AI - IoT Digital Twin PLM

Filtered Vector Search: Pre-Filtering, Post-Filtering and HNSW Metadata Filters That Do Not Break Recall

By MPRAUTO MPRAUTO October 10, 2026AI2 Comments

Filtered vector search explained: pre- vs post-filtering, HNSW graph connectivity under filters, ACORN, partitioning and selectivity-aware query planning.

Constrained Decoding for LLMs: Grammar-Guided Generation with XGrammar, Outlines and llguidance

By MPRAUTO MPRAUTO October 10, 2026AI1 Comment

Constrained decoding for LLMs explained: token masking, finite-state machines, pushdown grammars, XGrammar, Outlines and llguidance, with overhead.

Synthetic Data for LLM Fine-Tuning: Generation, Quality Filtering and Avoiding Model Collapse

By MPRAUTO MPRAUTO October 9, 2026AINo Comments

Synthetic data for LLM fine-tuning explained: self-instruct, distillation, rejection sampling, quality filters, decontamination and how to avoid model.

Differential Privacy for Machine Learning: DP-SGD, Privacy Budgets and What Epsilon Really Means

By MPRAUTO MPRAUTO October 9, 2026AINo Comments

Differential privacy for machine learning explained: DP-SGD, gradient clipping, noise calibration, privacy accounting, epsilon budgets and the accuracy.

Mem0 vs Letta vs Zep: Agent Memory Frameworks Compared

By MPRAUTO MPRAUTO October 8, 2026AINo Comments

Mem0 vs Letta vs Zep compared: memory architectures for LLM agents, extraction, temporal knowledge graphs, self-editing memory, latency, licensing and.

HNSW vs DiskANN vs IVF-PQ: Vector Index Internals, Quantization and Recall Trade-offs

By MPRAUTO MPRAUTO October 8, 2026AI1 Comment

HNSW vs DiskANN vs IVF-PQ explained: graph and quantization index internals, memory arithmetic, recall vs latency, filtered search, and how to pick an ANN.

Test-Time Compute Scaling: Reasoning Budgets, Best-of-N and Process Reward Models

By MPRAUTO MPRAUTO October 8, 2026AINo Comments

Test-time compute scaling explained: how reasoning budgets, best-of-N sampling, self-consistency and process reward models trade inference cost for.

GGUF vs AWQ vs GPTQ vs FP8: LLM Quantization Formats Compared

By MPRAUTO MPRAUTO October 7, 2026AINo Comments

LLM quantization formats compared: GGUF, AWQ, GPTQ and FP8 covering bit widths, calibration, kernels, accuracy loss, memory arithmetic and which format.

Multi-Head Latent Attention vs GQA vs MQA: KV-Cache Compression Explained