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Products that do what Miquiniela.com.mx does

Create football prediction pools that actually engage

  1. 1
    Mimosa151

    The easiest way to run a brainstorm, supercharged with A.I

    2022

  2. 2BG

    In Spain, there's a betting game called La Quiniela: https://es.wikipedia.org/wiki/La_Quiniela_(Espa%C3%B1a) Players predict the outcome of 14 football matches (home win, draw, away win). You win money if you get at least 10 correct, and the prize amount depends on the number of winners. Since all bets are public, the number of winners and the corresponding payouts can be estimated for each of the 3^14 possible outcomes. We can also estimate their probabilities using bookmaker odds, allowing us to compute the expected value for each prediction. As a side project, I wanted…

    2025

  3. 3
    Miora443

    Scale your creativity on editable canvas with agent memory

    Jul 2026 · miora.design

  4. 4OR

    Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…

    2023 · github.com

  5. 5CY

    Hello HN, We built Promptrepo to make finetuning accessible to product teams — not just ML engineers. Last week, OpenAI’s CPO shared how they use fine-tuning for everything from customer support to deep research, and called it the future for serious AI teams. Yet most teams I know still rely on prompting, because fine-tuning is too technical, while the people who have the training data (product managers and domain experts) are often non-technical. With Promptrepo, they can now: - Add training examples in Google Sheets - Click a button to train - Deploy and test instantly - Use OpenAI,…

    2025 · promptrepo.com

  6. 6
    Balto103

    Create march madness pools with ease

    2019

  7. 7MC

    Hello friends! We've been working hard on building Mimosa, and would love for you to try it! No signups required. Facilitating brainstorming sessions can be a challenging and time-consuming task. It's difficult to keep everyone on agenda, engaged, and contributing. So we've built Mimosa to be the easiest way to facilitate a brainstorming session. Imagine if a "digital whiteboard" and a "trello board" had a baby, but built with all the best practices of professional facilitation. With Mimosa, you can minimize bias by allowing team members to contribute anonymously before revealing their…

    2022 · mimosa.so

  8. 8CY

    Hi HN! Excited to show off the project we've been working on for the last couple months. We started with an idea for a crazy twist on prediction markets: You come up with a question for traders to predict, and then decide the outcome yourself. For example, you could create a market on “Will my date with [X] go well?” Anyone can bet on it, and the bets create a forecast on the chance your date goes well. After the date is over, you get to judge the result and reward the traders who picked the correct side. There are so many ways for this mechanism to go wrong: the creator of the market can be…

    2022 · manifold.markets

  9. 9
    Jurnee151

    Plan unique team events in minutes

    2021

  10. 10
    ZenML84

    Create reproducible machine learning pipelines

    2020

  11. 11

    Polymarket for your slack channel

    Nov 2025

  12. 12F1
  13. 13

    Open-source, easily create ready-to-use ML models for NLP

    2022

  14. 14UA

    Hello! So, I am experimenting with new approaches to automated machine learning, where you don't need anything besides either data or prompt This is a first platform from my auto ml serie called Łukasiewicz (Jan Łukasiewicz was a logician who created Polish notation) I much appreciate your feedback and if you want to try it out, I created a -75% off promo code "HACKERNEWS" on credits, so it hopefully will cover at least some of computing expenses, but more importantly will let you play with the platform at almost no cost Thank you!

    2024 · lukasiewicz.tmlc.pl

  15. 15

    Free sports prediction pools for friends and coworkers

    Jun 2026 · trofeo.live

  16. 16TS

    Hello Hacker News community! I'm currently working in financial risk management within the banking sector, and I began my career as a Data Science specialist. For quite some time, my friend and I have been developing a small pet project just for fun. This tool has repeatedly helped us save time when testing various hypotheses and machine learning models. The core idea is to combine different scripts—created in various programming languages and virtual environments—within a minimalist graphical interface. Whether you're building models, running a local neural network, or sending requests to…

    2024

  17. 17DA

    Over the past few months, I have built a distillation toolkit that supports cross-tokenizer distillation (e.g., distilling from LLaMA to Qwen vocab, or others). This approach has worked well on reasoning datasets like AIME, and we’ve validated on models like Phi and Qwen. We’ve also integrated Modal for quick deployment (with $30/month credits to try it out). Would love any feedback! GitHub: https://github.com/agokrani/distillKitPlus Docs: https://distillkitplus.mintlify.app/

    2025 · github.com

  18. 18
    Nutmeg4

    A World Cup 2026 prediction pool for your group chat

    Jun 2026 · nutmeg.bet

  19. 19LM

    We are the developers of an open-source package Metaflow that we started at Netflix. Metaflow provides a human-friendly interface to the full stack of ML infrastructure, including data access, compute, workflow orchestration, and versioning. It is used by hundreds of companies across industries. Over the past years, we have seen that there are two major stumbling blocks for folks who want to learn to build real-world ML applications: 1) Setting up the full infrastructure stack in the cloud costs time and money. The investment is worth it once you know what you want to do, but that's not…

    2023 · outerbounds.com

  20. 20
    Quinix3

    Your World Cup pool — without the WhatsApp chaos

    Jun 2026 · quinix.app

  21. 21MA

    I made this tool to get some better intuition on how neural networks/backpropagation worked, but I'm really unsure what to do with it now, so I've put it up on github, and I wrote a little primer on backprop and neural networks to showcase it. Really curious to hear any thoughts you might have, or anything I got wrong in the write up!

    2024 · github.com

  22. 22UA

    Hey HN! After using a combination of Unsloth and Axolotl a lot, and finding it generally painful to figure out the right performance tuning for things like batch sizing and multi-GPU sharding, I wrote a small Python lib that sets up known-good LoRA training configurations for Llama 3.1 8B and 70B Instruct, and includes helpers for distilling from larger models or training on serverless finetuning platforms, and includes a walkthrough for distilling DeepSeek-R1 into a Llama 3.1 8B LoRA... But you can use it for pretty much any finetuning task, not just distilling large models!

    2025 · github.com

  23. 23

    Built-in two-way texting for pool leagues — no app needed

    Jul 2026 · thepoolleaguemanager.com

  24. 24BA

    Introducing Bonsai 0.5B, one of the first ternary-weight LLMs to rival full-precision models of similar size, such as Qwen 2.5 0.5B and MobileLLM 0.5B. Trained on just 3.8B tokens, using 1,000x less data than other models, Bonsai redefines what’s possible for ultra-efficient training in low-bit models. Next, we're building larger and more powerful ternary-weight models for the edge. Technical Report: https://github.com/deepgrove-ai/Bonsai/blob/main/paper/Bonsa... Model (Unpacked): https://huggingface.co/deepgrove/Bonsai Reach us:…

    2025 · github.com

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