Blog

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.

Page 14 of 59

May 14, 2026Automated Detection of Scientific Methodology Bugs: Analyzing the Promise and Peril of LLM-Generated LintingModern scientific research rests upon a foundation of code that is increasingly complex, frequently untested, and often authored by researchers for whom software engineering remains a secondary skill. While syntax errors May 14, 2026UniversalVTG: Rethinking Scale and Unification in Video Temporal GroundingVideo temporal grounding, the task of localizing specific moments in untrimmed video based on natural language queries, has emerged as a critical capability for applications ranging from episodic memory retrieval in augm May 14, 2026Aligning Validation with Reality: Why Standard Cross-Validation Fails in Spatial Prediction and How to Fix ItWhen environmental scientists map pollution levels or predict species distributions, they face a persistent methodological tension. The data they collect comes from monitoring stations positioned by logistical constraint May 13, 2026The Fragility of Procedural Execution in Large Language ModelsCurrent discourse around large language models often centers on their reasoning capabilities. Recent advances in test-time compute and reinforcement learning have produced models that generate extensive chains of thought May 13, 2026ADAPT: Using Attention Signals to Solve the Rare Concept Generation Problem The Challenge of Semantic Composition in Diffusion Models Text-to-image diffusion models have achieved remarkable fidelity in generating common visual concepts, yet they consistently fail when asked to compose rare or u May 13, 2026Co-Evolution as the Stable Equilibrium: Unifying Generation and Detection in Visual AIThe arms race between synthetic image generation and forensic detection has long resembled an asymmetric conflict. On one side, generative models evolve continuously, leveraging diffusion transformers and autoregressive May 13, 2026Universal YOCO and the Decoupling of Depth from Memory in Transformer ScalingThe pursuit of more capable reasoning in Large Language Models has increasingly focused on test-time scaling; the practice of expanding computational investment during inference rather than simply growing model parameter May 13, 2026The Fragile Router: Re-examining Verifiability in Mixture of Expert TreesThe deployment of deep reinforcement learning agents in safety critical domains such as autonomous driving or medical intervention remains contentious precisely because these systems resist formal analysis. While neural May 13, 2026Recursive Agent Optimization: Training Models to DelegateThe limits of monolithic reasoning are becoming apparent as large language model agents tackle increasingly complex tasks. Current systems struggle with long horizon planning, context window constraints, and the combinat May 13, 2026Parametric RAG: Realigning External Knowledge with LLM Memory ArchitectureRetrieval augmented generation has become the standard mechanism for grounding large language models in external knowledge. The prevailing approach, which appends retrieved documents directly to the model's input prompt, May 13, 2026The Approximation Trade-off: Analyzing Knowledge Distillation in Resolution-Agnostic Vision TransformersVision Transformers have become the default backbone for modern computer vision, yet they harbor a persistent limitation that becomes acute in dense prediction scenarios. Pretrained at fixed resolutions due to the quadra May 13, 2026The Quantum Asymmetry: Hybrid QC-GANs and the Impending Crisis in Network DefenseThe arms race between intrusion detection systems and adversarial machine learning has entered a new phase. While classical generative adversarial networks have already demonstrated the capacity to evade machine learning May 13, 2026The Resurgence of Local Feature Matching: Why Data Scale, Not Architecture, Explains the Detector-Free Revolution Introduction For the past several years, the computer vision community has operated under a particular narrative regarding image matching: detector-based local feature methods were becoming obsolete, rendered unnecessar May 13, 2026Quotient-Space Diffusion: Learning on the Intrinsic ManifoldDiffusion models have established themselves as the dominant paradigm for generative modeling across diverse modalities, from natural images to molecular structures. In scientific applications, particularly molecular str May 13, 2026The Hierarchical VLA Trap: Why Visual Grounding Becomes the Single Point of FailureThe race to deploy capable robotic manipulation systems has increasingly converged on Vision Language Action (VLA) models as the architecture of choice. These systems promise to unify perception, reasoning, and control w May 12, 2026Temporal Coherence as Physics: Rethinking the Synthetic-to-Real Gap in Generative RenderingThe promise of inverse rendering has always been compelling: deconstruct a photograph into its constituent physical properties, then reconstruct reality at will. Yet despite rapid advances in diffusion models and neural May 12, 2026Bridging Neural Rendering and Analytic Geometry for Robust Autonomous NavigationAutonomous unmanned aerial vehicle navigation through complex outdoor environments demands the ability to synthesize photorealistic views from arbitrary camera poses, particularly when the UAV deviates from its original May 12, 2026The Silent Failures of Computational Physics: Why Solver Convergence Is Not EnoughRecent advances in large language model agents have automated substantial portions of the scientific discovery loop in software-centric domains such as machine learning research, chemistry, and biology. Yet the extension