Where we push the frontier
Our research agenda targets the hard problems between today's capable models and reliable, collaborative agents.
Real-time reasoning in changing environments
Reasoning that stays correct as the world and interface shift underneath the agent.
Situated reasoning grounded in the external world
Decisions anchored to observable state, not just internal priors.
Multimodal and latent visual reasoning
Understanding across text, images, screens, and video - including implicit visual structure.
Persistent memory and self-evaluation
Memory that compounds, paired with the ability to judge and improve its own work.
Human action tokens for machine labor
Representing real software actions as learnable, verifiable units of work.
Agent interoperability (MCP & A2A style)
Ecosystems where agents and tools cooperate through open protocols.
Reliability, observability, and governed autonomy
Measuring, auditing, and bounding agent behavior for trust at scale.
As of June 2026, AI capability is accelerating across coding, computer use, multimodal reasoning, scientific work, and Intelligent Machine Systems (IMS) - but reliability, autonomy boundaries, safety, and evaluation remain active challenges. ELI Labz treats these challenges as the core of the work, not a footnote.