Alternatives
Products that do what Debunking Election Fraud Claims – Interactive Data Viz and Simulations does
Hi HN! I built this after seeing several references to Election Truth Alliance on social media, and after reading their analysis, I just couldn't get the problems I saw in it out of my head. So I downloaded the data, and rebuilt their full analysis from scratch. Their critical error is a simple misunderstanding of the Law of Large Numbers: values collected in large samples converge to the true probability in the sample distribution. (not to be confused with the Law of Very Large Numbers: which states that unlikely things happen given enough time. That confused me too) Technical Details: - No…
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- 2LN
I was reviewing Dirac's Large Numbers Hypothesis (https://en.wikipedia.org/wiki/Dirac_large_numbers_hypothesis) and decided to give it a second go, now with measurements of fundamental constants more precise than 100 years ago. And I stumbled upon a value for Hubble's constant that's uncannily close. Here are the full calculations. https://colab.research.google.com/drive/1K1qoUFvqZp1fWbpcKJWq63nflgwS0ZHh?usp=sharing Meaningless, or meaningful coincidence?
2021
- 3PM
Hey HN, I have been working on using the info-gathering and truth-seeking properties of the markets to get more honest reporting on all sort of things. The idea is to have a market game where people can wager a fake currency on what think is true and then, the citizen reviews the crowd-sourced information and makes a judgement about which position has the best case. It is crowd-sourced journalism with a market game. Please let me know what you think and my email is [email protected], if you have any questions.
Sep 2025 · thecitizen.io
- 4CE
Hello Hacker News! We're a team of YC founders (Meldium W13, Draft S11, TapEngage S11) launching something new (https://www.getcensus.com). How many times has your business team asked you to generate yet another CSV file, write a ”quick report” in SQL, or send some custom data to a terrible API (looking at you Marketo)? We’ve built a product that connects directly to your data warehouse and syncs into apps like Salesforce, Customer.io and even Google Sheets. In fact, your business teams won’t even need to rely on engineering to manage all these pipelines. The tech stack for…
2020
- 5TV
Votizen is working to remove the influence of money in politics by making political decision-making more peer-to-peer. We're using Twitter and our API to pull tweets from only registered voters, and showing how the discussion breaks down among the parties. This has never been done before as far as I know, not even by the major media outlets. Please check it out and let me know what you think. If people are interested, we'll work to improve it for the further debates and campaigns.
2012 · live.votizen.com
- 6CB
A quick weekend side project. I am curious if the like count of a candidate for office can predict if they will win. For the past month or so I have been tracking the likes of several campaigns. Today I put a prettier face on it. http://cmpgns.net/ After the election I will do a quick analysis of the races and see if anything interesting turns up. If anyone adds a candidate I'm missing, I'll go in and add their opponent
2010
- 7TT
Before starting, i posted about america pac's unethical data collection a few days ago. https://news.ycombinator.com/item?id=41139801 Please read the linked cnbc's story, it explains almost everything there Long story short, america pac collects user data while lying and hiding its true intentions. Apparently, the data they collect might (and probably will be) used for door to door canvassing for donald trump. I find this deeply unethical and shady. I thought a nice idea to waste door to door canvasser's time was to pollute the database with fake names, fake emails... i've…
2024 · github.com
- 8MO
I wanted a way for people to support companies and people that align with their political beliefs. Additionally, I think it can serve as a valuable, source-linked public ledger of who said and did what over time, especially as incentives change and people try to rewrite their positions. This is fully AI-coded, researched, and sourced. Additionally, AI helped develop the scoring system. The evidence gathering is done by a number of different agents through OpenRouter that gather and classify source-backed claims. The point of that is not to pretend bias disappears, but to avoid me manually…
Mar 2026 · magaornot.ai
- 9RE
Recent academic work ([1], [2]) has suggested that LLMs can effectively simulate different Internet subpopulations. For example, you may ask ChatGPT to emulate being a high school teacher explaining Newton’s laws of physics. Building upon this, we created Roundtable, a platform that uses LLMs to predict how people will respond to any arbitrary survey question. To do so, we needed to first reduce bias arising from GPT’s training procedure. Because these models are primarily trained on Internet data, they can be heavily skewed towards the demographics of heavy Internet users (e.g.,…
2023 · roundtable.ai
- 10PW
Over the weekend we built Parliament Wow. It's hacky, buggy and slightly broken but it does the job :) Parliament Wow makes it easy to find out what is going on in parliament and what it actually means for you and me. We know that nobody has the time to watch hours of debates, drown in legal paperwork or keep up with the implications of every vote. Not me or you and least of all your MPs. There is just too much data. So we made a solution. We paired some semantic search with every publicly accessible document, audio recording or transcript we could get our hands on + some generative models…
