Asynchronous
288 autonomous F18A nodes (2 x GA144) execute concurrent workloads sans central clock bottleneck.
Why Volatco
Volatco avoids opaque cloud lock-in and fragile abstraction layers. It keeps computation close to hardware and human reasoning.
Ultra-low energy
Built for always-on systems, resilient edge devices, and power-constrained deployments.
100-year ethic
Generationally understandable computing hardware designed to resist planned obsolescence.
Research Spotlight
Agentic AI: Embodied Learning Model
The ideal research path frames agency through embodied interaction, not passive observation. In this view, an agent does not treat inputs as direct world representation; it runs experiments, receives results, and updates behavior from those interactions.
The foundational module describes a cycle of anticipation, result comparison, and intrinsic states such as frustrated, self-satisfied, and bored, which drives experiment-switching and developmental learning over time.
This is the direction behind Apeiron, a learning-first architecture in which identity, planning, and control stay adaptive because they are continuously revised by experience instead of being fixed once at deployment.
Apeiron is the next stage of hardware-software hybridization, allowing the user to focus directly on the problem instead of first asking whether a programming language can support the idea.
See the source pathway and branches: github.com/cartheur/ideal.