secrets detection,security
Find leaked credentials in code or outputs.
9,967 technical terms and definitions
Find leaked credentials in code or outputs.
Communication standard between tools and fab host as mentioned earlier.
Aggregate model updates without revealing individual contributions.
Secure aggregation enables federated learning by computing model updates without revealing individual user data.
Secure aggregation computes collective statistics without revealing individual contributions.
Secure aggregation encrypts gradients in federated learning. Server learns only aggregate. MPC-based.
Hardware-protected inference.
Cryptographic protocols for private computation.
Compute on encrypted data from multiple parties.
Secure multi-party computation allows joint computation without revealing private inputs.
For auth and security basics I can explain API keys, tokens, OAuth flows, and good practices for secret management.
Seebeck effect imaging detects voltage gradients from thermal variations revealing resistive defects and current paths.
Conductive layer for plating.
Initial thin metal layer for subsequent electroplating.
Seeds yield model accounts for systematic and random defects with separate density and clustering parameters.
Process segments recurrently.
Condition on semantic maps.
Segmentation classifies each pixel. Semantic, instance, panoptic. SAM for general segmentation.
Isolate questionable material.
Seldon Core deploys ML on Kubernetes. Enterprise features.
Separate selecting relevant info from making inference.
Checkpoint strategically.
Selective epitaxy grows crystalline semiconductor only on exposed silicon surfaces not on dielectrics.
Epi grows only on exposed silicon not on oxide/nitride.
Preferentially remove one material.
Dynamically adjust receptive field.
Choose which knowledge to transfer.
Selective prediction abstains from answering when confidence is insufficient.
Choose when to abstain from prediction.
Solder specific areas.
Selective SSMs dynamically adjust state transitions based on input content.
Ratio of polish rates between different materials.
Ability to measure target in presence of interferences.
Ratio of etch rates between target material and underlying layer.
Self-consistency samples multiple reasoning paths, takes majority vote answer. Improves accuracy over single sample.
Self-distillation distills model to itself. Different views or augmentations. Regularization effect.
Self-hosting gives control over data and cost at scale. Requires ML ops expertise. Use for sensitive data.
Contacts aligned to spacers and gates.
Self-aligned contacts use spacers and selective etch to automatically align contact openings to gates.
Via aligning itself to metal lines.
Self-alignment improves models using their own generated critiques and revisions.
Model asks and answers sub-questions.
Self-attention ASR uses transformer architecture for speech recognition without recurrent connections.
Combine capsules with attention.
Self-attentive Hawkes processes combine transformer architectures with temporal point process likelihoods for scalable event sequence modeling.
Sample multiple reasoning paths and vote.
Self-consistency samples multiple reasoning paths selecting most consistent final answer.
Generate multiple reasoning paths and pick the most common answer.
Model identifies flaws in its output.
Self-critique prompts models to identify weaknesses in generated responses.