Figure Eight has had a long, fruitful history with IBM. They’ve used our platform to curate training data for some of their most innovative AI products and services. IBM is a big believer in the power of the human-in-the-loop workflow and we take a great deal of pride in helping one of the most successful companies in the world realize some of their most ambitious machine learning projects.
Today, we’re thrilled to announce that Figure Eight is not just helping train, test, and tune models for IBM, but we’re now integrated within IBM Watson Studio itself. This new partnership opens up some of our most successful use cases–namely image categorization, natural language categorization, sentiment analysis, and content moderation–to IBM’s thriving Watson Studio community of machine learning scientists.
Watson Studio customers will be able to sync their data directly from Watson Studio to Figure Eight via this in-product integration. They’ll have access to the features and functionality of the Figure Eight platform, with the ability to code custom logic, write their own unique instructions for workflows, enjoy our full suite of quality controls, access our pool of skilled annotators, and more. As their data is annotated it becomes immediately available in Watson Studio. This can easily facilitate a continuous learning loop, where new data can be constantly annotated and leveraged, thus preventing data drift, optimizing models, and improving algorithmic performance.
Here’s a quick look at how it works in practice:
As we mentioned above, we’re rolling out four use cases for the Watson Studio community. Our integrated experience supports:
- Image categorization: This template allows you to create a custom ontology to classify and categorize image data.
- Natural language categorization: Similarly, you can classify text for intent, content, or any other classes your model requires.
- Sentiment analysis: Here, you can provide any kind of text data you’d like analyzed for sentiment. It’s important to note that our platform also supports conditional logic and reasoning behind sentiment, allowing you to get to the “why” not just the general opinion.
- Content moderation: Everyone has their own rules for what content is allowable on their application. This template allows you to define exactly what you consider acceptable so that we moderate your content your way.
You can watch the talk Ruchir Puri, Chief Architect for IBM Watson, gave at this year’s Train AI conference or check out IBM’s blog about the partnership to get a feel for why we’re both so excited about this integration. And if you’re interested in signing up, please just head here. We’d love to talk with you.