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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 23, 2026The Silent Compression of Reasoning: How Context Length Undermines LLM Self-VerificationThe past year has witnessed a convergence of two major trajectories in large language model development. On one front, test-time scaling has emerged as the dominant paradigm for solving complex reasoning tasks, with mode Apr 23, 2026Beyond Monolithic Representations: Semantic Part Compositing in 3D Generation with DreamPartGenThe field of text-to-3D generation has progressed rapidly from the era of Score Distillation Sampling, exemplified by DreamFusion and ProlificDreamer, toward more structured latent diffusion frameworks. Yet a persistent Apr 22, 2026When Reasoning Obscures Retrieval: An Analysis of the Lost-in-Thought Phenomenon and RecaLLMLong-context large language models have become central to modern AI applications, enabling complex agentic workflows, extended in-context learning, and sophisticated reasoning through test-time compute scaling. However, Apr 22, 2026Steering Generative Intent: Contextual Repulsion for Diversity in Diffusion TransformersThe ascent of modern text-to-image diffusion models has brought us to a curious inflection point. Systems like Flux, Stable Diffusion 3, and their contemporaries now demonstrate remarkable semantic precision, rendering c Apr 22, 2026The Cart Before the Horse: Evidence That Reasoning Models Decide Before They Think The Cartesian Paradox of Machine Reasoning René Descartes established modern Western epistemology on the foundation cogito, ergo sum: I think, therefore I am. The precedence of thought over existence, of deliberation ov Apr 22, 2026The Representational Unity of GPT-4o: Architecture, Inference, and the Unmeasured Cost of Modality Introduction The release of GPT-4o marks a structural inflection point in large-scale multimodal systems. According to the GPT-4o System Card published by OpenAI in August 2024, this model operates not as a choreographe Apr 22, 2026The Pixel-Voxel-Text Triad: Reconstructing Space Without BoundariesThe transition from narrow field of view cameras to omnidirectional perception represents more than a hardware upgrade for embodied agents. It constitutes a fundamental shift in how machines model the geometry and semant Apr 22, 2026The Expertise Trap: General365 and the Unsolved Challenge of General ReasoningThe contemporary narrative surrounding large language model capabilities has become fixated on Olympiad mathematics. We are shown charts where models achieve gold medal scores on the International Mathematical Olympiad ( Apr 22, 2026When SGD Proxies Fail: Optimizer Aware Data Attribution for Modern Deep Learning Introduction Data attribution has become a critical bottleneck in modern machine learning pipelines. As training datasets grow to billions of samples and models scale to trillions of parameters, the ability to identify Apr 22, 2026The Limits of Distribution Sharpening: Why Task Rewards Drive Real Capability Gains in Language ModelsThe integration of reinforcement learning into large language model post-training has fundamentally altered the trajectory of artificial intelligence development. Where once next-token prediction dominated, we now see so Apr 22, 2026Unpacking FASTER: Horizon-Aware Scheduling for Real-Time Flow-Based Vision-Language-Action ModelsThe deployment of Vision-Language-Action (VLA) models in physical environments marks a critical inflection point in robotics research. While simulation studies have demonstrated impressive dexterity through diffusion mod Apr 22, 2026Latent Phase Inference: Reconstructing Dynamical Systems from Temporal FossilsThe challenge of reconstructing complete spatiotemporal dynamics from fragmentary evidence sits at the intersection of inverse problems and scientific inference. In paleontology, researchers reconstruct entire ecosystems Apr 22, 2026Fit Aware Virtual Try On: Moving Beyond Appearance Transfer with the FIT DatasetVirtual try on technology has reached impressive levels of photorealism. Recent diffusion based methods can transfer garment appearance onto person images with remarkable fidelity. Yet as Karras et al. observe in "FIT: A Apr 22, 2026Optimal Splitting of Language Models: The Hidden Efficiency Gains in Multi-Domain TrainingThe field of large language model training has largely converged on a standard recipe: massive pretraining followed by specialization. But a new paper from Apple researchers titled "Optimal Splitting of Language Models f Apr 21, 2026The Geometry of Dialogue: Why Spatial Co-Location Matters for Audio-Driven Facial Animation Introduction For nearly a decade, the computer vision community has pursued the perfect talking head. We have witnessed remarkable progress in lip synchronization, micro-expression synthesis, and identity preservation f Apr 21, 2026The Hidden Bottleneck in Mathematical AI: Why Retrieval, Not Reasoning, Limits Mathematical RAGRecent advances in large language models have pushed mathematical reasoning benchmarks to unprecedented heights. Contemporary systems now claim gold medal performance on International Mathematical Olympiad problems, with Apr 21, 2026The Granularity of Meaning: Structural Abstraction as the Key to Machine Analogical ReasoningLarge Language Models have demonstrated remarkable capabilities across countless domains, yet they remain stubbornly susceptible to surface level pattern matching when confronted with tasks requiring deep structural unde Apr 21, 2026Chain-of-Steps: How Video Diffusion Models Think Through TimeVideo generation has long been viewed through the lens of pattern matching and statistical interpolation. Yet recent observations suggest these systems possess something more akin to reasoning; the ability to navigate ma