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CodeKairo T1 DSA Rush: Registration Open
A 1v1 knockout tournament in data structures and algorithms, held on CodeKairo Battles.
Schedule: Friday, 2 October • Registration closes at 10:00 AM • Check-in opens at 7:00 PM. Only players who check in are placed in the bracket. • Matches begin at 8:00 PM
Format • 1v1 knockout, seeded by rating • 1 hour per match. The first Accepted solution wins. • 10 problems, revealed at the start • Limited to 20 players
Prizes • 1st place: Lifetime Premium access • 2nd place: 6 months of Premium access • 3rd place: 2 months of Premium access • A participation certificate for every player and a winner's certificate for the top 3
Register: https://battles.codekairo.com/t/t1-dsa-grind
Join the group for the guidelines, rules, tournament details, mock drills and updates: https://chat.whatsapp.com/FdKKAtsfJyYDD9Qlqdi4Fu?mode=gi_t
CodeKairo T1 DSA Rush: Registration Open
A 1v1 knockout tournament in data structures and algorithms, held on CodeKairo Battles.
Schedule: Friday, 2 October • Registration closes at 10:00 AM • Check-in opens at 7:00 PM. Only players who check in are placed in the bracket. • Matches begin at 8:00 PM
Format • 1v1 knockout, seeded by rating • 1 hour per match. The first Accepted solution wins. • 10 problems, revealed at the start • Limited to 20 players
Prizes • 1st place: Lifetime Premium access • 2nd place: 6 months of Premium access • 3rd place: 2 months of Premium access • A participation certificate for every player and a winner's certificate for the top 3
Register: https://battles.codekairo.com/t/t1-dsa-grind
Join the group for the guidelines, rules, tournament details, mock drills and updates: https://chat.whatsapp.com/FdKKAtsfJyYDD9Qlqdi4Fu?mode=gi_t
CodeKairo T1 DSA Rush: Registration Open
A 1v1 knockout tournament in data structures and algorithms, held on CodeKairo Battles.
Schedule: Friday, 2 October • Registration closes at 10:00 AM • Check-in opens at 7:00 PM. Only players who check in are placed in the bracket. • Matches begin at 8:00 PM
Format • 1v1 knockout, seeded by rating • 1 hour per match. The first Accepted solution wins. • 10 problems, revealed at the start • Limited to 20 players
Prizes • 1st place: Lifetime Premium access • 2nd place: 6 months of Premium access • 3rd place: 2 months of Premium access • A participation certificate for every player and a winner's certificate for the top 3
Register: https://battles.codekairo.com/t/t1-dsa-grind
Join the group for the guidelines, rules, tournament details, mock drills and updates: https://chat.whatsapp.com/FdKKAtsfJyYDD9Qlqdi4Fu?mode=gi_t
We are looking for an experienced AI/Backend Developer to build an internal AI knowledge platform integrating Local LLMs, Box, and multiple external AI services.
The goal is to provide 10–20 employees with a single internal interface where they can search and utilize company knowledge stored in Box, interact with local and external AI models, and generate answers and documents with clear source references.
Key requirements include:
- Local LLM deployment on Mac Studio (Ollama or similar)
- Box API integration and on-demand search across large-scale company data
- RAG, document retrieval, and reranking
- Integration with external AI APIs such as OpenAI/GPT, Gemini, Grok, etc.
- AI Router/Orchestrator for selecting or combining multiple models
- User authentication and permission-aware document access
- Conversation history, knowledge management, and audit logs
- API usage/cost tracking and security controls
- Backend/API architecture suitable for future expansion
We do not plan to download or embed the entire Box dataset. The preferred approach is to search Box on demand, retrieve only relevant documents, process/rerank them, and provide the necessary context to the selected LLM.
We would like to begin with a small PoC and expand to production after validating search accuracy, response quality, performance, security, and operating costs.
When applying, please briefly describe your experience with Local LLMs, RAG, Box or similar enterprise storage APIs, multi-LLM integration, and the technology stack you would recommend for this project.
I’ve spent the last few months building WorldNeural, a free knowledge platform for AI.
The original idea came from a problem I kept running into: AI information is incredibly fragmented.
Models are in one place, papers somewhere else, benchmarks on different leaderboards, pricing on provider websites, companies and people somewhere else, and news moves faster than all of them.
So I built WorldNeural to bring these things together and, more importantly, connect them.
Today it includes thousands of AI news articles and research papers, 79 models, 80 companies, 150+ concepts, 200+ jobs, plus benchmarks, tools, people, events and an AI timeline.
For example, you can start from a model and explore the company behind it, related research, benchmark results, pricing, people and news — with links back to the original sources.
I launched it publicly recently, and the most useful feedback I’ve received so far was actually a difficult question:
“If I already use OpenRouter for models, Hugging Face for papers/models and GitHub for projects, what exactly will WorldNeural save me?”
That question stuck with me.
I can keep adding more data and features, but I don’t want to confuse “more stuff” with “more value.”
The platform is completely free. My current monetization idea is relevant B2B advertising — particularly companies providing AI APIs/inference and other products targeting AI developers and researchers — rather than putting the knowledge behind a paywall.
I’d really appreciate feedback from other builders:
What would make a product like this something you’d actually return to every week?
And if you think the premise itself is flawed, I’d genuinely like to hear that too.
WorldNeural: worldneural.com