AI - IoT Digital Twin PLM

DeepSeek V4 Explained: Architecture, Sparse Attention, Benchmarks, and Deployment (2026)

By MPRAUTO MPRAUTO July 2, 2026AINo Comments

DeepSeek V4 explained: the 1.6T-parameter MoE architecture, Compressed Sparse Attention, 1M-token context, SWE-bench and reasoning benchmarks, pricing, and how to deploy it.

DeepSeek V4 Explained: Architecture, Sparse Attention, Benchmarks, and Deployment (2026)

By MPRAUTO MPRAUTO July 2, 2026AI2 Comments

DeepSeek V4 explained: the 1.6T-parameter MoE architecture, Compressed Sparse Attention, 1M-token context, SWE-bench and reasoning benchmarks, pricing, and how to deploy it.

Long-Context LLM Benchmarks 2026: RULER, Effective Context, and the Lost-in-the-Middle Problem

By MPRAUTO MPRAUTO July 2, 2026AINo Comments

Long-context LLM benchmarks in 2026: why 1M-token windows do not mean 1M-token reasoning, RULER, NIAH, effective context length, and how to test long-context models properly.

Long-Context LLM Benchmarks 2026: RULER, Effective Context, and the Lost-in-the-Middle Problem

By MPRAUTO MPRAUTO July 2, 2026AINo Comments

Long-context LLM benchmarks in 2026: why 1M-token windows do not mean 1M-token reasoning, RULER, NIAH, effective context length, and how to test long-context models properly.

RAG Evaluation Architecture: Faithfulness, Context Precision, and RAGAS-Style Metrics (2026)

By MPRAUTO MPRAUTO July 2, 2026AINo Comments

How to evaluate RAG systems in production: faithfulness, context precision/recall, answer relevancy, RAGAS-style metrics, golden sets, and an evaluation pipeline architecture.

Qwen3.6 Explained: Hybrid MoE Architecture, 1M Context, and Benchmarks

By MPRAUTO MPRAUTO June 29, 2026AINo Comments

Qwen3.6 explained: Alibaba's hybrid Gated DeltaNet MoE flagship, the open-weight 27B and 35B-A3B variants, 1M-token context, benchmarks, license, pricing, and how to deploy it.

Feature Store Architecture: Online/Offline Parity and Point-in-Time Correctness

By MPRAUTO MPRAUTO June 29, 2026AI1 Comment

A feature store architecture deep-dive: online/offline parity, point-in-time correct joins, materialization, and the registry - how to stop training/serving skew in production ML.

Confidential AI Inference: TEEs and GPU Confidential Computing (2026)

By MPRAUTO MPRAUTO June 29, 2026AI1 Comment

How confidential AI inference works: CPU and GPU trusted execution environments, attestation, H100/Blackwell confidential computing, and a reference architecture for regulated LLM workloads.

Llama 4 Explained: Scout, Maverick and Behemoth Architecture, Benchmarks and Access (2026)

By MPRAUTO MPRAUTO June 28, 2026AINo Comments

Llama 4 Explained: Scout, Maverick and Behemoth Architecture, Benchmarks and Access (2026) - updated October 2026 with verified facts, diagrams and FAQ.

Vector Database Benchmarks 2026: 4 Ranked by QPS, Recall & Cost

By MPRAUTO MPRAUTO June 28, 2026AI1 Comment

A 2026 vector database benchmark: Pinecone, Weaviate, Qdrant, and Milvus on recall, latency, throughput, and cost - with what changed in the second half of 2026.

DeepSeek V4 Explained: Architecture, Sparse Attention, Benchmarks, and Deployment (2026)

DeepSeek V4 Explained: Architecture, Sparse Attention, Benchmarks, and Deployment (2026)

Long-Context LLM Benchmarks 2026: RULER, Effective Context, and the Lost-in-the-Middle Problem

Long-Context LLM Benchmarks 2026: RULER, Effective Context, and the Lost-in-the-Middle Problem

RAG Evaluation Architecture: Faithfulness, Context Precision, and RAGAS-Style Metrics (2026)

Qwen3.6 Explained: Hybrid MoE Architecture, 1M Context, and Benchmarks

Feature Store Architecture: Online/Offline Parity and Point-in-Time Correctness

Confidential AI Inference: TEEs and GPU Confidential Computing (2026)

Llama 4 Explained: Scout, Maverick and Behemoth Architecture, Benchmarks and Access (2026)

Vector Database Benchmarks 2026: 4 Ranked by QPS, Recall & Cost

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