2024 · parliament-wow.threepointone.workers.dev
- 11ER
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,…
2024 · blog.getzep.com
- 12FA
Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
- 13WT
I've been lurking on HN for years. You know the drill: interesting headline, 200+ comments, you dive in thinking "I'll just skim for 5 minutes"... and an hour later you're 36 chambers deep in a thread about memory allocation patterns in Postgres and you've completely forgotten what the original article was about. I don't just want a "summary" (which usually just shortens the noise). I want the meta-consensus: "What is the actual trade-off being debated? Who is winning the argument? Why does this matter?" So I built HNSignals. Think of it less like a "summarizer" and more like a Chief of…
Jan 2026 · hnsignals.com
- 14FF
Hey HN, I'm Steve, co-founder of Factor.fyi, a new data platform for querying and visualizing financial datasets using SQL. During the pandemic, I took much more of an active role in managing my portfolio. I wanted to be able to make informed decisions about the investments I was making, and explore financial data in new ways. Market and Econ data are some of the most talked-about and widely-available datasets out there, but I was frustrated by the lack of options to answer questions I had, like, "What would have happened if I had started dollar-cost averaging VTI back in 2013?"[1] Or, "How…
2022 · factor.fyi
- 157D
hi all. i’ve been shipping a small open project that tries to answer that question with evidence, not vibes. in 70 days it reached \~800 stars. the core claim is simple: many AI failures are not noise. they repeat because the geometry and ordering underneath are stable. if so, we should be able to name each failure mode, set acceptance targets, and stop shipping the same bug twice. ### what it is * a compact Problem Map of 16 reproducible failure modes in RAG and agents. * each item has a minimal fix and measurable gates. examples: * Semantic ≠ Embedding: metric and normalization mismatch.…
2025 · github.com
- 16QC
- 17IC
Hi, everyone! Lately, I've been working on quite a few applications that require a database, and as a result, I need some data to test everything. It has always taken me a lot of time to ask ChatGPT to generate fake data for me, so I decided to create a tool for developers called FakeData. FakeData allows developers to generate fake data easily with a simple UI/UX and customizable fields. This data can be used in their applications to test various functionalities. P.S. The app is not yet finished, and I would love to hear your honest feedback on it. Please be brutally honest about what…
2025 · fakedata-mu.vercel.app
- 18RA
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
- 19UP
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
- 20A1
Hello HN, Wish you a very Happy New Year. StatPecker is our baby project. A cute little infographics generation tool for anybody seeking insights. We recently dropped a new feature, to help user upload CSV upto 50mb or in other words data with ~1 million rows. We wanted to make sure user data doesn’t get leaked, so we developed a mechanism where the CSV is analysed on user’s device. We only use our AI APIs to generate SQL queries on the fly and query the DB on user’s machine, along with the final response for aggregated data. The result turns out to be quite fast. Would love you to try it out.
Jan 2026 · app.statpecker.com
- 21FR
Hi HN — we built Factifi, a Chrome extension that does instant fact-checking on anything you’re reading or watching. Please keep in mind, this is just an MVP and will be buggy and fail. We were constantly pausing podcasts and Substack posts to ask, “Wait, is that actually true?”. After too many 30-minute Google rabbit holes, we decided to automate the work. What it does • Extracts claims from articles, blogs, YouTube videos (and even images) • Assigns a verdict + confidence score using live web search, a 200 M-paper research index, and a few proprietary datasets • Flags likely deepfakes and…
2025 · chromewebstore.google.com
- 22AD
Hey HN, as a former data analyst, I’ve been tooling around trying to get agents to do my old job. The result is this system that gets you maybe 80% of the way there. I think this is a good data point for what the current frontier models are capable of and where they are still lacking (in this case — hypothesis generation and general data intuition). Some initial learnings: - Generating web app-based reports goes much better if there are explicit templates/pre-defined components for the model to use. - Claude can “heal” broken charts if you give it access to chart images and run a…
Mar 2026 · rubenflamshepherd.com
- 23MO
I'm Arthur, and I wanted to share an MVP for Marqt.org, which lets you crowd-source the truth. John Stuart Mill said that "Truth emerges from the clash of ideas." In that spirit, Marqt brings two adversarial sides together to quantify truth and showcase the best arguments for each side. It is inspired by markets, where buyers and sellers discover a product's true price and update it dynamically. The ultimate aim is to build an open-source semantic knowledge base that represents the collective wisdom of humanity in real-time. If we can do this, I believe it can solve the problem of…
2023 · marqt.org
- 24BA
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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