At Nuklai, they believe data should be accessible to everyone at all times, whether it's the data itself or the metadata. Their aim is to store data efficiently, transparently, and in a decentralised manner using Filecoin's decentralised data storage network.
Data is everything; typically, data is stored on major cloud providers like AWS, Google Cloud, or Alibaba Cloud. To make data accessible, Nuklai implemented three steps that pave the way to achieve this:
Define and decentralise the context of the data within the metadata. This is crucial to deeply understand the data, its source, and its content, which are necessary to create a comprehensive data ontology of the world;
Standardise data to make it more efficient and interoperable with the ultimate goal of accelerating innovation or even training AI models;
Once the data is defined and standardised, it is stored using Filecoin's data storage network and accessible through Nuklai at all times, while the data owner retains ownership.
Nuklai enhances data reliability by providing additional context enabling improved interoperability. Everyone can contribute by sharing and contextualizing datasets, accessible via app.nukl.ai.
Officials from Nuklai said they’re happy to collaborate with the Filecoin Foundation to bring Nuklai one step closer to building the world's ontology through an accessible and traceable storage and archiving solution.
Also commenting on this collaboration, representatives from Filecoin said they’re excited that Nuklai is taking advantage of Filecoin's unique ability to protect data and enhance AI. This collaboration demonstrates Filecoin is the backbone to the evolving AI and Web3 landscape.
Nuklai is a collaborative infrastructure provider for data ecosystems, integrating community-driven data analysis with data from successful modern businesses. Their platform connects data enthusiasts and institutional partners to harness untapped data and create new revenue streams.
The company aims to unify the fragmented data landscape by offering a user-friendly, streamlined approach to sharing, requesting, and evaluating data for valuable insights enhancing processes and fostering new business opportunities, augmenting next-generation large language models and AI.
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