Real problems people complain about online, pulled every morning and scored out of 100. Build, validate, or skip. How scoring works
Researchers and medical professionals lack an accessible LLM that combines 23andMe-style genetic data with medical records to predict or identify genetic disease sequences.
X23d agoToolMedicine & Health
Content creators find it frustrating that iPhone requires staying on one app to monitor video uploads until complete before switching to another app.
X14d agoToolMedia
The Amazon Alexa app has terrible UX where the AI prompt covers and disables links to view full articles, with no way to dismiss or interact properly.
X14d agoToolOther
3D artists and developers struggle to efficiently import and convert CAD data into SDS (subdivision surface) meshes that are immediately usable in modeling software, leading to manual rework and lost time.
X14d agoToolDev
Users find ride-hailing apps like InDrive and Bolt frustrating and unsafe to use at night, preferring Uber but needing better options among competitors.
X14d agoToolTransportation
Students struggle to track scholarship application deadlines, resubmission requirements, and fund dispersal status across multiple government schemes. A unified dashboard could consolidate application timelines and payment schedules. [Trending: "scholarship up" with 100+ searches in IN]
Google Trends14d agoToolEducationIN
Used car transactions lack transparency, trust, and convenient platforms. Buyers face information asymmetry, scattered listings, and difficult logistics. A marketplace could aggregate verified listings and simplify the buying process.
YC Graveyard6y agoToolConsumer
Hey HN, I’m Antonio from Nori Robotics (https://norirobotics.com). We build a $1,688 bimanual mobile robot in San Francisco for robotics developers and researchers.I started working on Nori while doing robotics research at Columbia. I was teaching robots through human demonstrations, but getting my hands on affordable hardware was difficult. Most labs have one or two expensive robots, which makes it hard to collect large datasets, run long experiments, or test across several robots.So I built my own. After seven iterations the latest Nori has:* 19 degrees of freedom* Two 7+1 DOF arms with a 1.5 kg payload per arm* A 55 kg telescoping lift* A differential wheeled base* Four 720p, 30 fps RGB cameras* 2D lidar* A dual microphone array with full-duplex voice communication* A 432 Wh battery* A Raspberry Pi 5 with 4 GB RAM (SLAM and safeties are run on board, heavier ACT and VLAs must be run from a computer via LAN or a server via WAN)Getting this under $2,000 was the main engineering challenge. Nori has more than 100 moving and structural parts, so costs add up quickly across actuators, bearings, wiring, power delivery, and assembly. Some main choices we made to get the cost low was using high-ratio servos instead of QDD motors, and using a wheel base instead of legs.We assemble each robot in San Francisco and have designed it to be easy to manufacture and repair (we offer 3D files to print repairs).Our open SDK includes teleoperation and demonstration tools: https://github.com/Nori-Robotics/nori-sdk-pyWe also built a browser-based simulator so you can try it out: https://lab.norirobotics.com/nori/modelWe’ve shipped our first robot and are building the next batch. Eventually, we want people without robotics experience to teach Nori tasks and share them with other owners.Currently the hardware is already capable of basic cleaning tasks, opening drawers, restocking shelves and pouring beers. Here is a video of Nori doing th
Hacker News14d agoToolAI
I'm the developer. I built this because AI-generated conspiracy videos were getting out of control in my own YouTube feed. Weedout is a $1.99 Safari extension for macOS that removes videos YouTube labels “Made with AI” from feed, search, related videos, playlists and Shorts. It uses YouTube's label rather than AI detection, runs locally, and does not catch unlabeled videos.Source for developers who want to fork or build: https://github.com/masteranza/weedout-for-youtubePull requests are not accepted; the repository is for independent forks.
Hacker News14d agoToolAI
Shoppers face frequent recalls, contaminants, and unsafe food with no easy way to scan items for instant 'safe' or 'risky' alerts, as current info sources (news, labels) are insufficient and slow.
X16d agoToolFood & Nutrition
Users struggle to make AI-generated writing, websites, and photos look authentically human, leading to detectable or low-quality outputs that need manual fixing.
X1mo agoToolAI
Users want a specialized app interface for interacting with Claude AI, mirroring the convenience of Codex, to improve daily workflows and accessibility.
X15d agoToolAI
Listeners want adjustable playback speeds (like 0.5x) for voice notes to better understand fast talkers or save time, which current apps lack.
X19d agoToolProductivity
Users are frustrated by seeing unwanted short-form video content on the platform and seek simple, granular blocking tools beyond current options.
