notjoemartinez
Joined 3 years ago
Karma
235
Submissions
17
Member since
Feb 17
https://notjoemartinez.com/
View on Hacker NewsRecent submissions
Comment · 1 year ago
Incident metadata and transcripts are stored in a PostgreSQL db indefinitely. We've logged over 250k incidents since January. Planning on combining the incident data with other sources for historical analysis, search and such.
Comment · 2 years ago
If you email me the police department I you're curious about I can see if I can add it to the supported departments.
Comment · 2 years ago
> are you doing this real time or in a batch mode/daily scrape?
I'm transcribing the previous day starting 1AM every day, which is about as much as my old MacBook I have can handle. I'm in the process of applying for the Broadcastify Calls API which should give me access to real time feeds but it will be a challenge to get the compute needed to handle real time transcriptions.
> personally it would be useful to maybe subscribe to key words and get notifications for specific cities
This is a feature I have planned. It will come with a major disclaimer about whisper transcript hallucinations.
Edit: spelling
Comment · 2 years ago
Location: San Antonio, TX
Remote: Yes
Willing to Relocate: Yes
Technologies: Vue.js, Flask, Node.js, Express.js, PostgreSQL, SQLite, ChromaDB, Docker, Nginx, Windows Presentation Foundation // Infrastructure: AWS (EC2, Cloudfront, S3, Lambda), and Cloudflare (Workers, Pages, R2, KV) // Libraries: OpenCV, scikit-learn, LangChain, TensorFlow, Pandas, Matplotlib, and ChartJS // Languages: Python, JavaScript, C/C++, Bash, Java, C#, HTML, CSS.
Résumé/CV: https://notjoemartinez.com/about/resume.pdf
Email: [email protected]
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I am a software engineer with over 5 years of experience in full-stack development, a background in embedded systems, computer vision, and data visualization. I am currently seeking internship or full-time employment opportunities.
GitHub: https://github.com/NotJoeMartinez
Website: https://notjoemartinez.com
Comment · 2 years ago
I've been trying to solve a problem with implementing semantic search on my YouTube search engine yt-fts (https://github.com/NotJoeMartinez/yt-fts). I've managed to substantially speed up search results by storing subtitle embeddings in Chroma. But a bigger problem has been with how to properly segment the text in a way that accounts for the duration and context of word embeddings while returning precise time stamps. This a blog post exploring what I've tried so far.
Comment · 3 years ago
Thank you! I was able to integrate this into the project[1]. I'm also looking into using your openai-to-sqlite[2] library for semantic search.
[1]https://github.com/NotJoeMartinez/yt-fts/pull/25 [2]https://github.com/simonw/openai-to-sqlite
Comment · 3 years ago
> yt-fts search "love" --channel "Lex Fridman" | grep "love" | wc -l
> 7060