in-place operations, optimization
Modify tensors without copying.
346 technical terms and definitions
Modify tensors without copying.
In-situ doping incorporates dopants during epitaxial growth achieving uniform high-concentration regions.
Add dopants during CVD for controlled doping profile.
Real-time monitoring during processing.
Real-time TEM during processing.
Classes too coupled.
Inbound logistics manages material flow from suppliers to manufacturing facilities.
Evaluate generation quality.
Process for handling outages and problems.
Have incident playbooks for AI failures. Quick rollback capability. Post-incident review to prevent recurrence.
InCoder is Meta code model with infilling capability. Fill in the middle.
Incoming inspection examines materials and components for specification compliance.
Inspect received materials.
Cavity not fully filled.
Not all dopants ionized at low temperature.
Incremental completion streams suggestions as you type. Lower latency feel.
Wearout phase.
Save only changes since last checkpoint.
Add documents without rebuilding.
Separate mixed signals into independent sources.
Build searchable index.
Keep index current with new data.
Malicious instructions hidden in retrieved documents or tool outputs.
Chart for individual measurements.
Efficient attention for sets.
Induction heads copy patterns from context. Key mechanism for in-context learning. Two-layer circuit.
Circuits implementing in-context learning.
Induction heaters use electromagnetic fields generating heat in conductive materials.
Built-in assumptions vs learned patterns.
Inductive crosstalk couples current changes between adjacent lines through mutual inductance affecting signal return paths.
Predict without using test set information.
Learn programs from input-output examples.
Generalize from specific examples.
No target data during training.
Solution-based trace analysis.
Defect caught in early testing.
Early failure period.
Infant mortality is elevated early failure rate from latent defects eliminated by burn-in.
Early failures due to defects.
Computational expense of generating outputs after training.
Inference: Running the trained model to generate outputs. Optimize with quantization, batching, KV-cache. Cost = tokens x compute per token.
Attention with infinite context.
High-bandwidth low-latency network for HPC.
InfiniBand provides low-latency RDMA networking. Essential for distributed training. 200-400 Gbps.
Infinite capacity scheduling assumes unlimited resources identifying bottlenecks and capacity needs.
Neural network behavior as width approaches infinity.
Influence functions estimate impact of training examples on test predictions.
Influence functions identify training examples most influential to recommendations enabling interpretability and debugging.
Measure training example impact on predictions.
Influence propagation models how preferences spread through social networks.