fix image, changed author and minor formatting fixes

This commit is contained in:
Manas Chopra
2026-02-04 15:27:45 +05:30
parent 369c01dd4d
commit bb259602d9
2 changed files with 12 additions and 13 deletions
@@ -2,11 +2,11 @@
title: "Sketch & Search: Google Deepmind x Qdrant x Freepik Hackathon Winners"
draft: false
slug: sketch-n-search-winners
short_description: "Discover the winners of Qdrant’s Sketch & Search Hackathon in collaboration with Google Deepmind and Freepik, where developers built innovative vector search applications beyond chatbots — from robotics to gaming, e-commerce, and more."
preview_image: blog/sketch-n-search-2025/sketch-n-search-hero.png
social_preview_image: blog/sketch-n-search-2025/sketch-n-search-hero.png
short_description: "Discover the winners of Qdrant’s Sketch & Search Hackathon in collaboration with Google Deepmind and Freepik, where developers built innovative vector search applications beyond chatbots - from robotics to gaming, e-commerce, and more."
preview_image: blog/sketch-n-search-2025/sketch.png
social_preview_image: blog/sketch-n-search-2025/sketch.png
date: 2026-02-03
author: Qdrant
author: Manas Chopra
featured: true
tags:
- news
@@ -63,8 +63,8 @@ Repo: [Prometheus](https://github.com/resilienthike/Prometheus)
allowfullscreen>
</iframe>
**What it is:** "Roast My Snack transforms snack photos into 4-panel comics where Dr. Hawley — a Gen-Z molar with Adult Swim energy — roasts your snack's ""aesthetic threat level"" to your smile. The insight: Telling teens ""sugar causes cavities"" doesn't work. But ""that snack is gonna turn your smile yellow""? That lands.
We use vanity as a force for good. Built with Gemini Vision, Qdrant semantic search, and clinic-validated dental science from Poppy Kids Pediatric Dentistry. Age-adaptive roasts (Spicy for tweens, Savage for teens), transparent risk scoring, and Instagram-ready exports. Dental education kids actually want to share."
**What it is:** Roast My Snack transforms snack photos into 4-panel comics where Dr. Hawley - a Gen-Z molar with Adult Swim energy - roasts your snack's "aesthetic threat level" to your smile. The insight: Telling teens "sugar causes cavities" doesn't work. But "that snack is gonna turn your smile yellow"? That lands.
We use vanity as a force for good. Built with Gemini Vision, Qdrant semantic search, and clinic-validated dental science from Poppy Kids Pediatric Dentistry. Age-adaptive roasts (Spicy for tweens, Savage for teens), transparent risk scoring, and Instagram-ready exports. Dental education kids actually want to share.
**Stack:** Gemini/Flash, Nano Banana, Qdrant, Freepik
@@ -97,13 +97,12 @@ We use vanity as a force for good. Built with Gemini Vision, Qdrant semantic sea
## Why These Projects Matter
These projects show what happens when developers apply vector retrieval to creative, scientific, and real-world workflows:
- Molecular structures transformed into cinematic, reusable scientific storytelling.
- Educational experiences that use humor, memory, and personalization to change behavior.
- Image-to-design pipelines that turn a single photo into production-ready plans.
- Creative systems that learn what works and build long-term visual memory.
- Search-driven reuse of styles, prompts, and assets across domains.
- Practical applications where embeddings connect data, visuals, and human intent.
These winners stand out because they treat retrieval as an engineering primitive - not a bolt-on feature. Instead of generating “one-off” outputs, they build systems that can *remember*, *reuse*, and *stay grounded* as inputs and requirements change:
- Prometheus turns structured scientific data (PDB + Mol* renders) into a repeatable video pipeline, and uses similarity search to reuse proven camera/prompt templates across targets.
- Roast My Snack couples vision + semantic search with an explicit scoring layer (age-adaptive tone, transparent risk signals) so the output is controllable and consistent - not just funny.
- AutoScape anchors image-to-design generation in a curated plant/material catalog with retrieval, so designs come with real constraints (availability, pricing) and can be iterated, shared, and audited.
Across all three, Qdrant enables the “long-term memory” layer: storing embeddings of past assets, prompts, and outcomes so future runs can start from what already worked - faster iteration, better consistency, and less prompt thrash.
As with any hackathon, there were tons of amazing submissions, and we wish we could showcase them all, but we hope this sample showcases the strong power of the Qdrant Community when tasked with new challenges and creative approaches.
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