... Optimisation & Reliability Update - Chrome Extension We ve slashed load times and made translations more dependable (currently supports Hindi). What s new: Backend speedups: Skip transcript fetch + vector storage for repeat videos (1 20 ms check). Faster quick-question generation with a lighter prompt + Gemini 1.5 Flash. Reduced similarity search work. Translation reliability: Translate larger chunks instead of every caption line. Hard timeout per translation + circuit breaker to avoid stalls. Bound input size for faster, predictable calls. YouTube Video GitHub ...

... resource-constrained devices. Very quickly we hit the same wall many of you might have faced Retrieval-Augmented Generation (RAG) was essential for most applications, but slow and cumbersome to implement. So we started from scratch. We re-imagined vector search from first principles, moved beyond cosine similarity, and invented a new distance metric. The result? Faster, more accurate retrieval and a foundation for building AI products much more easily. That s how Moorcheh.ai was born. With Moorcheh.ai ...

... assistants and agents for small, resource-constrained devices. Along the way, we discovered that Retrieval-Augmented Generation (RAG) is essential for most applications but often becomes a major bottleneck. From first principles, we developed Moorcheh.ai a next-generation vector search engine built on a new distance metric (moving beyond traditional cosine similarity). The results exceeded our expectations, and we ve continued to build on that foundation. Today, Moorcheh.ai is a platform that lets you create a fully functional, production-ready ...

... embed on your website and train using your own content. Upload your PDFs, DOCX, or TXT files Embed the AI on your site And boom, it can instantly answer questions from your content Thanks to OpenAI embeddings + vector search, it actually understands your data. I m building this solo, no funding, and fully in public ...

... GitHub PR, so you can audit the JSON before you trust it. Day-one blank slate. The registry opens today , first movers get instant visibility. We d love your feedback on 1. Categories you d like to filter by (vector DBs, DevOps, AI models, etc.). 2. Security gotchas we should bake into the submission checklist. 3. Your own provider! Drop a PR and we ll merge within 24 h. Try it: https://www.utcp.io/registry Add a tool, propose a provider ...

... Creativity is currency Community is the new capital Young people are more powerful than ever But in Africa, many Gen Z creators still feel stuck. Too many ideas. Too little guidance. 3/ That s why I m building VectoRise A creative ecosystem that helps Gen Z: Discover their identity Unlock their potential Build purpose-driven lives Launch digital ideas All in one platform. 4/ It s a mix of: Personal branding Tools for digital creativity Community-driven discovery Values that ... ... ground, not distract Think: LinkedIn meets Notion meets Inner Compass made for Africa. 5/ Why share this here? Because Product Hunt helped many bold ideas take off. And I want to build VectoRise

... Just dropped a new integration for developers working with real-world documents and vector search: Tensorlake + Qdrant = structure-aware retrieval at scale. Instead of flat blobs, you can: Parse PDFs into labeled fields extracting metadata like names, dates, balances, etc Embed with semantic structure Store and query with Qdrant filters that actually match your use case Built for RAG, document agents, contract intelligence, and anyone tired of lossy parsing. Full blog: https://www.tensorlake.ai/blog/a... Open to feedback or ideas ...

... corpora Language inference: Fast contextual reasoning beating Meta s LLaMA models in our benchmarks Intent detection: Real-time inference (<65ms latency on CPU) Streaming input: Live video/audio support, no GPU needed Built with a mix of AVX-512 vectorization, LoRA-edge compression, and Z-Phase self-supervised pretraining. Entire stack deploys on-prem, air-gapped, or in your local dev env. We re giving free access to the first 99 devs on our waitlist: https://tally.so/r/meG5RQ Check ...

... wrapper that makes agents improve automatically after feedback. Just 2 lines: pip install dead-simple-self-learning learner.save_feedback("Summarize contract", "Include indemnity clauses if mentioned.") enhanced_prompt = learner.apply_feedback("Summarize contract", base_prompt) No retraining. No finetuning. No vector DB. How it works: Embeds each task (OpenAI/MiniLM) - Finds similar past tasks Retrieves mapped feedback Optionally filters with LLM - Enhances system prompt before running Works with OpenAI, DeepSeek, LangChain agents. If you're building agents and want them to improve ...

... what if I'd like to ask something broad like: "Where are the the biggest performance bottlenecks" or "Tell me if there any obvious bugs in the code", when there's nothing really specific to compare agains't the vector embeddings? Any known ways on how people are solving this ...

... Makers & Builders using LLMs! Anyone else building cool stuff like PDF Q&A or custom bots with RAG, but finding the context retrieval step... frustrating? Most AI app data stacks these days use vector search (Pinecone, Weaviate, etc.) to grab text chunks for the LLM. But sometimes it feels like it finds stuff that's keyword-similar while totally missing the actual point the user asked for. Leads to those slightly weak or "confidently wrong" LLM answers ... ... what's your single biggest headache right now in getting truly relevant context for your RAG pipeline? Is it nailing the chunking strategy? The embedding choice? Hitting the limits of pure vector

... real, practical AI skills without coding experience. That s exactly why we created this course. We ve designed it to be hands-on, teaching real-world AI automation using no-code and low-code tools like N8N, CrewAI, and VectorShift so you can build smart workflows, optimize business processes, and save hours of manual effort. We ve worked with companies and professionals integrating AI into their workflows, and one thing is clear: AI is no longer optional. Whether ... ... code workflows, and how to leverage AI in your business. If you're ready to move from questions to hands-on skills, our AI Automation Course will guide you through real-world use cases using N8N, CrewAI, and VectorShift

... accelerating development, but could it also be a major security risk? AI-generated code sometimes introduces vulnerabilities due to improper training data will this create new attack vectors? Could hackers use AI to automate exploits and find weaknesses faster than ever? On the flip side, will AI-powered security tools like Snyk AI or Dependabot actually make software safer by detecting threats in real time? Are we heading toward more secure software, or will AI open Pandora ...

... search tool - Gives the API access to leverage web search and cite sources Computer use tool - Gives the API access to use a remote machine, this is huge File search tool - Upload a batch of files to a vector store and then query them via an endpoint Web search tool I read this as we can now give API calls the ability to search the web and the return object can contain citations. This is interesting to me because ... ... this programmatically and unlocks a ton of new use cases for automation. Computer use tool pricing: $3 per 1M input tokens and $12/1M output tokens. File search tool The new file search tool allows you to create vector

... built, for anyone who wants to build AI apps fast. It has pretty much every piece that every successful AI app uses right now. RAG read from local documents (pdf,text) Tools fetching data from 3rd parties DB Vectors vectors

... first I'm working at RAG app that will serve as internal knowledge hub for companies. Connect your tools and find anything through slack! Currently trying to figure out how to do sales and document upload to vector database Comment from Gabriel Silas(@gabriel_silass): Focusing on my AI tool for creators, but marketing's proving a bit tricky. Comment from Kamil Makowski(@makos): Finishing my macOS app for two-way Google Calendar sync Comment from Endi Luamba(@deleted ...

... Building Retrieval Augmented Generation (RAG) system poses several challenges, but perhaps the most daunting ones are text segmentation and vectorization. While organized knowledge bases like FAQs are relatively straightforward to handle and yield good results, real-world documents such as regulations, methodologies, and plans present unique difficulties. These documents tend to be lengthy, containing dispersed knowledge points throughout.When doing Knowledge Bases, the segmentation extraction of documents is very headache-inducing, and the matching effect is also very general ...

... This is the year I will be launching in a few vectors with AI. It s going ...