Notefy is an AI meeting assistant that turns recordings into notes, summaries, and ready-to-share presentations. Upload a meeting securely to get accurate multilingual transcription and an AI chatbot trained on your meeting so you can ask questions and get instant answers. Instantly share outputs with teammates and connect via integrations like Slack and Discord.
Hi HN, I built VectorVid after repeatedly seeing teams hack together Whisper + vector DB to search inside webinars and demos.The problem: You have 100+ hours of videos. You want to index them for RAG. But the pipeline is messy—transcription, frame sampling, OCR, chunking, embeddings, then plugging into your own vector DB.VectorVid does one thing: video → RAG-ready JSON.Input: Video URL (webinar, lecture, demo) Output: { chunks: [{ start_sec, end_sec, text, scene_description, ocr_text, embedding
I have been writing a few posts about improving your vibe coding efficiency lately and this post is one more such contribution. I am building products since 6+ years and this post is about things that you can just start doing and see your vibe coding skills improve with huge margins.One thing to start off, this is neither a guru-kind of post where I will claim I know something you all don't know, nor it is that I am any more intelligent than you. ItItss simply just my personal experience.He
There is a possibility of self-improving artificial super intelligence. While this sounds sci-fi, there is a non-zero possibility of it happening.I have been a hater, I mean... who knows... but for the sake of argument let's accept it as a possible outcome.Given that assumption, is there anything more scary than a space-based, distributed data center in the sky, with a non-aligned agent? How does one unplug that?Think about this for a moment. Starlink is the Internet 2.0. It is a very diffi
Hi HN,I’m the founder of AXION One. We are building a neuro-symbolic microkernel in Rust (Stable 1.78) that attempts to replace heuristic resource allocation with a Vector Symbolic Architecture (VSA) and a Joint Embedding Predictive Architecture (JEPA). The Problem: Running modern AI workloads on Linux leaves policy decisions (scheduling, memory security, energy profiles) to opaque legacy subsystems. You effectively have a black box (the model) running on top of another black box (the kernel), w
Am I expecting too much from a university degree? As someone early in my career, can I still contribute to the education of our field?I’d appreciate advice on learning in public and on whether the approach below makes sense.I’m a 19-year-old programmer from Brazil. I’ve been working on systems for aerospace machining facilities since I was 17. As I’ve learned more about professional software development, I’ve also realized how messy my early code was—which I think is a normal part of learning.I
Hi HN,I’m the founder of AXION One. We are building a neuro-symbolic microkernel in Rust (Stable 1.78) that attempts to replace heuristic resource allocation with a Vector Symbolic Architecture (VSA) and a Joint Embedding Predictive Architecture (JEPA). The Problem: Running modern AI workloads on Linux leaves policy decisions (scheduling, memory security, energy profiles) to opaque legacy subsystems. You effectively have a black box (the model) running on top of another black box (the kernel), w
Hi HN, I've been exploring various applications of formal methods to ML/interpretability and I've been hoping to get more eyes on the approach.I have been working on a small interpretability project I call Symbolic Circuit Distillation. The goal is to take a tiny neuron-level circuit (like the ones in OpenAI's "Sparse Circuits" work) and automatically recover a concise Python program that implements the same algorithm, along with a bounded formal proof that the two
Why Machine Learning Fails at Prioritization ProblemsMachine learning has been enormously successful at perception tasks: vision, speech, translation, classification. But over the last few months, I’ve become convinced it’s the wrong abstraction for a large class of problems that show up in real businesses.These aren’t problems about recognition. They’re problems about prioritization.What I mean by “prioritization problems”In many operational settings, the task isn’t to predict an outcome in iso
With AI advancing fast, which career is most future-secure if I put in serious effort: DevOps, Cybersecurity, or Machine Learning?
Investing.com -- WiMi Hologram Cloud Inc. (NASDAQ:WIMI) stock surged 11.3% on Monday after the company announced the launch of its independently developed Quantum Convolutional Neural Network for ...
Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving real-time monitoring and combustion safety.
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Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
Plaud AI, a San Francisco-based startup that produces AI-powered note-taking hardware, has announced the next generation of ...
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