Memory

Coordinating tools, models, and steps (retrieval, calls, validation) to deliver reliable end-to-end behavior.

Constraining model outputs into a schema used to call external APIs/tools safely and deterministically.

Forcing predictable formats for downstream systems; reduces parsing errors and supports validation/guardrails.

Models that process or generate multiple modalities, enabling vision-language tasks, speech, video understanding, etc.

Methods to protect model/data during inference (e.g., trusted execution environments) from operators/attackers.

System design where humans validate or guide model outputs, especially for high-stakes decisions.

Tendency to trust automated suggestions even when incorrect; mitigated by UI design, training, and checks.

Methods for breaking goals into steps; can be classical (A*, STRIPS) or LLM-driven with tool calls.