R.
6-axis life form that can express emotion and dance
R. launched on November 24, 2017 with 136 votes, #288 of 3,137 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 8 years on.
What it does
R is the worlds first emotional 6-axis life form with unique possibilities to express emotions and react to a conversation driven by baidu's leading AI technology. With six fully independent axes, loaded with sensors and microphones, & with the same loudspeaker design as the H built into the base, motor control will make it dance & express feelings
R is an emotional 6-axis life form using baidu artificial intelligence and industry-grade motor control to react and express emotions.
Does a similar job
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Neural emotion matrix for NPCs2025 · github.com · ▲48Hey! I built this system to humanize NPCs by giving them emotions using Rust and ML. The system provides emotion coordinates (based on Russell's circumplex model) from text input or actions, with persistent emotional memory per entity. Think NPCs that remember how they feel about specific players or events. I pre-trained a DistilBERT model on ~1k video game dialogues (Skyrim, Cyberpunk, etc.) and plan to extract and evaluate 100k+ dialogues soon. However studio/team can manually add dialogues to enrich their own dataset. The matrix doesn't generate dialogue, it only analyzes content.…
- RORebuild of Blossom, an open-source social robot2024 · msgtn.xyz · ▲58
From the post: Blossom is an open-source robot platform for human-robot interaction (HRI) research that I developed during my PhD. I’ve used Blossom for research in design, machine learning, and telepresence; others have made Blossoms for their own research purposes. I have continued working on “rebuilding” the entire platform: I redesigned the inner frame as a model kit, complete with Gunpla-inspired runners and instructions, and refactored the codebase as r0b0, a Python library for communicating between hardware peripherals and software applications. In preparation to present Blossom at…

I ran a language model on a PS2Mar 2026 · github.com · ▲46The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.

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