Agentic AI
LLM‑driven systems that autonomously decompose tasks, call tools, and coordinate with other agents to reach goals.
LLM‑driven systems that autonomously decompose tasks, call tools, and coordinate with other agents to reach goals.
Input crafted to fool a model into misclassification or unsafe behavior without obvious changes to humans.
Technique that lets models weight different parts of input sequences, central to transformers and modern LLMs.
Neural network trained to compress and reconstruct inputs, useful for denoising, anomaly detection, and latent features.
AI system that can plan, act, and iterate toward goals with minimal human input, often chaining tools and memory.
Mechanism that periodically claims and reinvests rewards back into a position to increase APY.
Independent security review of code and architecture to find vulnerabilities before deployment.
Cross‑chain trade that either completes for both parties or reverts for both, often using HTLCs.
Verifiable statement about an identity, event, or state. Used in staking, oracles, and decentralized identity.
Cryptography using public and private keys, enabling signatures and secure key exchange over open networks.
Specialized hardware optimized to compute a specific proof‑of‑work algorithm at very high efficiency.