X15d agoToolMedia
As AI agents become economic actors needing fast, software-speed money movement for compute, data, and services, there's no dedicated on-chain or payment infra to support this new class of actors.
X16d agoToolAI
Travelers face hassles like long lines or mobility issues at airports and want a reliable, pre-bookable concierge service integrated with flight bookings to avoid delays and stress.
X23d agoToolTravel
Real-time alerts and incident tracking for water desalination and utility infrastructure failures. Helps authorities, industries, and municipalities coordinate response to widespread system outages. [Trending: "מתקני התפלה" with 500+ searches in IL]
Google Trends15d agoToolLogistics & DeliveryIL
Hi HN, we’re Brandon and Kingston, the founders of Hebbian Robotics. We built HFlow (https://github.com/Hebbian-Robotics/hflow), an SDK that turns multimodal recordings from robots and human operators into standardized, quality-checked episodes and queryable dataset manifests. A recording can contain synchronized video, joint states, actions, timestamps, and metadata, and HFlow processes those streams together.Here’s a demo of HFlow in action: https://www.youtube.com/watch?v=xni0GwV-xAwRobotics data pipelines often begin as scripts: one transcodes video, another checks timestamps, another adds labels, and another copies selected recordings into a training set. This works until the corpus grows. Then it becomes difficult to know which code ran, why an episode was excluded, or whether a dataset can be reproduced. The first pain is usually quality control because frozen cameras, missing topics, timestamp drift, and duplicate recordings can quietly enter training data.Brandon first encountered this while training embodied AI models for two-arm industrial cleaning robots. Kingston had run into related problems while building high-throughput infrastructure at Jane Street. Later, while speaking with robotics data providers, we kept seeing teams rebuild similar processing and quality-control infrastructure. We learnt that processing robotics data is itself one of the bottlenecks to improving robotics models.An HFlow pipeline consists of transformations, checks, labels, and enrichments. The SDK exposes them as plain Python functions that receive an episode and return measurements, artifacts, or transformed data. During development, the functions can run in-process. For scheduled corpus processing, HFlow packages the same registered steps as Airflow 3 DAGs, where teams can inspect task status, logs, retries, and reruns.HFlow currently accepts one MCAP file per episode. MCAP (https://mcap.dev/) is an open container format by Fo
Hacker News15d agoToolAI
I built FnScribe because I'm pretty privacy concious and wanted a wispr flow-like app that kept everything local and on device. Currently works for Mac (sillicon and intel).It's dead simple. Hold the fn key, speak and release. I use a quantized Wisper small.en model for transcription. It inserts the text into the active application. There's also a hands-free model for longer dictation. Audio transcription is kept in memory. There's no account or transcription history. Clipboard contents are restored after it inserts it. GPLv3, Mac-only, English only..still in alpha. Hope you enjoy it! Would love some feedback.
Hacker News19d agoToolDesign & Creative
Hi HN, I'm Kushagra, one of three founders of Almanac, a Hermes with a brain that knows everything about your company.We started our journey with setting up Hermes for our company, thinking it must be easy. We wanted an agent that would know every context about our company, so we could ask questions and get context-appropriate responses to.This started a very annoying and difficult journey. Setting up Hermes, getting it to talk right, building OAuth apps for every connector myself, then feeding it context myself, and ultimately struggling with Hermes's default memory. At the same time, we saw our YC batchmates struggling with the same problem, and we saw an opportunity.So we built Almanac. This is how it works. You sign up, you get a Hermes agent straight out of the box. You have a one-click connect to any account (Gmail, Calendar, Granola, PostHog, etc). You have personal accounts (only accessible by you) and also shared accounts (accessible by everyone in the company). The consequence being I can never see my cofounders' accounts.The “brain” of this agent is wikis. We pull in information from your connected sources, and start organizing this information in two wikis. A personal one, for you, which understands who you are, what your preferences are, the people in your life, and the things going on in your life. The second wiki is a company wiki, which includes what the company is, what you’re working on, what the roadmap is, and what the blockers of the company are. Your agent ultimately has access to these two wikis and the original accounts, which invoke the feeling of “it just knows you.”Here’s a demo: https://www.youtube.com/watch?v=ajXP5PHuK18We're three cofounders, Rohan, Kushagra, and Divit, and we've been friends for 11 years, since studying for the IIT-JEE. We all did Electrical Engineering (Rohan at IIT Delhi, me at IIT Kharagpur, Divit at BITS Pilani, Hyderabad), and Rohan and I later went to Harvard, where this pr
Hacker News15d agoToolAI