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Public AI explainer video

Browsing से Recommendation तक

You're on your phone, searching an e-commerce app for black shoes. You scroll through options, tap one you like, and check its photos, price, and...

Prompt

Source idea used to generate this video.

मान लीजिए आप एक E-Commerce app खोलते हैं। आप सबसे पहले search करते हैं— “Black Shoes.” आप कुछ shoes देखते हैं। एक shoe आपको पसंद आता है। आप उस product पर click करते हैं। फिर उसकी तस्वीरें देखते हैं। Price देखते हैं। Reviews पढ़ते हैं। लेकिन आप order नहीं करते। आप app बंद कर देते हैं। आपको लगता है— “बस, बात खत्म।” लेकिन... असल में यहीं से algorithm का काम शुरू होता है। आपकी shopping activity से कई तरह के signals मिल सकते हैं। जैसे— आपने क्या search किया? किस product को देखा? किस product पर ज्यादा समय बिताया? किस category में interest दिखाया? क्या आपने कोई product cart में डाला? क्या आपने कोई product खरीदा? इन signals को system analyse कर सकता है। अब algorithm के सामने एक सवाल होता है— “इस customer को अगली बार क्या दिखाया जाए?” और यहीं से recommendation शुरू होती है।

Narration

Narration used to create this video.

Video narration

You're on your phone, searching an e-commerce app for black shoes. You scroll through options, tap one you like, and check its photos, price, and reviews. It seems promising-but you don't order. You close the app. You might think the shopping session ended there. It didn't. That activity can become signals: clues the system uses to decide what to show you next. Your search, the product you clicked, how long you stayed, the category you explored, whether you added something to your cart, and even whether you bought anything can be considered. The algorithm, the app's decision system, analyses these signals and asks: what should this customer see next? That is where a recommendation begins. It isn't a guaranteed product; it's a possible suggestion shaped by your activity. So when you open the app again, what appears may connect to those black shoes you explored, though you never ordered.

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