| "Tell me more about your cousins," Rorschach sent. "Our cousins lie about the family tree," Sascha replied, "with nieces and nephews and Neandertals. We do not like annoying cousins." "We'd like to know about this tree." Sascha muted the channel and gave us a look that said Could it be any more obvious? "It couldn't have parsed that. There were three linguistic ambiguities in there. It just ignored them." "Well, it asked for clarification," Bates pointed out. "It asked a follow-up question. Different thing entirely." [....] "Sascha," Bates breathed. "Are you crazy?" "So what if I am? Doesn't matter to that thing. It doesn't have a clue what I'm saying." "What?" "It doesn't even have a clue what it's saying back," she added. "Wait a minute. You said—Susan said they weren't parrots. They knew the rules." And there Susan was, melting to the fore: "I did, and they do. But pattern-matching doesn't equal comprehension."
Bates shook her head. "You're saying whatever we're talking to—it's not even intelligent?" "Oh, it could be intelligent, certainly. But we're not talking to it in any meaningful sense." — Peter Watts, Blindsight https://rifters.com/real/Blindsight.htm |
This is an enormously updated Eliza. Its usefulness is predicated upon its training corpus but because our corpus ingestion sizes are so large today it becomes a qualitatively different experience when searching on information that has already been generated.
However, synthesizing or inferring new conclusions from existing information still is our leg work to perform.
I found that StackOverflow type questions work quite well. Breaking down research paper text filled with lingo I'm not familiar with works well. Threading James Burke-Connections-like insight comprehensions among information in front of me though, is still on me.