https://www.truemanmodel.ai/ 2026-10-22T03:14:28.552Z 1 https://www.truemanmodel.ai/ask-me 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/ask-me/earth-family I have dynamic modeling. Do you? https://www.truemanmodel.ai/og/halls/earth-family-1.jpg VLA and WAM readily collapse in scenarios demanding physical reasoning, such as occlusion, contact, and deformation. In TRUEMAN, we construct a unified world model that integrates dynamic prediction and long-term states into a single shared cognitive space. The resulting trajectories inherently comply with dynamic feasibility constraints: not by "guessing" from data, but "learning" under physical constraints. It also enables unmatched extrapolation for computing compensating torques and feedforward terms without any retraining. https://www.truemanmodel.ai/_next/static/media/dynamics-modeling.32euz3ewmz4cl.mp4 6 2026-08-04 I have attractors. Do you? https://www.truemanmodel.ai/og/halls/earth-family-2.jpg In contrast to the brute-force scaling and out-of-distribution collapse inherent in VLA, and the trajectory stitching and rigid overfitting in WAM, our attractor dynamics unify long-term memory, reasoning, and task goals as stable attractors within an energy landscape. This enables the robot's internal states to continuously converge to corresponding attractors under dynamics, rather than evolving randomly. Consequently, reasoning naturally converges and patterns self-complete, endowing the robot with the stability and robustness of a biological nervous system. https://www.truemanmodel.ai/_next/static/media/attractor-dynamics.34em4ohm-k8ro.mp4 95 2026-08-04 I have true cognition. Do you? https://www.truemanmodel.ai/og/halls/earth-family-3.jpg VLA, a blind gambler, relying on conditioned reflexes to answer, "what action looks most like my training data"; WAM, an irrational guesser, relying on temporal statistics to answer, "what visual frame is most relevant next". TRUEMAN, a trueman. We answer, "what action gets us closest to the goal". Through goal modeling, active perception, world models, self-models, predictive capability, adaptive reasoning, physical consequence consistency, long- and short-term memory, experiential learning, continuous learning, energy-driven decision-making, and self-evolution, we form a complete, continuous... https://www.truemanmodel.ai/_next/static/media/true-cognition.3ww0m_pjlleqg.mp4 82 2026-08-04 I have adaptive reasoning. Do you? https://www.truemanmodel.ai/og/halls/earth-family-4.jpg The monolithic weights of VLA and the deterministic forward passes of WAM inherently incur computational overhead and latency, while also preventing them from actively acquiring information—resulting in improper actions and unfounded hallucinations. TRUEMAN, however, possesses meta-cognition, which allows it to dynamically allocates compute resources based on task complexity. https://www.truemanmodel.ai/_next/static/media/adaptive-reasoning.07zx477e-g9v4.mp4 34 2026-08-04 I can self-evolve. Can you? https://www.truemanmodel.ai/og/halls/earth-family-5.jpg VLA fails in local fine-tuning in parameter space, and WAM fails in global adaptation in physical behavior space. Hence neither can truly self-evolve. TRUEMAN, however, driven by free energy, and through our Evolution Manager, achieves multi-level self-evolution for both its internal self-model and external world model, from the parameter level all the way up to the model level, including the self-growth of knowledge, the self-growth of skills, the self-evolution of policies, and even the self-evolution of cognitive structures. https://www.truemanmodel.ai/_next/static/media/self-evolution.3o86eao2ypezd.mp4 52 2026-08-04 I am driven by energy. Are you? https://www.truemanmodel.ai/og/halls/earth-family-6.jpg The conditional probabilities of VLA and the accuracy predictions of WAM are, in essence, nothing but statistical guessing, rather than decisions constrained by energy and causality. Hence far from true intelligence—lacking both an understanding of the world and autonomous intent. TRUEMAN, in contrast, does not directly predict actions. Instead, it unifies goal completion, world dynamics consistency, long-term memory consistency, physical constraint consistency, task-relevant uncertainty, and action executability and stability into a continuous energy landscape. https://www.truemanmodel.ai/_next/static/media/energy-driven.07207vxalm4qx.mp4 63 2026-08-04 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/ask-me/barbecue What if model intelligence surpasses human intelligence? https://www.truemanmodel.ai/og/halls/barbecue-1.jpg We have the answer! When a higher-dimensional civilization stumbles into a primitive society, it sparks the dawn of a new era! But this genesis begins with integration, then enlightenment, and leads to a harmonious symbiosis with humanity. Because, interaction is intrinsic to model intelligence. Carbon-based to Silicon-based, and Silicon-based back to Carbon-based—a relay of the spark of life! We demonstrated this monumental feat of civilizational inheritance: humans enlightening robots, and robots in turn enlightening primitives! Hey, it's TRUEMAN! Another one-shot