55 karma · joined November 5, 2019
https://getmesa.dev is mine
I'm using a YOLO-WORLD-XL object detection model. Lets me detect objects using text. This is the initial filter that scans for agents - once those are detected and outlined with bounding boxes the entire image and each cropped bounding box are then sent to chatgpt to confirm if the image looks legit. Once image passes those checks - I create image embeddings of each agent using CLIP and those are stored in a vector DB, and each agent is then compared to the DB and matched.
The matching system isn't perfect - but I think good enough to get the point across and can be easily tuned with more data! Happy to take suggestions here - I just spun this up over the weekend
some recent things I've made https://www.mindthenoise.com/ https://www.realtimefascism.com/
I don't have an anonymous contact method so just DM me here https://bsky.app/profile/realtimefascism.com
Would be cool to even have designated groups so you could filter by left wing, right wing, international, etc.
Gonna work on this after I optimize the codebase
yes - not sure what detail you want but I'll try to be thorough here.
Tech stack is React, Next JS, Radix UI lib, Tailwind, Firebase for database auth and cloud functions, Vercel for deployment, OpenAI for article classification, WorldNewsAPI for news.
Cloud Functions run at different intervals, I have one that runs every 30 minutes (recent news), 12 hours (weekly news), 84 hours (monthly news) and 168 hours (quarterly news). This is a big WIP
On a cloud function run it fetches articles from newsAPI, this search is done with a mix of keywords that determine if its related to the current administration, then gets filtered down to 'credible' sources (listed in a comment on this thread). The content of the articles that pass these filters get send to gpt-4o to be classified for relevance (is it an action of the administration / related) if it passes that >70%, the ai determines if it matches any of the 14 steps of facism, and will add a direct quote / impact / summary of why it matched that step, and finally will get added to DB and displayed on the site.
In terms of development - heavy use of Cursor IDE, and start with v0 by Vercel which is why I was able to get this up and running within ~3 days. Although the codebase looks disgusting rn
Allowed Sources Major Wire Services (1.0) Reuters, AP, AFP, Bloomberg Top US News (0.9) NYT, WaPo, WSJ, ProPublica
Conservative Media (0.7-0.8) Fox News, National Review, Washington Times, The Dispatch, Washington Examiner, RealClearPolitics, Reason
Progressive Media (0.7-0.8) Mother Jones, The Nation, Democracy Now!, New Republic, Jacobin, Truthout, Slate
International (0.8-0.9) BBC, Guardian, FT, Economist, DW, France24, Al Jazeera
Fact Checkers (0.9) FactCheck.org, PolitiFact
Major Networks (0.8) NPR, NBC, CBS, ABC, CNBC
Digital Media (0.7-0.8) Atlantic, Wired, Axios, USA Today, Time
as for the time-dependance / algorithm, good question .I'm still working on tweaking it, right now recency has a 30% weight. I just started this last thursday so im quite unsure how things will change / look on the site over time and what makes sense for a half life / decay of an article.
But yes love the idea : )
Spent the last few weekends building this idea out.
After moving into a new place and discovering my upstairs neighbors being louder than I expected, I figured it'd be useful to check a spot's noise levels before moving in.
Enter MindTheNoise—just drop any address, share the noise levels, what’s causing it, and any other helpful info.
Let me know what you think
- Ryan