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ChatGPT, Microsoft Bing, and Google Bard – AI tools that are widely used today – have radically increased productivity and caused significant disruptions in various industries. As useful as these tools may be, they come with four major drawbacks:
(01)
Today’s AI tools often hallucinate, marking their task, but confidently providing the wrong answers to questions.
(02)
Without any verifiable provenance of the underlying data, answers are difficult to trust.
(03)
Training Gen AI models can cause legal issues, concerns over intellectual property rights, and privacy worries.
(04)
Using synthetic data instead of high-quality data for training can degrade models and perpetuate biases.
Turn your data into Knowledge Assets and create predictable AI agents to execute tasks using your data in just a few steps. Knowledge Assets on a Decentralized Knowledge Graph (DKG) provide AI agents with provenance and data ownership options, allowing flexibility in choosing AI models. Use ChatDKG to expand Knowledge Assets by launching a paranet, a community-owned unit on the DKG. Request network incentives through ChatDKG to fuel paranet growth and mine with each new relevant Knowledge Asset.
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