Qubic crosses five major technological stages: from ternary AI to embodied intelligence

During its latest “All Hands” meeting, Qubic announced significant progress in developing artificial intelligence capable of interacting with the physical world. Moving beyond theoretical promises, the project now demonstrates concrete reinforcement learning capabilities and the deployment of innovative neural architectures. These advancements mark a turning point in the network’s trajectory.

Neuraxon Takes Physical Form: When AI Becomes Robotics

The first achievement concerns the physical manifestation of Neuraxon intelligence. Qubic successfully integrated its AI system into a robotic sphere capable of accurately tracing letters on the ground. This transition from digital to physical domain is more than a technical demonstration: it validates reinforcement learning algorithms in a tangible context.

Jose, a researcher on the scientific team, emphasizes the importance of this step: “It’s exciting to see the sphere write with precision… our main letters Qubic.” This ability to convert digital neural processes into mechanical movements opens the door to more ambitious robotic applications.

Explosion of Training Data: Exponential Progress Toward AGI

To reach Artificial General Intelligence (AGI), the complexity of datasets is a decisive factor. Qubic has crossed a critical threshold by developing a 1-terabyte dataset, 100 times larger than the previous generation.

This increase is not limited to raw storage. It is accompanied by a major structural evolution:

• Increased Neural Density: Each simulation now starts with 1,000 neurons, compared to only 100 before, multiplying learning complexity by ten.
• AIGARTH Concept: The system simulates clusters of neurons where only the top 12 “agents” (those that survive and find food) pass their architecture to subsequent generations. This genetic mechanism accelerates model evolution.
• Multi-Neuraxon Architecture: This dataset prepares for the deployment of the “multi-neuraxon” model planned for Q2 2026, aiming to create a true network of interconnected neural networks.

Ternary Approach Validated by Academia: Surpassing Classic Binary

The technological revolution led by Qubic lies in its adoption of a biology-inspired ternary logic. Unlike the dominant binary architecture, this three-state system offers unprecedented structural stability and higher energy efficiency.

A scientific paper on ternary AI has been accepted for the prestigious ALife conference in Japan. Other submissions to ICML in South Korea and a conference in Germany extend the project’s academic recognition. Jose explains the stakes: “This ternary approach can help a network save energy and gain structural stability.”

Remarkably, visual language models (VLMs) are also adopting ternary architectures, placing Qubic at the forefront of an emerging industry trend. The project not only innovates but anticipates major sector evolutions.

Dogecoin Integration: From Proof of Concept to Native Infrastructure

April 1, 2026, will mark a decisive turning point. Qubic will natively integrate Dogecoin (DOGE) mining directly into its Oracle infrastructure. This transition goes beyond a simple proof of concept: it consolidates the project’s technical ecosystem.

While previous integration of Monero (XMR) mining operated in parallel with the network, Dogecoin will benefit from a native implementation leveraging the Oracle machine’s resources directly. The transition will take about a month, during which both assets will be mined simultaneously.

In the long term, CPU resource optimization will enable directing 100% of the power toward joint QUBIC-Dogecoin mining, utilizing idle machine cycles to maximize profitability.

An Accelerating Technical Ecosystem

These five advancements illustrate the progressive maturation of the Qubic network. From embodied intelligence to ternary architectures, from moving toward AGI to integrating native mining infrastructures, the project consolidates its position as a major technological player in the on-chain AI space.