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Google wants to make AI easier to use, starting with image recognition

Google wants to make AI easier to use, starting with image recognition

"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", the post said. It is a technology akin to Google's image search tool that can quickly retrieve photos on the web based on what a person searches for.

2017 saw the release of the Google Cloud Machine Learning (ML) Engine to help developers with ML expertise in creating models that work on data, and the Google Cloud is aiming to make its AI capabilities become one of its platform's major selling points. While there are already custom AI options (Microsoft can fine-tune its trained AI models for you), Google's approach is simple and hands-on enough that your favorite website or device maker could roll AI into their products with relatively little effort. Its drag-and-drop interface lets you easily upload images, train and manage models, and then deploy those trained models directly on Google Cloud.

Google has been adding machine learning capabilities to its range of cloud services for some time and a year ago claimed AutoML was better at coding AI tools than human programmers.

AutoML has not launched publicly, but interested companies can request access via this form. You can also store the training data in Google Cloud Storage. Google says it will also be offered as an option for businesses in India. Specifically, it's looking to "automate the product attribution process by recognizing nuanced product characteristics like patterns and neckline styles", says Urban Outfitters Data Scientist Alan Rosenwinkel. Creating and maintaining a comprehensive set of product attributes is critical to providing our customers relevant product recommendations, accurate search results, and helpful product filters; however, manually creating product attributes is arduous and time-consuming. In an video-call interaction, Google Cloud's chief Scientist of AI/ML Dr Fei Fei Li explained that when it comes to machine learning, it is still a fairly expensive investment.

Machine learning systems that create custom models, especially in the vision space, are nothing new. "Cloud AutoML has great promise to help our customers with better discovery, recommendation, and search experiences". The technology was developed through collaboration with multiple other internal AI teams, she said. "We want to reach out to them all, and make AI accessible to these developers".

This new service goes beyond Google's existing portfolio of cloud machine learning services, which are either aimed at assisting with the broadest number of applications, or helping existing machine learning practitioners streamline the process of plying their craft. "But you can still build a highly accurate machine learning model".

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