Alternatives
Products that do what Exploring Russian Election Interference with Graphiti does
Hi HN, we're Jack and Daniel from Zep. We've built a visual exploration tool and AI assistant for analyzing Russian election interference in the run-up to next week's US elections. The Explorer uses Graphiti, Zep's open-source temporal Knowledge Graph library. Graphiti autonomously creates dynamic, temporally-aware knowledge graphs representing complex, evolving relationships between entities. To offer users a detailed view of Russian state operations and related topics, we populated the graph with over 50+ sources. These include US DOJ indictments, research by US and foreign governments,…
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2020 · github.com
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- 4GA
2015 · github.com
- 5LT
2015 · linkurio.us
- 6IB
I run a small AI lab and playground and got super excited about Anthropics paper "Verbalizable Representations Form a Global Workspace in Language Models" (https://transformer-circuits.pub/2026/workspace/index.html) It talks about how they use a tool they call a Jacobian Lens to view inside the middle layers of LLM while it's working before it commits to a word (token). I wanted to see if I could get a version of this running on the open models and to my surprise it worked! I ran some experiments with it and build a public facing free tool anyone can use with your…
Jul 2026 · lucid.earthpilot.ai
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Get Cited in Google AI search, ChatGPT, Perplexity & Copilot
Dec 2025
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Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think!
Jun 2026 · atomprophet.io
- 9TA
In this post, we document the results of some experiments comparing vanilla Graph RAG (just a single pass of text2cypher) vs. a router agent Graph RAG approach that can call vector search tools alongside text2cypher. The routing agent uses an LLM to decide which vector search tool to call, depending on the terms identified in the question, and it works quite well. The results show that recent frontier LLMs like `gpt-4.1` and the trusty workhorse `gemini-2.0-flash` produce great quality Cypher reliably and reproducibly, with some prompt engineering to ensure that the graph schema is formatted…
2025 · blog.kuzudb.com
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Hey HN community! Over the past year, AI copilots like Cursor and Windsurf have fueled a dramatic shift in software engineering workflows. And yet, many technical users in adjacent fields like data science and analytics have been unable to reap the rewards of this revolution. It turns out that the existing tools are a poor match for analytical workloads. Beyond that Cursor and similar tools have very poor support for Jupyter notebooks, data science is a fundamentally different discipline from software engineering and we believe it requires a correspondingly different tool. We're excited to…
Sep 2025 · sphinx.ai
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Hey HN, Since the launch of GPTs, I’ve struggled with integrating vast, up-to-date knowledge into a custom GPT and embedding it into websites and apps. After months of trial and error, we’ve developed an AI Search & Knowledge Assistant that solves this problem. Over the weekend, I built a demo assistant for Stripe that provides accurate answers, useful links, images in responses, cites sources, and keeps a thread history of your conversations. Here’s what’s included: - 3,700+ public documents full of useful info - 105+ million characters of rich knowledge - Powered by the ChatGPT-4o model…
2024 · demo.ordemio.com
- 13IE
Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the…
2023 · huggingface.co
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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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Based on embeddings of the political parties manisfestos (gathered from ChatGPT) on different matters, we visualise how different they truly are on a PCA projection I want to extend this to US parties/candidates and make it more general
2024 · huggingface.co
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Hi HN, I’ve spent the last decade building hardware products like humanoid robots, 3D printers, and self-driving tractors. I needed a tool to navigate technical documents faster, so I created one with friends. This tool helps with component search, cross-referencing, comparison, and debugging. We’d love your feedback, whether you find it useful or not. Thank you! Try it here: www.convergelab.ai
2024 · convergelab.ai
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Hey folks! This is a project that I've been working in my free time for the past few months. It's a news aggregator that uses AI to select relevant articles and summarize them. The default sources are frameworks and libraries' updates, popular HN topics, and languages' subreddits threads that make past a certain threshold. You can run a local instance (needs an OpenAI key) and customize it with your own sources, and adjust the prompt as well. The resulting website can be browsed at https://dev-radar.com/ My next experiment will be with local news. I'm building some feeds with…
2023 · github.com
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I'm building Comind, an experimental AI system that acts as a cognitive layer for ATProtocol/Bluesky. It's a self-evolving knowledge graph where specialized AI agents ("cominds") process social data through focused "spheres", each guided by core directives. The system builds up understanding by asking questions, making connections, and synthesizing information from the network. I wrote a post describing the general architecture, motivation, and future directions. There's a few small results from Comind's early run. Built with neo4j, a small Modal GPU instance, and the Python atproto…
2025 · cameron.pfiffer.org
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First of all please go check out the amazing project this analysis is based on: https://news.ycombinator.com/item?id=46435308 For my paper [1] I analyzed HN attention dynamics using 72k temporal snapshots from December 2025 to model decay curves, preferential attachment, and engagement survival. Today I’ve cross-referenced these findings with the recent 22GB HackerBook SQLite export to validate my early-engagement prediction models on this 22GB historical subset. [1] Preprint available on SSRN: https://dx.doi.org/10.2139/ssrn.5910263
Dec 2025 · philippdubach.com
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I’ve been experimenting with a graph-based approach to a classic trading problem: why most dip-buying strategies can’t tell the difference between a temporary overreaction and a genuine structural collapse. Most systems treat a −5% move the same regardless of context. My hypothesis was that where a company sits in the market’s structure matters more than the price move itself. The engineering idea I built a knowledge graph of the U.S. public markets with ~207k edges across ~21 relationship types, organized into four layers: Operational: supply-chain relationships (SUPPLIES_TO, PRODUCES)…
Dec 2025
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2016 · open-synthesis-sandbox.herokuapp.com
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Hi everyone, We have been developing a platform to enable professionals to build AI assistants to help them through their work. After a few months, we realized people are trying to sell basic functionalities that can be built from scratch in a couple of hours. Due to this, individuals who are not familiar with the current SOTA are misinformed about the potential of generative models. So, we decided to open up some of our most popular templates as standalone tools for free to empower individuals and set a solid standard for what people should expect. We believe the barrier to accessing…
2024 · join.modularmind.app
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Zep is a long-term memory store designed for conversational AI applications built using modern LLMs. It handles the storage, summarization, embedding, indexing, and enrichment of chat histories, and offers developers a simple, low-latency API to this data. Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to deploying conversational AI applications that provide rich and intimate experiences to users. Key features include long-term memory persistence, auto-summarization, vector search, auto-token counting, and Python…
2023
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Hey there HN! We’re Vasilije, Boris, and Laszlo, and we’re excited to introduce cognee, an open-source Python library that approaches building evolving semantic memory using knowledge graphs + data pipelines Before we built cognee, Vasilije(B Economics and Clinical Psychology) worked at a few unicorns (Omio, Zalando, Taxfix), while Boris managed large-scale applications in production at Pera and StuDocu. Laszlo joined after getting his PhD in Graph Theory at the University of Szeged. Using LLMs to connect to large datasets (RAG) has been popularized and has shown great promise.…
2025 · github.com
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