Let’s play a quick word association game: Peanut butter…jelly. Arches…golden. NES…Netflix? That last one sounds like a stretch, but the [darNES] development team had a Hack Day and a dream. They started with cached Netflix data and ended up playing it on an ordinary NES. (YouTube link)
The data was pre-converted so that the video frames were stored as tilesets and stored in the ROM image. [Guy] used the NES memory mapper (MMC3) to swap the frames. [darNES] had originally planned to use a Raspberry Pi in the cartridge to handle the video conversion and networking, but had to change gears and make a static ROM image due to time constraints and resource availability.
Accessing the Netflix data is just like the days of yore – load the cartridge into an unmodified NES and hit the power button (they didn’t even need to blow on it!). A bare-bones Netflix gallery appears. You can move the white cursor on the screen with the NES controller’s D-pad. House of Cards was the choice, and true to form, the next screen shows you a synopsis with a still image and gives you the option to Play. Recommend is also there, but obviously won’t work in this setup. Still, it got a chuckle out of us. [darNES] admits that due to time issues they did not optimize the color palette for the tilesets. They plan to release more of the technical info this week, but have already given us some hints on their Hacker News thread.
Check out the videos after the break to see the video they fit onto a 256K NES cartridge.
Continue reading “[darNES] Stores Cached Netflix On NES Cartridge”



[Val] cast rays from the center of each wall through the center of the screen. The ray which was longest before intersecting another wall would be the best escape route. This simple solution worked, but only for about 40 seconds. At that point, Super Hexagon would start throwing more complex patterns, and the AI would fail. The final solution was to create an accessibility condition which also took into account how much space was available between the various approaching walls. This new version of the AI was able to beat the game.


