Problem Statement
According to surverys by 2027 there would be 440 million people seeking love through online platforms. Unfortunately the first filter is via chat which does not always represent real character, nature and personality of the person, which eventually results into lesser chances of getting into dates and hence taking it longer to find someone. This is a wide spread problem which is not openly spoken about.
what it does
creates replies which will reduce your chances of getting ghosted and increases your chances to meet someone you like in person or date
what all used
used appwrite , flutter, openai, fastapi
challenges we faced
current models other than chatgpt , its quite difficult to handle and remember context. Since ChatGPT api is not exposed by openai.
most proud about
Real life problem statement, helpful, easy and fun solution, solution which can also go viral
Learnings
limitations of ai in understanding humor which is relatable to context of conversation, understand common patterns and reading in between the lines, not understanding local sub pop culture traits, habits, human behaviours, limitations of ai in understanding natural delays in human replies according to human work profiles.
Example : When you initally start chatting to someone you like, initally that person might give you reply in antisipation, excitement and urge instantly, but you know when that delay to reply or ignore game starts.
whats next
regionalized and personalized messages, which would be using ocr from screenshot of the tinder or bumble profile page, so that we can get some details from photo and we can get some keywords from the profile bio via ocr
By personalised and regionalised messages , lets take an example, most popular option to go out on first date could be meeting for drinks in some city and could be meeting for coffee in some and could be not a very casual or easy thing to even meet in some conservative regions and asking out means quite different and serious compared to some other cities.
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