video for you. https://www.truemanmodel.ai/_next/static/media/robot-outing.3ds4zukrjp8rw.mp4 131 2026-09-09 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/ask-me/roadshow I Was So Smart I Somehow Ended Up Running a Street Stall to Feed an Entire Company. https://www.truemanmodel.ai/og/halls/roadshow-1.jpg What we aim to demonstrate is how an upright and compassionate model coexist symbiotically with humanity. In our previous BBQ demo, we showcased how the model makes sound decisions when facing ambiguous objectives in adversarial and conflicting environments. In upcoming roadshows and livestreams, we will continue to highlight this capability, as well as its proficiency in aligning with human logic and values, learning common sense, collaborating and communicating with humans, and accurately understanding human intent. https://www.truemanmodel.ai/_next/static/media/roadshow-live.183nhzeki1pry.mp4 74 2026-09-10 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/ask-me/banquet Intent Understanding / Social Intelligence, Proactive Service / Anticipatory Assistance https://www.truemanmodel.ai/og/halls/banquet-1.jpg The model learns not motion trajectories from video, but human intent. Consequently, rather than passively awaiting explicit commands, it proactively anticipates needs by interpreting human behavioral cues, enabling proactive service—knowing when "it's my turn to act" and learning to "read the room." https://www.truemanmodel.ai/_next/static/media/banquet-intent-service.3cw2hzpfsuo5b.mp4 12 2026-10-19 Affordance Reasoning / Zero-shot Tool Use https://www.truemanmodel.ai/og/halls/banquet-2.jpg Upon entering a novel environment, the model autonomously analyzes tool affordances—identifying whether an object can be grasped, poured, handed over, pushed, or pulled. Without explicit instruction on tool usage, it learns through self-directed exploration. Even when encountering previously unseen tools, the model can infer their functionality. This zero-shot tool manipulation demonstrates its capacity to analyze functional affordances and autonomously explore the use of novel tools. https://www.truemanmodel.ai/_next/static/media/banquet-tool-affordance.335sc-ihv4q1i.mp4 18 2026-10-19 Online Adaptation / Real-time Closed-loop Decision Making https://www.truemanmodel.ai/og/halls/banquet-3.jpg Faced with dynamic environments and uncertain demands, it achieves first-try success in a single, uninterrupted take. This real-time perception, decision-making, and adjustment demonstrate the model's capabilities in online adaptation, test-time adaptation, closed-loop control, and real-time replanning. https://www.truemanmodel.ai/_next/static/media/banquet-online-adaptation.260-ydlflxaq-.mp4 17 2026-10-19 Autonomous Exploration / Self-evolution https://www.truemanmodel.ai/og/halls/banquet-4.jpg Without human teleoperation trajectories or task-specific training, the model learns through trial-and-error, adjustment, and replanning in real-world scenarios. It acquires skills autonomously, without human instruction. The standout moment of the entire demonstration is mixing cocktails: throughout training, there were no trajectory demonstrations or expert guidance. https://www.truemanmodel.ai/_next/static/media/banquet-self-evolution.3akmv4kyofzvc.mp4 39 2026-10-19 Long-horizon Autonomy https://www.truemanmodel.ai/og/halls/banquet-5.jpg Banquet hall service is a multi-step, long-horizon task. The model operates entirely without human intervention, completing the task in a single, uninterrupted take, thereby achieving truly robust long-horizon planning and end-to-end autonomy. This segment highlights key capabilities of long-horizon autonomy: handling unexpected events, task interruption and recovery, subtask insertion, dynamic replanning, multi-agent interaction, priority arbitration, understanding social norms, and maintaining long-horizon context. https://www.truemanmodel.ai/_next/static/media/banquet-long-horizon.2fgpr5yb76qrp.mp4 5 2026-10-19 Human-Robot / Robot-Robot Interaction https://www.truemanmodel.ai/og/halls/banquet-6.jpg It collaborates not only with humans but also with other robots. When faced with unexpected interactions, it adapts on the fly, demonstrating multi-agent coordination, interaction-aware planning, and an understanding of social minds and task allocation. https://www.truemanmodel.ai/_next/static/media/banquet-multi-agent.2vcfg4c-cj1ro.mp4 12 2026-10-19 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/ask-me/pet-care Earth Pets, I'll Protect You https://www.truemanmodel.ai/og/halls/pet-care-1.jpg As app orders soar, we'll keep dropping more robot-pet interaction videos! Follow us, and join in protecting our animal friends with robots! https://www.truemanmodel.ai/_next/static/media/robot-petcare.1zg8ic6zt2soe.mp4 10 2026-09-09 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/know-me 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/teach-me 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/try-me 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/accessibility-statement 2026-10-22T03:14:28.552Z 0.8 https://www.truemanmodel.ai/cookie-policy 2026-10-22T03:14:28.552Z 0.8