Artificial Intelligence: Mobile AI and ML Platform Fritz Raises $5 Million

March 25, 2020 | Artificial Intelligence, News
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Fritz AI lets you run artificial intelligence and machine learning models on your mobile.

Mobile AI and machine learning startup Fritz AI will use the $5 million it raised in its recent funding to expand and accelerate its product launch.  The round was led by Foundry Group. NextGen Venture Partners, Inner Loop Capital, Eniac Ventures, Uncork Capital, and Hack VC also participated in the funding. (VentureBeat)

Fritz: AI+ML – No coding required!

Fritz is looking to simplify and shorten the development of AI and machine learning models for customers. It offers off-the-shelf, deep learning models that are ready to deploy for applications such as object identification in videos. Clients have also used Fritz models to change hair color in real time, replace photo backgrounds, and create stickers for messaging apps.

Interestingly, these models can even run on mobile platforms such as Android and ioS. They also don’t need an internet connection. They range from compact models to suit size and bandwidth to fast models built with an eye on processing speed.

For instance, an app was created to help African smallholder farmers diagnose crop disease in the field – without an internet connection. The solution – custom-trained object detection models for Cassava, Potato, and Fall armyworm.

Fritz end to end

Fritz also offers an end-to-end platform (pictured above) for managing the machine-learning workflow. So engineers can simply in plugin pre-trained models and get their AI/ML project going without having to code.

“Our integrated platform empowers your dev team to tackle each challenge in the mobile ML lifecycle: generate and collect labeled datasets, train optimized models without code, deploy and manage on any mobile platforms, and improve models and app UX based on real-world data,” says Fritz on its website.

Related Story:     Artificial Intelligence: An AI Bot Will Design the Next-Gen AI Chips

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