Alternatives
Products that do what Search San Francisco using natural language does
Hey HN! We're Alex and Szymon from Bluesight (https://bluesight.ai/), where we're developing a foundation model for satellite data. We've created a demo to showcase the current capabilities of state-of-the-art models and identify areas for improvement. Our demo allows you to search for objects in San Francisco using natural language. You can look for things like Tesla cars, dry patches, boats, and more. Key features: - Search using text or by selecting an object from the image as a source ("aim" icon) - Toggle between object search (default) and tile search ("big" toggle,…
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We’ve trained a generative AI model to browse the web and answer questions/retrieve code snippets directly. Unlike ChatGPT, it has access to primary sources and is able to cite them when you hover over an answer (click on the text to go to the source being cited). We also show regular Bing results side-by-side with our AI answer. The model is an 11-billion parameter T5-derivative that has been fine-tuned on feedback given on hundreds of thousands of searches done (anonymously) on our platform. Giving the model web access lessens its burden to need to store a snapshot of human knowledge…
2022 · beta.sayhello.so
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Hi HN, I am Jiayuan, and I'm here to introduce a tool we've been building over the past few months: Devv (https://devv.ai). In simple terms, it is an AI-powered search engine specifically designed for developers. Now, you might ask, with so many AI search engines already available—Perplexity, You.com, Phind, and several open-source projects—why do we need another one? We all know that Generative Search Engines are built on RAG (Retrieval-Augmented Generation)[1] combined with Large Language Models (LLMs). Most of the products mentioned above use indexes from general search engines…
2024 · devv.ai
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Hi there! When Supabase announced their recent hackathon, I thought it was a good time to build something to learn more about so many of the new AI models and tech out there. From the different techniques of embedding documents to the future RAG. With the rise of short form content with TikTok and Youtube. A lot more knowledge is in videos than ever before. Finding specific answers within millions of videos can be difficult for any one person to go through. So the question is if there is Google that indexes text on website making it easier to find based on the context of on your question,…
2023 · avse.vercel.app
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I built a browser-based tool for detecting objects in satellite imagery using vision-language models (VLMs). You draw a polygon on the map and enter a text prompt such as "swimming pools", "oil tanks", or "buses". The system scans the selected area tile-by-tile and returns detections projected back onto the map as GeoJSON. Pipeline: select area and zoom level, split the region into mercantile tiles, run each tile with the prompt through a VLM, convert predicted bounding boxes to geographic coordinates (WGS84), and render the results back on the map. It works reasonably well for distinct…
Mar 2026 · useful-ai-tools.com
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Hi HN, I built an open-source AI agent that has already indexed and can search the entire Epstein files, roughly 100M words of publicly released documents. The goal was simple: make a large, messy corpus of PDFs and text files immediately searchable in a precise way, without relying on keyword search or bloated prompts. What it does: - The full dataset is already indexed - You can ask natural language questions - Answers are grounded and include direct references to source documents - Supports both exact text lookup and semantic search Discussion around these files is often fragmented. This…
Jan 2026 · epstein.trynia.ai
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Simulate anything on a map from a text prompt -- and conduct risk analysis against LiveUA map's global realtime data points from social media and news sources. I trained a GPT-2-size model on historical incident data used to predict things that will go wrong. As historian Benjamin Breen mentions, the leading language models are good historians, so the application will simulate historical events pretty well also. I include a Multi-Agent RL Urban Mobility model in progress displayed on the map as small white cubes representing traffic and pedestrians. Around SF, it uses real census data and…
2025 · mused.com
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We're a small team of 3 engineers, and wanted to make a better way to look for for properties online. Traditional portals (esp. outside of US) are just a bit rubbish for doing anything other than basic searching. So we've: - Created a crawler that reads through estate agents websites to find homes for sale - Parses that through a series of LLMs and other models to understand each home in depth (e.g. floor type, location, total sqft) - Parses every photo through an embeddings vector space so that people can search for whatever they want. Check it out: https://jitty.com Currently…
2025
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We built a search engine interface on top of OpenAI GPT 3.5 and Microsoft Bing that summarizes and cites top search results in response to natural language questions. By using search results, the AI is able to reference recent news and provide citations for specific facts. Our interface offers concise answers, without having to click through links, scroll past irrelevant content, or read ads. No login is required; no personal data is collected. We believe in the power of combining the intuitive UI of web search with the intelligence of large language models. The search engine does indexing…
2022 · perplexity.ai
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2024 · tryhelix.ai
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Hey, just a work related project I made, which could be open sourced :D If you're looking for an example on how to use/fine-tune yolov8, I feel like taking a look at this repo and reading the README could help you get up to speed (also linked some nice refs)! This is actually a full rewrite of a proprietary project I made (and documented on my site) like a year ago, will do some finishing touches (write blog post about it, mark the old version deprecated, record a tutorial on how to set it up on an Ubuntu server, etc, etc) in the following month, but felt like sharing it now, cuz I…
2023 · github.com
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Yachay is an open-source community that works with the most accurate text-to-geolocation models on the market right now
2022 · github.com
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Hi HN, I am Anubhav from Ramanlabs. We have been working on a native gui application to allow users to search any video data( mp4, mkv) or video streams (http/rtsp) using computer vision. Application is supposed to work like a video player which displays decoded frames and recognizes objects concurrently, making it an interactive experience. It works in super real-time and only expects a quad-core CPU with AVX2 instructions at minimum. Application is free to download (without any signup/account). We are only supporting WINDOWS for now [0]. Even though this is a binary application,…
2022 · ramanlabs.in
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I built an MCP server that gives any local LLM real Google search and now vision capabilities - no API keys needed. The latest feature: google_lens_detect uses OpenCV to find objects in an image, crops each one, and sends them to Google Lens for identification. GPT-OSS-120B, a text-only model with zero vision support, correctly identified an NVIDIA DGX Spark and a SanDisk USB drive from a desk photo. Also includes Google Search, News, Shopping, Scholar, Maps, Finance, Weather, Flights, Hotels, Translate, Images, Trends, and more. 17 tools total. Two commands: pip install…
Feb 2026
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I recently developed a JavaScript library that determines what San Francisco neighborhoods and/or districts someone is in. The application is served from Google App Engine so if no one is using the application the server instances are shut down and your first couple queries might be slow. But after a couple instances are spun up it performs quite well. The example application is just an example so it's not very sophisticated or pretty to look at. For the example to work properly it must run on a device that supports the HTML5 geo location API such as an iPhone. If you get chance take a…
2013
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