reorder point, supply chain & logistics
Reorder point is the inventory level triggering replenishment orders calculated from lead time demand and desired service level.
536 technical terms and definitions
Reorder point is the inventory level triggering replenishment orders calculated from lead time demand and desired service level.
Augment same image multiple ways in batch.
Repetition penalty reduces probability of recently generated tokens.
Discourage repeated tokens.
Repetition penalty reduces probability of repeated tokens. Frequency and presence penalties in APIs.
Reduce probability of tokens that have already appeared to avoid repetitive text.
Rephrase question before answering for better results.
Training objective in ELECTRA.
Remove dummy gate and deposit metal gate.
Replanning revises strategies when plans fail or conditions change.
Parallel simulations at different temperatures.
Replicate hosts ML models with simple API. Community models. Easy to deploy custom models.
Replit Code is small efficient code model. Good for completion.
Ghostwriter is Replit AI coding assistant. Integrated in Replit IDE.
Create structured reports from data.
Generate reports from data. Analysis and insights.
Analyze entire codebases to understand architecture and dependencies.
Representation surgery edits learned representations removing or adding specific properties.
Compare representations across models.
Find most representative training examples.
Representer points are training examples best explaining test predictions through kernel decomposition.
Ensure experiments can be repeated.
Reproducibility requires fixed seeds, deterministic ops, version pinning. Document everything for replication.
Events requiring requalification.
Validate process after change.
How to group inference requests.
Group multiple requests together for efficient processing.
Request IDs enable tracing across services. Include in logs. Debug production issues.
Request queuing manages incoming requests ensuring fair processing order.
Request scheduling manages inference queue. Priority, fairness, SLA-aware. Optimize throughput and latency.
Cascade requirements to subsystems.
Track and control requirements.
Track Python package versions.
Rerankers refine initial retrieval results. Cross-encoders are more accurate. Two-stage retrieval.
Reranking uses expensive models to refine order of initially retrieved documents.
Reranker scores query-document pairs for relevance. Use after initial retrieval to improve precision. Cross-encoders work well.
Paste a paper or abstract and I will summarize, explain methods and results, and highlight limitations and open questions.
AI helps literature review. Summarize papers, find connections.
Reserved instances/savings plans offer discounts for committed usage. Good for steady-state inference workloads.
Cloud pricing strategies.
Moving semiconductor manufacturing back to home country.
Residual analysis examines model fit by analyzing prediction errors.
Chart prediction errors.
Normalization after residual addition.
Track information flow through residuals.
Residual stress analysis measures stress distributions in packages using techniques like Raman spectroscopy or warpage measurement.
Residual connections add input to layer output. Enable deep networks. Gradient flows through skip connections.
Compound on surfaces.
Predict 3D resist shape after develop.
Amount of energy needed to expose resist.