LANGUAGE
Systems for understanding and generating language-based information.
Exploring the technology stack required to build intelligent systems that can perceive, reason, learn and interact with the physical world.
Vilam AI explores the software and computational foundations needed for intelligent machines.
The technology direction connects perception, learning, memory, reasoning, planning and action into an integrated intelligence architecture.
Systems for understanding and generating language-based information.
Visual understanding for objects, environments and visual context.
Combining multiple information modalities into a unified system.
Task-specific intelligence for particular environments and systems.
Intelligent machines need to transform raw sensory information into useful representations of their environment.
Memory and contextual information can help intelligent systems maintain useful state across interactions, tasks and environments.
Intelligent systems eventually need to operate within real limits of compute, memory, latency and energy.
Our technology direction considers efficiency as an important part of practical AI systems, particularly for physical machines.
AI becomes especially interesting when intelligence is connected to a physical system that can sense, decide and interact with the world.
AI systems depend on the infrastructure underneath them — from experimentation and training to inference and deployment.
Vilam AI's technology direction considers the relationship between models, software, compute and the physical systems that run them.
Measure system behaviour under defined conditions.
Understand performance across changing environments.
Observe systems during real-world operation.
Design appropriate boundaries for intelligent systems.
Explore the research, technology and systems behind Vilam AI.