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@oortech@MaxLi_Columbia@oortchair@realkemabae With AI models becoming increasingly dependent on high quality training data, how does OORT plan to make its decentralized data supply competitive with centralized providers because quality and verification matter just as much as having a large contributor base?
@oortech@MaxLi_Columbia@oortchair@realkemabae OORT is pushing computation toward the edge for privacy, but AI workloads can be extremely demanding. How are you thinking about the trade-off between privacy, local compute limitations and the performance users expect from centralized AI?
@oortech@MaxLi_Columbia@oortchair@realkemabae OORT has grown DataHub to over 330K contributors across 136 countries, so how is @oortech making sure that growth translates into better and more useful AI datasets rather than simply more data?
@oortech@MaxLi_Columbia@oortchair@realkemabae As decentralized data storage continues to grow, how does OORT plan to balance privacy, security, scalability, and cost while competing with traditional centralized cloud providers?
@oortech@MaxLi_Columbia@oortchair@realkemabae What is OORTβs long-term vision for becoming a leading decentralized data cloud, and what are the biggest technical challenges the team must overcome to achieve that vision?
@oortech@MaxLi_Columbia@oortchair@realkemabae How does OORT ensure that user data remains private and secure across a decentralized network, especially when data is distributed across multiple independent nodes?
@oortech@MaxLi_Columbia@oortchair@realkemabae With AI and Web3 generating massive amounts of data, how is OORT preparing its infrastructure to handle the rapidly increasing demand for decentralized data storage and computing?