Every local pet shelter around me charges a minimum average of $425 to adopt a dog, but I also see dog adoption fees as high as $750. This includes the adoption fee to adopt either a puppy or an adult dog, regardless of breed. The cost to adopt a puppy in Lancaster County, PA from the Amish is usually between $350-600, even for more desirable breeds. Getting a puppy from the Amish is also a lot easier, as no paperwork is required, and you don’t have to work around “operating business hours”. Many shelters require that adopters own a backyard or live in a mortgaged property (to avoid issues with landlords); this cuts out a lot of people who would otherwise be great adopters.
Shelters and rescues operate under the guise of rescuing animals from neglect or abandonment but they charge the same, or MORE for dogs that could easily be obtained through backyard breeders or puppy mills. It’s understandable that rescues/shelters would want to ensure that adopters can afford to care for their animals, but it also puts a hinderance on a lot of people who could be great pet parents, and also discourages people who may otherwise just look to backyard breeders or puppy mills instead.
r/LearnFromOthers
Most people assume AI gets “smarter” the longer you talk to it.
In reality, the opposite often happens.
As conversations become longer, the model has to process more and more context at once. That creates a strange effect where earlier details start losing weight while newer information dominates the response.
Over time, the conversation can slowly drift. The model may begin contradicting earlier points, forgetting constraints, or becoming less precise.
What makes this interesting is that the system does not actually “remember” things the way humans do. It continuously rebuilds the response from the available context window.
That means consistency becomes harder as the amount of information grows.
A lot of people interpret this as the AI getting tired or confused, but it is really a limitation of how current language models handle context and attention across long sequences.
Most people assume AI is reasoning when it responds.
It is not.
AI does not form thoughts or opinions. It predicts the next most likely word based on patterns in data. There is no understanding behind it, only probability.
That is also why it can sound confident even when it is wrong.
Once you understand this, you stop treating it like an authority and start using it as a tool for:
generating drafts
structuring ideas
exploring options faster
The shift is subtle, but it completely changes how useful AI becomes.