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Your Personal Open-Source Humanoid Robot for $8,999 — JX Mo, K-Scale Labs

Jul 2, 2025 · 19:26

Jingxiang Mo, founding engineer at K-Scale Labs, introduces their open-source humanoid robots: the 5-foot K-Bot (pre-order for $8,999, delivered by October) and the 1.5-foot Z-Bot, both fully open-source from hardware to ML models. The K-Bot uses MIT CHiTA actuators, provides up to 250 TOPS compute, runs an RL-based whole-body controller trained with MJX in 1-2 hours, and offers a Python/Rust SDK (pip install kos) with a digital twin simulator for rapid development. Mo emphasizes modularity—swappable end-effectors and upgradable heads—and positions K-Scale as the first US consumer humanoid robotics company, targeting developers and households. The robots are significantly cheaper than competitors (Tesla Optimus at ~60K, Unitree at 40K) and include VR teleoperation, OTA software updates, and a bimonthly hackathon community.

Text-to-Speech Data Preparation and Fine-tuning Workshop - Ronan McGovern

Jun 3, 2025 · 34:00

Ronan McGovern walks through fine-tuning Sesame's CSM-1B text-to-speech model on a specific voice, using a YouTube video as the data source. He explains token-based TTS models, including how audio is represented via codebooks and how CSM-1B uses a main transformer for zeroth tokens and a secondary transformer for 31 hierarchical tokens. The workshop covers data preparation: downloading audio with yt-dlp, transcribing with Whisper Turbo, manually correcting the transcript, and splitting audio into 30-second chunks (41 clips from a 30-minute video). Fine-tuning uses Unsloth with LoRA adapters (rank 32, alpha 16) on linear layers, training for one epoch with a batch size of 2 and virtual size of 8, reducing loss from ~6.34 to ~3.72. Evaluation compares zero-shot inference (random speaker), voice cloning (closer but imperfect), and fine-tuned plus cloning (best result, producing an Irish-accented voice with natural errors). McGovern recommends 50+ 30-second clips for noticeable effect and notes that combining fine-tuning with voice cloning yields good performance even with limited data.