I don’t know why you are mentioning Starship when I made no mention of that. Starship HLS is also a dumb idea, but that’s beside the point.

SLS is horribly expensive for what it provides.

The Defense Production Act could be used to meet these ends. SpaceX is a defense contractor and exists at the privilege of the US Government for the US Government.

Coming from several people who work with SpaceX, there is a dedicated group of people that exist to distract Elon from all vital SpaceX functions.

SLS is on track to be more expensive when adjusted for inflation per moon mission than the Apollo program. It is wildly too expensive, and should be cancelled.

This coupled with the fact that the rocket is incapable of sending a manned capsule to low earth orbit which is the the lunar gateway is planned to a Rectilinear Halo Orbit instead.

Those working in the space industry know that SpaceX’s success is not because of Elon but instead Gwynne Shotwell. She is the President and CEO of SpaceX and responsible for all things SpaceX. The best outcome after the election is to remove Elon from the board and revoke his ownership of what is effectively a defense company for political interference in this election. Employees at SpaceX would be happy, the government would be happy, and the American people would be happy.

The technical definition of AI in academic settings is any system that can perform a task with relatively decent performance and do so on its own.

The field of AI is absolutely massive and includes super basic algorithms like Dijsktra’s Algorithm for finding the shortest path in a graph or network, even though a 100% optimal solution is NP-Complete, and does not yet have a solution that is solveable in polynomial time. Instead, AI algorithms use programmed heuristics to approximate optimal solutions, but it’s entirely possible that the path generated is in fact not optimal, which is why your GPS doesn’t always give you the guaranteed shortest path.

To help distinguish fields of research, we use extra qualifiers to narrow focus such as “classical AI” and “symbolic AI”. Even “Machine Learning” is too ambiguous, as it was originally a statistical process to finds trends in data or “statistical AI”. Ever used excel to find a line of best fit for a graph? That’s “machine learning”.

Albeit, “statistical AI” does accurately encompass all the AI systems people commonly think about like “neural AI” and “generative AI”. But without getting into more specific qualifiers, “Deep Learning” and “Transformers” are probably the best way to narrow down what most people think of when they here AI today.