David J. Atkinson

@luftruessel @selfhosted I put in Lutron fan switches. Pricy, but work great and integrate easily with #homeassistant via Zigbee.

https://www.amazon.com/dp/B07N1GXM38?ref%5C_=ppx%5C_hzsearch%5C_conn%5C_dt%5C_b%5C_fed%5C_asin%5C_title%5C_1

@DarrinBrunner That might have something to do with your TV’s standby status and settings. For example, “Wake-on-LAN” is not always available, nor are some network interfaces, including BT.

@festus @selfhosted Excellent examples. What the tag [AI] conveys is not what you really need to know, which is the quality of the code (component/unit), unit testing, and so forth. I assume there is some acceptance testing done at the project level. The human who submits the code must understand that flaws in their code is their responsibility, just as those who contribute/maintain the project are responsible at the system level. It is both an objective and reputational process. Does it really matter what tools are used if the work product passes the test, verification and validation criteria? Sloppy code is not unique to AI tools.

@irmadlad This is such a great idea. I sometimes tell my rack, “you are my everything” and I give it whatever it wants. I’m about to reposition some of the equipment. That is plenty intimate enough to play Barry White.

@Zeoic You are both correct. Chess was chosen as an early problem domain for work on first-order logic-based programming. That certainly was considered AI. People really interested in chess later abandoned logic programming in favor of brute-force, highly parallel special purpose hardware. That was not AI.

“Expert systems” (I hate that term) are application area of “Pattern-Directed Inference Systems” (PDIS). Rule-based systems are just one type of PDIS. For example, “Constraint Satisfaction” is another powerful AI technique often used in resource optimization and scheduling systems.