Nunchux AI (nunchux.ai) comes out of stealth today. Ten years ago at Berkeley, we spent whole nights on a Titan X in Theano, trying to make iGAN, pix2pix, and CycleGAN real-time so creators could see the results the moment they asked for them. Image models now cost about 10,000x more to run. Video is another two orders of magnitude beyond that. The reason for speed has not changed. Every attempt is a question, and the answer changes the next question. Latency decides whether the result arrives while the idea is still yours. Cost decides how many questions you get to ask. Quality decides whether the answers were worth asking for. So we are building fast, cheap, and high-quality multimodal inference for every developer and enterprise, and we are building with researchers from MIT, CMU, and Berkeley, along with engineers who have shipped at AMD, NVIDIA, and Snowflake. We are now opening access through the waitlist. New accounts get $10 in credits.

Try out Sheng-Yu's latest work with pip install tpips. TPIPS is a text-prompted image perceptual similarity metric and a revisit of the classic LPIPS metric.