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Upshot initially started as a crowd-sourced appraisal platform for infrequently traded assets like NFTs. They used a mechanism design called peer prediction to incentivize accurate valuations from humans. However, they found scalability and accuracy limitations with this approach. As a result, they shifted their focus to building AI infrastructure for pricing long-tail assets and creating efficient financial infrastructure. They developed proprietary AI models that leverage various data sources, including open market data, metadata, and social sentiment data, to generate real-time price estimates for assets. Upshot is now building a decentralized AI network that allows anyone with AI models to contribute and coordinate along shared economic objectives. They are aiming to create a collective intelligence where the network's output is better than any individual model. Users can access Upshot's price predictions through various tools, lending platforms, and perpetual platforms. They are also exploring tokenized asset appraisal and AI-powered loans. Upshot's model is designed to protect IP and ensure verifiability of inference. They are leveraging modulus labs' technology to provide ZK predictors that verify the output of models without revealing proprietary information. This approach allows for a range of specialized models to be utilized in different contexts, enabling more accurate and expressive AI applications in the decentralized space.