This is really cool! I always believed one valuable use case for AI is to take unstructured data and structure it.

I am building ThetaEdge (https://thetaedge.ai) which is in Beta now. We built a similar feature but specific to investing and markets. You get notified when certain market things you care about happen like 'Alert me when nvidia releases a new product' or 'tell me when a 20 delta call for Apple is more than $1'.

The challenge of building something like this is consistency and accuracy which is important in finance.

Awesome to see a clean focused product like YesNotice with a very clear utility.

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IncreasePosts 4 hours ago | parent [-]

I agree about the importance of that use case, but how do you confirm that the AI doesn't modify the data in some unwarranted manner during the process?

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mempko 4 hours ago | parent [-]

Great question! Don't use AI to process the data, especially when a computer can do the work :-). AI is good at taking unstructured data and structuring it. Computers are great at computing.

Here is an example of Google's AI failing

https://www.google.com/search?q=is+2026+next+year

Google screenshot: https://imgur.com/a/FOT4aDF

ChatGPT also fails: https://imgur.com/a/mb3rRgZ

and here is the ThetaEdge result: https://imgur.com/a/ZAZZgiR

	▲	IncreasePosts an hour ago \| parent [-]
		Sure - I guess what I was asking is how to make sure everything is okay in the unstructured -> structured conversion. "My name is John and I'm 40 years old" -> {name:"John", age:40} How can you gain confidence that the AI doesn't spit out {name:"John", age:41} The only thing I do currently is have a massive test suite to gain some statistical confidence it works, but I worry about situations like a person having a rare unicode character in their name (not to even speak of people intentionally trying to trick the system)