Today we hear what James Rebsco from Striveworks has to say about solving this problem for the federal government.
Rebesco suggests beginning with a deep understanding of the problem. Once you make sure the solution makes sense, then look at AI opportunities that can help solve the problem.
Applying the solution to real-world situations can be difficult. One may produce a model that behaves flawlessly in a clean, air-conditioned environment. In the real world, the situation is changing daily, commonly called a contested environment.
The defense community must deliver and manage production-grade machines that operate in austere, disconnected, and high-stakes environments.
Some in the academic community would like to put a stop to AI progress. The idea is to produce ethical and moral guidelines before proceeding. That certainly sounds nice when debating on a campus. Rebesco points out that we do not have the luxury of this approach. In today's geopolitical environment, we have adversaries who are very smart, capable, and well-resourced.
History has shown us the results of appeasement and delay.
He emphasizes the importance of embedding AI in real-world scenarios and ensuring models can adapt and learn. Robesco also discusses the concept of "situational awareness" in AI and the need for continuous testing and evaluation.
During the interview, he mentions StriveWorks' platform, Chariots, which aims to provide dependable, mission-critical AI solutions.
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