Artly AGI has undergone years of development, testing, and refinement to deliver the precise, high-performance results it does today. Its history is rooted in more than a decade of R&D in computer vision, deep learning, and robotics—including foundational work at Orbeus Inc. (acquired by Amazon), followed by advancements at AWS AI and Amazon Robotics. Through multiple iterations, Artly AGI has led to a paradigm shift from increasingly outdated manual programming to dynamic learning. This learning approach relies on demos across various media—vision, voice, text, and motion—to teach our robots.
But imitation learning isn’t the only force behind Artly's robots. Artly AGI also leverages various multimodal models such as LLMs (Large Language Models) and VLMs (Vision Language Models) in the robots' perception-planning-control loop. At the core of the platform lies a modular OS kernel that breaks down larger task sequences, such as preparing a latte, into smaller skills like picking, pouring, or chopping. These tasks are rigorously tested, stored in a cloud-based AGI Hub, shared across different robots when needed, and reused efficiently.
Apart from inducing flexible reasoning and multimodal understanding in the robots, these models also test them with temporal and spatial constraints to ensure their performance is adaptable. As a result, our bots can carry out nuanced, meticulous tasks that are often deemed too complex or risky to automate.
To ensure safety, Artly AGI relies on simulation during the training phase. Situational variables such as force interactions, slippage, and environmental variation are replicated to test the robots' response. This prepares them for potential real-world failures and improves their resilience.
The final step in deploying these task sequences is Artly Studio, the web-facing interface of Artly. Artly Studio provides users with a user-friendly, human-centered, no-code environment where they can safely access and deploy any task.
All in all, Artly AGI is building a new generation of robust, reliable robots that are ready for diverse scenarios. Through advanced risk mitigation strategies and diversity-based testing frameworks, our robots ensure safety, adaptability, and performance, hitting a milestone in human-centered automation.
