Show HN: LemonSlice – Upgrade your voice agents to real-time video

Hey HN, we're the co-founders of LemonSlice (try our HN playground here: https://lemonslice.com/hn https://lemonslice.com/hn). We train interactive avatar video models. Our API lets you upload a photo and immediately jump into a FaceTime-style call with that character. Here's a demo: https://www.loom.com/share/941577113141418e80d2834c83a5a0a9 https://www.loom.com/share/941577113141418e80d2834c83a5a0a9 Chatbots are everywhere and voice AI has taken off, but we believe video avatars will be the most common form factor for conversational AI. Most people would rather watch something than read it. The problem is that generating video in real-time is hard, and overcoming the uncanny valley is even harder. We haven’t broken the uncanny valley yet. Nobody has. But we’re getting close and our photorealistic avatars are currently best-in-class (judge for yourself: https://lemonslice.com/try/taylor https://lemonslice.com/try/taylor). Plus, we're the only avatar model that can do animals and heavily stylized cartoons. Try it: https://lemonslice.com/try/alien https://lemonslice.com/try/alien. Warning! Talking to this little guy may improve your mood. Today we're releasing our new model* - Lemon Slice 2, a 20B-parameter diffusion transformer that generates infinite-length video at 20fps on a single GPU - and opening up our API. How did we get a video diffusion model to run in real-time? There was no single trick, just a lot of them stacked together. The first big change was making our model causal. Standard video diffusion models are bidirectional (they look at frames both before and after the current one), which means you can't stream. From there it was about fitting everything on one GPU. We switched from full to sliding window attention, which killed our memory bottleneck. We distilled from 40 denoising steps down to just a few - quality degraded less than we feared, especially after using GAN-based distillation (though tuning that adversarial loss to avoid mode collapse was its own adventure). And the rest was inference work: modifying RoPE from complex to real (this one was cool!), precision tuning, fusing kernels, a special rolling KV cache, lots of other caching, and more. We kept shaving off milliseconds wherever we could and eventually got to real-time. We set up a guest playground for HN so you can create and talk to characters without logging in: https://lemonslice.com/hn https://lemonslice.com/hn. For those who want to build with our API (we have a new LiveKit integration that we’re pumped about!), grab a coupon code in the HN playground for your first Pro month free ($100 value). See the docs: https://lemonslice.com/docs https://lemonslice.com/docs. Pricing is usage-based at $0.12-0.20/min for video generation. Looking forward to your feedback! EDIT: Tell us what characters you want to see in the comments and we can make them for you to talk to (e.g. Max Headroom) *We did a Show HN last year for our V1 model: https://news.ycombinator.com/item?id=43785044 https://news.ycombinator.com/item?id=43785044. It was technically impressive but so bad compared to what we have today.