Researching
the Hard Problems
in AI.
Vilam AI explores artificial intelligence, machine intelligence and embodied AI with a focus on systems capable of understanding, learning and acting in complex real-world environments.
Build understanding, not just bigger models.
We are interested in the fundamental problems that stand between today's AI systems and genuinely capable intelligent machines.
Our research direction spans perception, reasoning, learning, world models, multimodal intelligence, efficient computation and embodied AI.
Exploring the intelligence stack.
Systems that perceive, reason, learn and make decisions.
01Connecting artificial intelligence with physical machines.
02Representing environments, objects, relationships and changing states.
03Planning, decision-making and reasoning under uncertainty.
04Exploring capable intelligence with practical computational efficiency.
05Combining visual, language, audio, spatial and other information.
06Towards machines that can understand.
Our research considers intelligence as a combination of perception, representation, reasoning, learning, memory and action.
AI that doesn't stop at the screen.
Embodied AI brings intelligence into machines that sense their environment, interact with objects and operate within physical space.
A machine needs a model of the world.
We are interested in systems that can build useful internal representations of environments, objects, relationships and changing situations.
Better representations can enable more capable reasoning, prediction, planning and interaction.
Can a machine reason about what happens next?
More intelligence. Less waste.
Advanced intelligence must eventually operate under real constraints — compute, memory, energy, latency and physical hardware.
Vilam AI's research direction therefore includes efficient models, efficient inference and intelligence designed for real-world machines.
Intelligence should improve with experience.
We explore learning systems that can adapt to changing environments and use feedback to improve their future behaviour.
Intelligence should connect different worlds.
Turning intelligence into behaviour.
Our AI research is intended to support intelligent machines developed within the broader Vilam robotics ecosystem.
A research stack for intelligent machines.
Research should eventually move.
The path from research to intelligent machines requires experimentation, engineering, evaluation and continuous iteration.
Toward a future of machine intelligence.
We are exploring the foundations required for machines that can perceive their surroundings, build useful models of the world, reason about complex situations, learn through experience and act intelligently in the physical world.
The difficult problems are the ones worth solving.
Explore our research direction or connect with the team at Vilam AI.