This conversation is closed. Start a new conversation
or join one »
We should create adaptive systems to support humanity in it's goals.
What if, we created a server/os/program that could create virtual machines on it's own. The administrator first creates a virtual machine template with a purpose (mail server, apache server, etc.) We then have a team of developers take a systems administrator wiki and start automating everything by writing a program that can do it. So the server would be adaptive, it would act upon input much like a human. The server creates the virtual server, the virtual server uses programs to automate tasks. If we focused on this we could probably create an endless loop, slightly scary because I think that was in the AI movie. Just a thought...
Showing single comment thread. View the full conversation.
Showing single comment thread. View the full conversation.














Koen Wesselman
Timothy Shreffler
Koen Wesselman
I'm a paid freelance programmer next to my Information Science. I'm not infallible though.
I think it's possible to create systems that learn from situations automatically by their results and can predict the outcome of certain situations based on results from previous (similar) situations. Of course you could channel any problems the system hasn't occured before on to experts so they can solve them and the system can learn from it, but then it wouldn't be a self-sufficient-system but only decrease the need for experts. You can read more about these kind of systems here or Google for the term "Expert Systems":
https://en.wikipedia.org/wiki/Expert_system
To answer your second question: Yes, the result would always be the same. Saying this I am assuming that the input the system receives (from the outside, like the situation, and from the inside, as in the database) would be precisely the same as the system uses math to calculate the solution: A calculation always has the same result, untill you change a parameter.
Timothy Shreffler
Koen Wesselman
We program a system that calculates whether firefighters are allowed to enter a building. We give the system as input possibilities:
- The number of firefighters / victims
- The size of the fire
- The complexity of the building
Then, after implementing the system, a fire occurs:
- There's 3 firefighters and 2 people inside, unconscious
- It's a small fire
- The room with the people is easily accessible
But there is also a gas leak about to happen, as the pipe is of bad quality and likely to burst. (Theoretically, probably not likely in real life, but I dont know anything about gas pipe's..)
The system wouldn't be able to make a right decision because we can't give it all the information we need to. An expert would have to make a quick decision due to the time limit of this situation and the system needs updated.
Of course this is not very likely a thing to forget to build into the system but it's an example: We can never predict every possible attribute of a situation. Hence we will always need experts for when the system doesnt suffice and the system will never be self-sufficient. The risk of assuming creating a self-sufficient system is possible is that we will end up having no experts when the system can't calculate the right answer. That's why we should always remember we need to be able to replace systems like these with humans may the need occur.
Timothy Shreffler