[PODCAST] Democratizing Unstructured Data at Scale

Machine learning applications require massive datasets, but it can be challenging to build and store large amounts of unstructured data.

Utilizing AI Graviti Podcast

With the development of artificial intelligence, we need massive datasets to process machine learning. However, the acquisition, storage and processing of a large amount of unstructured data pose great challenges for them. In this blog, Edward will share about democratizing unstructured data and introduce the open datasets community of Graviti.

As we know that massive datasets are required for machine learning applications, but building and storing large amounts of unstructured data can be a challenge. Today Edward Cui will talk with Frederic Van Haren and Stephen Foskett in this blog about his open repository for unstructured data. Coming from Uber’s self-driving organization, Cui realized the value of data and the challenge of storing massive amounts of unstructured data in his work, so he created the Graviti platform and made it available for free to open datasets. These datasets available in our dataset platform enable the development of a variety of applications, from agriculture and environmental science to gaming and robotics. In addition to addressing data sharing and quality challenges, we are working with the Linux Foundation on the OpenBytes project.

Click here to listen to the full podcast

Three Questions

  1. Frederic: Are there any jobs that will be completely eliminated by AI in the next five years?
  2. Stephen: When will we see a full self-driving car that can drive anywhere, any time?
  3. Tom Hollingsworth, Gestalt IT: Can AI ever recognize that it’s biased and learn how to overcome it?

Guests and Hosts

Date: 11/30/2021 Tags: @graviti_ai, @FredericVHaren, @SFoskett

Write at the end

In this podcast, Edward systematically explains his recent ideas for Graviti as the next-generation data platform. Not only did this give everyone a better understanding of Graviti's data platform in relation to unstructured data, but it also gave people a deeper understanding of unstructured data. The purpose is to better help people stand on the shoulders of giants, continuous innovation.

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