What Did I Watch?
Describe any movie or show from memory, AI finds it for you
What it does
Ever tried explaining a movie you watched years ago but couldn't remember the name? Just describe it in your own words "kids with spinning battle tops" or "fish looking for his son" and AI instantly identifies it. Supports 20 languages, voice input, and shows posters, ratings, and where to watch. Open source and free to use..
Does the same job
all alternatives →
- WDWhat Did I Watch? – Describe any movie/show and AI finds itFeb 2026 · whatdidiwatch.onrender.com · ▲5
- AMAI Movie Finder – I created a way to find movies by describing2025 · aimoviefinder.com · ▲10
Hi Hacker News, I'm excited to share a project I've been passionately working on in my spare time: AI Movie Finder (https://www.aimoviefinder.com). The idea was born out of a simple, yet frequent, frustration: having a movie on the tip of my tongue but being unable to recall the title. All I could remember were fragments – a specific scene, a snippet of dialogue, the general plot, or even just the mood it evoked. Traditional search engines often fell short with these kinds of abstract queries. So, I decided to build a solution. AI Movie Finder uses a natural language processing…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
