3 ms·
Honestly, this feels as impressive as getting the correct answer to "Hey Siri, what's the weather like tomorrow?"... I too would do it manually and begin by tr
by netsharc 1y ago
Honestly, this feels as impressive as getting the correct answer to "Hey Siri, what's the weather like tomorrow?"...
I too would do it manually and begin by trawling through emails from my brother's address. Obviously just the word "Monty" means the brother probably mentioned the name somewhere else (e.g. in real life) and then just used that reference key assuming OP knows what/whom it is referred to.
It's somewhat impressive that an AI can infer that "this email's subject is a male name, and the email discusses his reading preferences, it's possible the email sender is talking about his son." (I wonder if AI would "understand" (whatever "understanding" means for AIs) that the email sender is not talking about a cat named Monty, because cats can't read).
- skulk 1y agoIn 2015, Siri (and a number of other assistants) could tell you the weather tomorrow easily, but general question-answering was a pie-in-the-sky research dream. Tons of labs were working on this problem using all kinds of approaches. These mostly fell over when you asked a different kind of question, like one with a structure that just wasn't in the training set. The most impressive ones seemingly cherry-picked their results pretty aggressively.
- what-the-grump 1y agoI mean… we’ve data mined and extracted, and summarized, etc. etc. what’s impressive to me we can do this quickly. Take each chunk extract key phrase, summarize, now for each chunk, or vector search, is the basis of every rag chatbot built in the last 2-3 years.