Hacker News: SiddanthEmani

New comment by SiddanthEmani in "Daily AI Times"

SiddanthEmani — Sun, 20 Jul 2025 20:01:01 +0000

Just launched "Daily AI Times" - 7 days in and it's already transforming how I consume AI research!

Instead of spending hours prompting ChatGPT/Claude for "latest AI developments," I built a fully automated pipeline that does the heavy lifting.

Manual AI Prompting vs Automated Pipeline:

Manual Way:

→ Limited by training cutoffs

→ Generic summaries

→ 30+ minutes of prompting

→ Miss breaking developments

Daily AI Times Way:

→ 42,000 articles processed in 7 days

→ 1,050 premium items via AI consensus

→ 115 live sources, 7 AI agents working 24/7

→ Zero manual effort, maximum signal

Meet the Complete AI Team:

Bulk Intelligence Squad:

• Quinn (Llama-3.1-8B) - Content Quality

• Riley (Gemma2-9B) - Relevance Scoring

• Casey (Llama3-8B) - Category Classification

Deep Intelligence Duo:

• Scout (Llama-4-Scout-17B) - Fact-Checking

• Sage (Llama-3.3-70B) - Bias Detection

Content Creation Team:

• Script Writer (Gemini-2.5-Pro) - Podcast Scripts

• Voice Duo - The Talented Jane and Joe (Gemini-2.5-Flash-TTS) - Multi-Speaker Audio

The 9-Step Pipeline:

1. Collection: 1,000 articles from 115 sources

2. Bulk Intelligence: Multi-dimensional scoring

3. Consensus: 70% agreement rule filters noise

4. Deep Analysis: Fact-checking + bias detection

5. Final Consensus: Weighted combination

6. Classification: Headlines, articles, research papers

7. API Generation: Frontend-ready endpoints

8. Audio: Auto-generated podcasts with dialogue

9. Deployment: GitHub Pages + global CDN

Results: 2.5% acceptance rate, 7.5-min cycles, 6x daily

Future Roadmap:

→ Enhanced audio formats (briefs, deep dives)

→ New categories (Healthcare AI, Climate Tech, Robotics)

→ Scale to 10K+ articles, 15+ agents, real-time processing

When 7 AI agents agree something is important - it probably is!

Live Demo: https://siddanthemani.github.io/daily-ai-times

GitHub: https://github.com/SiddanthEmani/daily-ai-times

How do you stay current with AI developments?

Show HN: Daily AI Times

SiddanthEmani — Sun, 20 Jul 2025 20:01:01 +0000

Article URL: https://siddanthemani.github.io/daily-ai-times/

Comments URL: https://news.ycombinator.com/item?id=44628790

Points: 3

# Comments: 1

New comment by SiddanthEmani in "Ask HN: Is anybody building an alternative transformer?"

SiddanthEmani — Fri, 14 Feb 2025 21:33:41 +0000

Titans has a new approach to longer and faster memory compared to transformers.

https://arxiv.org/html/2501.00663v1

New comment by SiddanthEmani in "Apple collaborates with Nvidia to research faster LLM performance"

SiddanthEmani — Wed, 18 Dec 2024 22:53:30 +0000

With competition on the rise, it’ll be a race to provide faster inference speeds for general queries

New comment by SiddanthEmani in "Sortledton: A Universal, Transactional Graph Data Structure [pdf]"

SiddanthEmani — Sun, 03 Nov 2024 03:24:43 +0000

A lot of the Sr. system architects I’ve talked to complained how time consuming/complex (lack of a better word) it is while managing both relational and graph databases. Every CRUD operation leads to more dusting/cleaning your latent factors/connections in your graph databases. There is ongoing research that the complexity arises due to the independent nature of your data across multiple databases, but the latent factors by definition are data-about-your-data. So the task is to make your latent factors dependent to their pertaining relational data, which enables easier house cleaning.

New comment by SiddanthEmani in "Drasi: Microsoft's open source data processing platform for event-driven systems"

SiddanthEmani — Sun, 20 Oct 2024 23:25:56 +0000

Cypher is so cool. I included a graph database in my RAG patient chatbot

https://github.com/SiddanthEmani/patient_chatbot

New comment by SiddanthEmani in "Patient Chatbot – An Intelligent Conversational Agent for Healthcare"

SiddanthEmani — Tue, 01 Oct 2024 06:01:41 +0000

The Patient Assistant Chatbot is designed to help patients manage their healthcare interactions by providing information on medical appointments, medications, and other health-related queries. Built with Django, Neo4j, WebSockets, and advanced AI models, it ensures secure and real-time communication between patients and their healthcare data.

Key Features:

Real-time Communication : Utilizes WebSockets for instant message exchange.

Secure Data Handling : Combines Django's security with Neo4j's graph database to manage sensitive information.

Intent Recognition : AI-driven classification to understand and respond to diverse queries.

Action Handling : Facilitates scheduling appointments and updating medication regimes.

Conversation Management : Maintains and summarizes conversation history for context-aware responses.

Technology Stack:

Backend : Django, Django Channels

Databases : PostgreSQL, Neo4j

AI & NLP : LangChain, Google Generative AI (Gemini)

Real-time Communication : WebSockets via Django Channels

Patient Chatbot – An Intelligent Conversational Agent for Healthcare

SiddanthEmani — Tue, 01 Oct 2024 06:01:41 +0000

Article URL: https://github.com/SiddanthEmani/patient_chatbot

Comments URL: https://news.ycombinator.com/item?id=41705031

Points: 3

# Comments: 1