Data & Analytics Articles
Browse 157 articles about Data & Analytics.
AI Agent Evaluation: How to Build Custom Benchmarks That Actually Test Intelligence
Public benchmarks are often contaminated by training data. Learn how to build custom AI agent benchmarks using simulation environments and iterative testing.
How to Use AI Agents for Data Migration: Lessons from Real-World Testing
AI agents can handle messy business data migrations—but they need the right guardrails. Learn what works, what fails, and how to validate outputs safely.
ARC AGI 2 vs Pencil Puzzle Bench: The Benchmarks That Expose AI Capability Gaps
These two benchmarks test reasoning you can't fake with training data. See how GPT-5.2, Claude, Gemini, and Chinese models actually compare.
What Is Benchmark Gaming in AI? Why Self-Reported Scores Are Often Inflated
Kimi K2 reported 50% on HLE but independent testing found 29.4%. Learn how benchmark gaming works and how to evaluate AI models honestly.
What Is the China AI Gap? Why Chinese Models Lag on Benchmarks That Can't Be Gamed
ARC AGI 2 and Pencil Puzzle Bench reveal Chinese frontier models score like Western models from 8 months ago. Here's what the data shows.
What Is the Frontier Math Benchmark? Why Open Research Problems Expose True AI Reasoning
Frontier Math uses unpublished problems that take researchers days to solve. Models with full Python access still score under 3%. Here's why it matters.
What Is the Humanities Last Exam Benchmark? How Independent Testing Revealed a 21-Point Score Inflation
Kimi K2 self-reported 50% on HLE. Independent testing found 29.4%. Here's how the HLE benchmark works and why third-party verification matters.
What Is the Pencil Puzzle Benchmark? The Test That Measures Pure Multi-Step Logical Reasoning
Pencil Puzzle Bench tests constraint satisfaction problems with no training data contamination. GPT-5.2 scores 56%. Chinese models score under 7%.
What Is the SWE-Rebench Benchmark? How Decontaminated Tests Expose Chinese Model Inflation
SWE-Rebench uses fresh GitHub tasks that models haven't seen in training. Chinese models that match Western scores on SWE-bench drop significantly here.
Why Cursor, Claude Code, and Devin Use grep, Not Vectors
Cursor, Claude Code, and Devin lean on grep, find, and direct file reads — not vector search. Why agentic coding tools dropped RAG and where it still wins.
What Is LiteParse? LlamaIndex's Open-Source Document Parser for AI Agents
LiteParse is a free, GPU-free document parser from LlamaIndex that preserves spatial layout for tables and charts. Here's why it matters for AI workflows.
What Is the Remote Labor Index? Why AI Agents Complete Only 2.5% of Real Freelance Work
Scale AI's Remote Labor Index tested frontier agents on 240 Upwork projects. The 97.5% failure rate reveals the gap between task execution and real jobs.
AI Job Market Impact: What the Data Actually Shows About White-Collar Employment
White-collar job openings hit a 10-year low. Here's what the Anthropic AI Exposure Index, Gartner forecasts, and real layoff data reveal.
What Is the Anthropic AI Exposure Index? How to Find Out If Your Job Is at Risk
Anthropic's AI Exposure Index maps 800+ occupations against real Claude usage data. Here's how to read it and what it means for your career.
How to Use Gemini Deep Research for Competitive Intelligence and Market Reports
Gemini's deep research feature outperforms ChatGPT and Claude for multi-source reports. Here's how to use it for competitive analysis and market research.
Gemini Embedding 2 and the End of Stitched-Together Embeddings
Why Gemini Embedding 2 matters: a primer on embeddings and how a unified vector space replaces the brittle stitching of separate text, image, and audio models.
Gemini Embedding 2 vs Qwen3 VL Embeddings: Which Multimodal Model Should You Use?
Compare Gemini Embedding 2 and Qwen3 VL embeddings across supported modalities, embedding dimensions, API access, and real-world search use cases.
What Is Matryoshka Representation Learning in Gemini Embedding 2?
Gemini Embedding 2 supports flexible embedding sizes from 3,072 down to 768 dimensions. Learn how Matryoshka learning works and when to use smaller embeddings.
How to Search Video Content with Gemini Embedding 2: Chunking Strategies Explained
Embed video clips in 15-30 second chunks using Gemini Embedding 2 to enable text-based search over long-form video content without transcription.
How to Build a Unified Multimodal Search System with Gemini Embedding 2 and LangChain
Use Gemini Embedding 2 with LangChain and ChromaDB to build a single search index that handles text, images, audio, video, and PDFs in one query.