TheMiracleMartianHideout

There are two religons in the world of developing a capability of artificial intelligence in a component, 1st which talks about developing the capability with the resource parameters of the system where the capability would be used and the 2nd one which talks about developing the capability of using resources which are primarily available on the web, the intent of both schools of thought being the same, end up with a decisioning system which does the same with high probability of it being accurate. Let's talk about the 2nd school of thought first, build with networked component on a web, this gives a lot of advantages - better compute power, experience over the web being transmitted leading to more accurate decisioning. This model definitely serves the purpose of quickly developing a system which will provide a machine learning approach which is much faster. Now let's consider the 1st school of thought, having an AI chip inbuilt within the environment where it's invoke...

As developers, programmers & code enthusiasts (awkward starting but bear with me for a little while..) we are always instructed to code with an environment close to the one in production. Our risk of not making a code run successfully in production surpasses the little nuances in shortcuts we take to make it run quickly in lower environments. Alright enough of code talk, we should be discussing space & mars so the same theory applies to what space gives us as an environment which marks the beginning of something either working or not working completely - the difference is - the risk here is far greater than than the minuscule issues which come to the code problem on earth. So what does that mean? Any entity being programmed to be used in space should be capable at minimum of 2 governing factors to perform without surprises... Autonomous decisioning. Scaled learning. The best way to do that is to have a component of decisioning being driven by a human interface but ...