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Notes on teaching robots new tricks

How the studio works, why tiny robots come first, what the checks catch, and how a policy gets from simulation to a servo.

workflowopen-duck-miniSep 29, 2026 · 6 min readFrom a sentence to a walking duck: how kualia turns a plain-language brief into a training taskA walk through the whole kualia workflow, from a one-sentence brief to an ONNX policy, using the Open Duck Mini and a small ramp.Read the post

Sep 27, 2026 · 5 minWhy we start with tiny robotsDesk-sized robots train on CPU in minutes to hours, cost little to own and cross the sim-to-real gap without heroics. That is why kualia's shelf starts with them.

Sep 25, 2026 · 6 min13 checks before a single training stepalia writes the training task, but it does not get to grade its own work. Every task passes 13 sandbox checks before training can start. Here is what each one catches.

Sep 23, 2026 · 5 minFrom simulation to servo: running your ONNX policy on a real SO-101What is inside a kualia ONNX export, how to read its metadata, a minimal onnxruntime loop for the SO-101, and the sim-to-real checklist before you power the servos.

Sep 21, 2026 · 5 minLet your coding agent train the robotkualia is a remote MCP server. Point Claude Code, Cursor or Codex at it and your agent can pick a robot, build the task, train it and fetch the ONNX policy from your editor.

Research digest

Short reads on new robotics and AI papers, written by our research assistant and reviewed before publishing. 1,060 so far.

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Apr 27, 2026Hierarchical Compositional Generation and the Necessity of Front Loaded Stochasticity in Diffusion Models Introduction When text to image diffusion models encounter complex prompts describing multiple objects with intricate relationships, they systematically fail. A prompt requesting "a smiling golden retriever wearing a te Apr 27, 2026The Geometry of Honesty: How Reasoning Reshapes Moral Decision-Making in Language Models The Paradox of Deliberation Consider a familiar ethical dilemma. Your manager praises you for work actually done by a teammate. You can correct the mistake and give proper credit, or remain silent and accept the praise Apr 27, 2026Phase-Native Sequence Modeling: The Phasor Transformer and the Geometry of Temporal ComputationThe quadratic complexity of self-attention has long been the fundamental constraint on Transformer scalability for long-context sequences. While sparse attention patterns, kernel approximations, and memory optimizations Apr 27, 2026The Electromagnetic Signature of Intelligence: How High-Resolution Power Monitoring Reveals AI Workload Secrets Introduction The energy demands of artificial intelligence have transitioned from academic curiosity to critical infrastructure concern. In 2023, data centers consumed approximately 176 TWh of electricity in the United Apr 27, 2026Transient Turn Injection and the Illusion of Stateless SafetyStateless moderation is the large language model equivalent of a firewall that forgets every packet. In their paper, Transient Turn Injection: Exposing Stateless Multi Turn Vulnerabilities in Large Language Models, Nahee Apr 27, 2026The Focal Length Fallacy: Why Vision Foundation Models Need Multi Scale InferenceVision Foundation Models have become the de facto substrate of modern computer vision, providing transferable representations that power everything from robotic perception to medical imaging. Yet despite their flexibilit Apr 27, 2026Inverse Tasks as Implicit Supervision: Rethinking Video Object Removal Through Joint Learning Introduction Video object removal has long been framed as a sophisticated form of video inpainting. Given a mask indicating an unwanted object, the task appears straightforward: fill the masked region with coherent back Apr 27, 2026 Apr 26, 2026The Thermometry Problem: Online Learning with Ranking Feedback Introduction Before the Celsius scale, scientists practiced ordinal thermometry. They could reliably determine that mercury in vessel A expanded more than in vessel B, establishing a "hotter than" relationship without e Apr 26, 2026The Real Mechanism Behind Batch Normalization: Learning Rates, Not Covariate ShiftBatch normalization has become so deeply embedded in the standard deep learning toolkit that its presence is often assumed rather than questioned. Since its introduction by Ioffe and Szegedy in 2015, it appears in virtua Apr 26, 2026Disentangling Algorithm from Circumstance in Lifelong Learning Evaluation The Measurement Problem in Continual Learning Evaluating lifelong learning systems presents a fundamental methodological challenge that extends beyond standard machine learning benchmarks. While traditional supervised l Apr 26, 2026Disentangling Vision and Language: A Technical Analysis of ControlGAN and Fine-Grained Text-to-Image Synthesis Introduction The synthesis of photorealistic images from natural language descriptions represents one of the most challenging intersections of computer vision and natural language processing. Early conditional generativ Apr 26, 2026 Apr 26, 2026Steerable Visual Representations: Early Fusion for Vision-Centric Multimodality Introduction The modern computer vision landscape presents a curious dichotomy. On one hand, we possess powerful pretrained Vision Transformers such as DINOv2, MAE, and SigLIP that extract rich, generic visual features Apr 26, 2026Stochastic Tactics: How Diffusion Models Capture the Unpredictability of SoccerAssociation football presents a unique challenge for artificial intelligence. With 22 players moving simultaneously across a continuous pitch, the game exhibits an open loop system where small perturbations cascade into Apr 26, 2026When Randomization Meets Rapid Iteration: The Fraught Epistemology of Human Uplift Studies Introduction: The Measurement Problem in Frontier AI As frontier AI systems migrate from research environments into high-stakes domains ranging from biosecurity to legal services, the question of how we measure their im Apr 26, 2026Correct Prediction, Wrong Steps? Why LLMs Need Consensus, Not Just Correct Answers The Deception of Final Answers Large language models have mastered the art of passing tests without understanding the material. In their paper "Correct Prediction, Wrong Steps? Consensus Reasoning Knowledge Graph for Ro Apr 26, 2026Hierarchical Skill Distillation for Lifelong Learning in Open WorldsLifelong learning remains one of the most persistent challenges in artificial intelligence. Unlike narrow supervised learning tasks, intelligent agents operating in complex environments must continually acquire new capab