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Lol, ignorance is blissIf you research what's in the sausage you're gonna stop eating it.
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Lol, ignorance is blissIf you research what's in the sausage you're gonna stop eating it.
Dolphins? Just kidding. Hey, Nord Stream ll didn't blow itself upThe Terminator Salvation movie had underwater robots - "hydrobots".
We already have underwater attack drones (Ukraine) and I think the US military has them too. I could be mistaken, but I think WWII had remote control and autonomous underwater drones (at least, torpedoes - I know we have them now). I think the US military has underwater drones that can lay inactive on the ocean floor and then activate on enemy detection.
The Terminator Salvation movie had underwater robots - "hydrobots".
We already have underwater attack drones (Ukraine) and I think the US military has them too. I could be mistaken, but I think WWII had remote control and autonomous underwater drones (at least, torpedoes - I know we have them now). I think the US military has underwater drones that can lay inactive on the ocean floor and then activate on enemy detection.
A deeper dive:AFAIK, an LLM, which is what is generally used as a tool for search results (e.g., when you ask a question in a browser search bar, or in an AI window) you are dealing with an LLM which is basically a word matching app that searches its model for matches. That model is basically constructed by scanning the internet - including sites like NWFA. Such an "AI" doesn't really know anything, it just constructs text from its model.
There are other AI apps/models/etc., that do other things (e.g., make pictures/videos, have a conversation, etc.), but what you get when you do use an internet search engine (e.g. Google) is an LLM.
When you ask a search engine "what is an LLM?" you get:
A large language model (LLM) is a type of artificial intelligence that can understand and generate human language by analyzing vast amounts of text data. LLMs are used for various tasks, such as answering questions, summarizing text, and translating languages.
I would not use the word "understand" in the same sense as humans understand language. It is more of a statistical match - not a cognitive match.
FWIW - one of my s/w dev gigs was working on a team that developed an application called "SchemaLogic", which was a ontology/taxonomy database (I liked to say it was metadata about metadata) which is closer to a basic knowledge base for understanding language than an LLM is.
It is used to categorize & classify word relationships to help build a knowledge base. E.G., it is a tool to relate words like "blue" to a color or a mood, or "blue jeans" or "blues music", not statistically, but contextually. It has "terms" and "vocabularies" in a semantic relationship, not a statistical one.