Alternatives
Products that do what NNext.net – A Firebase-like managed vector storage for ML applications does
Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up…
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2021 · github.com
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2018 · rpubs.com
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I’m 15 and self-taught. I'm learning ML from scratch because I want to really understand how things work. I’m not into frameworks. I prefer math, logic, and C++. I implemented a basic MLP that supports different activation and loss functions. It was trained via mini-batch gradient descent. I wrote it from scratch, using no external libraries except Eigen (for linear algebra). I learned how a Neural Network learns (all the math) -- how the forward pass works, and how learning via backpropagation works. How to convert all that math into code. I’ll write a blog soon explaining how MLPs work in…
2025 · github.com
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2023 · github.com
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Hey HN, At Mintplex Labs are building developer tools for AI applications. One area we encountered frustration was the use of Vector Databases like Pinecone, Chroma, QDrant, or Weaviate to "unlock" long-term memory and contextual answers. It is nearly impossible to manage this data when in use for production. The craziest thing was how you cannot atomically CRUD any vectors in most of these vector databases. Let alone easily copy, clone, or migrate data or entire indexes without paying for re-embedding - among other things. With VectorAdmin you get a database level UI with the ability to…
2023 · vectoradmin.com
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Hi HN, I'm Daniel from Superlinked! We have built an open-source framework that improves vector search relevance and usefulness by combining structured metadata with unstructured data in your embeddings. We included self-hostable API server that sits between your data sources and vector database. Docs: https://docs.superlinked.com/ We're launching our cloud offering soon where you can use Superlinked to orchestrate high-performance retrieval for RAG, Search & Recommendation apps in your own cloud. Looking for feedback and happy to answer questions!
2024 · github.com
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Hi, I'm Ben, the co-creator of Embedbase. Embedbase lets you use OpenAI Embeddings and Pinecone seamlessly. For example, you can add Embedbase to your app and pair it with GPT3 to allow people to search using natural language (e.g. How many workouts did I complete last week?), or simply expanding your current search experience beyond full-text search (e.g. looking for "similar" documents in Notion to find other related information) Managing embeddings is uncharted territory, we needed to discover the best practices ourselves. Now we're happy to share our learnings with Embedbase. Shoot if…
2023 · embedbase.xyz
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Disclaimer it is a heavily AI assisted project. The goal was not to be the most performative but the kind that's easier to learn from. I wanted to share this in case there are people who had the same idea or wanted to see something like this.
Jun 2026 · github.com
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Hey folks, Elias here. Excited to unveil my latest project. Why I Built This: Traditional keyword search isn't cutting it. I've used LLM-embeddings to provide more nuanced, relevant results. How It Works: LLM-embedding similarity on curated datasets for semantically similar results. No need to iterate over keywords any more. Current Datasets: - YC Companies - Show HN Posts, - Ask HN Posts - ProductHunt Startups - Github Top 200k Repos Use Cases: - Validate a product idea's existence - Check if someone already Asked HN something - Have fun - search random terms and see what pops up Want to…
2023 · payperrun.com
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This is an AI generated TED talk from a system we built at the TED AI hackathon this weekend. It's built on top of ElevenLabs, SDXL and Wordware (https://wordware.ai/). We also have a custom index of over 2 million arXiv papers and 6 million Wikipedia articles. All open source: https://github.com/ashvardanian/extrapolaTED
2023 · youtube.com
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2023 · github.com
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2018 · dataturks.com
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2021 · losttech.software
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Hello HN, I recently posted a work-in-progress paper, along with code necessary for replicating all its results, at: https://github.com/glassroom/heinsen_routing Among other things, the code in this repo outperforms Hinton et al.'s recent state-of-the-art result in visual recognition[0] while requiring fewer parameters and an order-of-magnitude fewer training epochs. Most of the original research we do at work tends to be either proprietary in nature or tightly coupled to internal code, so we cannot share it with the world. In this case, however, I was able to remove all…
2019
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Hey HN, I’m a solopreneur and have been in the SaaS space for the past 3 years. My last three startups failed, and a common challenge in all of them was figuring out how to reach my audience. SEO always seemed like the answer, but I didn’t know where to start. It felt overwhelming—so many technical terms like keyword research, clustering, SERP, semantics, topical authority… I could go on. That’s where my idea for my next startup came from: building an all-in-one SEO tool that’s easy to use and understand. The complexity of SEO is hidden behind a simple UI, and the only thing users need to do…
2025 · babylovegrowth.ai
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Hi HN,I am Anubhav from RamanLabs.We have been developing dedicated modules based on deep-learning for purposes like face-detection,object-detection,pose-estimation etc. We hope to make it easy for developers,hobbyists to integrate such functionalities into their existing app/pipeline at the cost of a few milliseconds.All our modules run end to end in super-realtime even on consumer-grade CPUs[0]. For now we provide only Python based API. We provide Demo for each of the modules to allow testing for your desired data distribution.We also have a blog[1] where we hope to add more technical…
2022 · ramanlabs.in
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Dec 2025 · github.com
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