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IBM Watson teams up with Anaconda to simplify AI open- source adoption

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IBM Watson has announced a new collaboration with leading Python data science platform provider, Anaconda, Inc., to simplify the adoption of AI open-source technologies for executing data science projects. The partnership marks a milestone in helping to address the AI and data science skills gap that exists in many organisations today.

As data scientists today increasingly rely on open-source technologies to tap into a mine of AI skills and capabilities for business Ops projects, there was an unmet need to simplify enterprise adoption. Previously, the use of open-source technologies in enterprise was complicated both from a technical and legal perspective, with issues arising from co-location and testing in real-time with various teams in the organisation.

The new partnership, which will integrate Anaconda Team Edition repository with IBM Watson Studio on the IBM Cloud Pak for Data, aims to overcome these technical and operational challenges, as enterprises will be able to better govern and accelerate the deployment of AI open-sourced technologies across any cloud provider.

Furthermore, Anaconda is offering their 20 million users free access to a lite version of Watson Studio1; where they can manage data science projects on IBM’s enterprise-grade environment.

This combined solution, an automated AI lifecycle platform to streamline building and operationalising of AI, is expected to be available by 19th June 2020.

In a press release this week Peter Wang, CEO and Co-founder of Anaconda, explained: “Our aim at Anaconda is to help organizations unleash their full potential through data science, and we’re proud to work with IBM to give their customers the latest open-source data science packages in an enterprise-friendly way. Both our companies share a goal of making data science and machine learning more accessible, and this relationship is a further step in that direction.”

To find out more about the Anaconda Repository for IBM Cloud Pak for Data before it’s release, visit IBM Big Data Hub.

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