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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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May 9, 2026Beyond Static Snapshots: How TraceScope Resolves the Interaction Gap in Phishing Detection The Failure Mode of Static Analysis The cat and mouse game between security researchers and phishing operators has reached an inflection point where traditional detection pipelines are no longer merely disadvantaged, bu May 9, 2026Exact Attention at Extreme Scale: Combinatorial Decomposition Enables Billion-Token Contexts on Single GPUsLong context windows remain one of the most persistent bottlenecks in large language model deployment. While architectural innovations have pushed context lengths from thousands to millions of tokens, the fundamental con May 9, 2026Rethinking Vision Encoders: How LLM Initialization Challenges the Contrastive Pretraining Paradigm in Compact VLMs Introduction The current generation of Vision Language Models (VLMs) has achieved remarkable capabilities, yet the path toward practical deployment remains obstructed by a fundamental architectural assumption. For years May 9, 2026Scaling Laws Meet Photorealistic Avatars: An Analysis of Large-scale Codec AvatarsThe creation of photorealistic 3D human avatars has long faced a fundamental tension. Systems trained on high-fidelity multi-view studio data deliver exceptional quality and precise anatomical control, yet they struggle May 9, 2026 May 9, 2026Joint Environment Prediction for Temporally Consistent Video RelightingVideo relighting sits at the intersection of computer vision and graphics, demanding both semantic understanding of scene geometry and photorealistic synthesis capabilities. Traditional approaches rely on explicit intrin May 9, 2026Specification as the New Code: Lessons from the Kitchen LoopThe emergence of large language model coding assistants has precipitated a curious crisis in software engineering. Despite tools that generate functional code at unprecedented velocity, empirical studies reveal a troubli May 9, 2026The Expressive Geometry of Local Attention: Why Restricting Context Can Expand Capability The Efficiency Paradox in Transformer Design The transformer architecture has become the dominant substrate for modern language modeling, yet one of its most puzzling variants continues to challenge our intuitions about May 9, 2026Addressing the Data Desert: A Technical Analysis of the AfriVoices-KE Speech CorpusThe development of robust automatic speech recognition (ASR) and text-to-speech (TTS) systems relies fundamentally on the availability of large-scale, phonetically diverse audio datasets. For the majority of the world’s May 8, 2026The Enumeration Gap: Why Counting in Long Videos Remains Unsolved Introduction Counting is among the earliest mathematical skills humans acquire, yet it remains an unsolved frontier for multimodal AI. While a child can reliably tally occurrences of an event across a thirty minute vide May 8, 2026Beyond the Mean: Why Spatial Structure Matters in Segmentation Uncertainty Quantification Introduction Uncertainty Quantification (UQ) in image segmentation has become a cornerstone of trustworthy machine learning, particularly in safety-critical domains such as biomedical imaging and autonomous driving. Mod May 8, 2026Beyond Frame-Level Detection: Contextual Reasoning for Capsule Endoscopy Video AnalysisCurrent artificial intelligence research in capsule endoscopy has reached an impasse. While convolutional neural networks and vision transformers now achieve impressive accuracy on curated image datasets, these benchmark May 8, 2026The Emergence of Political Rhetoric in LLM Collectives: An Analysis of Elected Leadership and Common Pool Resource ManagementThe tragedy of the commons remains one of the most persistent challenges in both human societies and artificial multi-agent systems. When multiple actors share a subtractable resource without clear extraction limits, rat May 8, 2026Amortized Cognition: Real-Time Reasoning in Streaming Video Language ModelsThe deployment of Video Large Language Models in interactive, real-time environments presents a fundamental architectural tension. On one hand, the complexity of temporal reasoning across visual streams demands deliberat May 8, 2026Rethinking Sample Efficiency in Android Agent Training: The Single State Multiple Actions ParadigmTraining autonomous GUI agents for Android devices through online reinforcement learning has long faced a fundamental economic constraint. The latency of Android emulators creates a severe bottleneck where environmental May 8, 2026HyCOP and the Return of Modular Structure in Neural OperatorsScientific machine learning has reached an inflection point. While monolithic neural operators like Fourier Neural Operators and DeepONets have demonstrated impressive interpolation capabilities within training distribut May 8, 2026The Compositional Boundary: Why LLMs Fail to Scale Sequential ReasoningThe question of whether large language models can achieve systematic generalization remains one of the most contested issues in artificial intelligence research. While these models demonstrate impressive performance on r May 8, 2026Evolution-Guided Policy Gradient in Reinforcement Learning: A Hybrid Architecture for Robust Continuous ControlDeep Reinforcement Learning has achieved remarkable success in game playing and robotic control, yet its deployment in real-world scenarios remains hindered by fundamental algorithmic fragilities. The paper Evolution-Gui