Academic research

Our latest research addresses the Buyer's Inspection Paradox.

The Buyer's Inspection Paradox is a fundamental paradox in information economics. This paradox arises from the need for buyers to access and inspect information to determine its value, while sellers need to limit access to prevent expropriation. This paradox is a result of information asymmetry, a major cause of market failure.

To resolve this, we use automated decision functions (i.e., AI agents) to inspect and purchase information, while ensuring the information remains secure and cannot be expropriated. These decision functions are implemented using language models and are evaluated in that academic work. For an agent to be said to perform well, it must be cost-effective in acquiring useful information and capable of strategically searching the marketplace.

Our work is a step towards resolving information asymmetry by addressing the buyers’ inspection paradox. This research is crucial in designing mechanisms for information markets, considering that information is often expensive to produce but cheap to reproduce. Our goal is to create a more efficient market for information, contributing to a future where everyone can buy and sell information at its true value.

We have been doing fundamental and applied deep learning research for nearly a decade.

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