn and transfer learning from Google.
"We believe Cloud AutoML will make AI experts even more productive, advance new fields in AI and help less-skilled engineers build powerful AI systems they previously only dreamed of."
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