I've watched enough algorithmic trading bots blow up to treat any AI agent touching real money with extra scrutiny.
Trading agents are one of the highest-stakes applications I can think of for verifiable AI. Get the verification wrong here and the cost isn't a bad chatbot response. It's real money moving on a flawed decision.
BitQuant uses OpenGradient's framework to build AI agents that operate in financial markets. The pitch is that verifiable inference gives these agents an audit trail that black box trading bots never had.
That solves one problem. It doesn't solve the problem of whether the underlying strategy is actually sound. A verified bad trading model still loses money, just with cryptographic proof attached to the loss.
Verification builds accountability. It doesn't build alpha.
Those are different problems, and only one of them has anything to do with the infrastructure underneath.
#opg $OPG @OpenGradient
Trading agents are one of the highest-stakes applications I can think of for verifiable AI. Get the verification wrong here and the cost isn't a bad chatbot response. It's real money moving on a flawed decision.
BitQuant uses OpenGradient's framework to build AI agents that operate in financial markets. The pitch is that verifiable inference gives these agents an audit trail that black box trading bots never had.
That solves one problem. It doesn't solve the problem of whether the underlying strategy is actually sound. A verified bad trading model still loses money, just with cryptographic proof attached to the loss.
Verification builds accountability. It doesn't build alpha.
Those are different problems, and only one of them has anything to do with the infrastructure underneath.
#opg $OPG @OpenGradient