Bug Bounty Payout Map: What Google, Hyper-V, Meta TEE, Apple and Mozilla Pay For
Read payouts with their product, category, threat scenario and evidence requirements; program ceilings and quality rules are not interchangeable.
#comparison
6 postsCommercial Landscape: OpenAI, Perplexity, Gemini, Claude, Grok
By 2026, the deep research commercial market has differentiated: OpenAI is comprehensive, Perplexity is fast, Gemini integrates ecosystems, Claude reasons deeply, Grok is real-time. This article compares each product's differences—not who is best, but who fits your scenario.
【Ecosystem】How the Community Builds Deep Research Skills
10+ community deep-research skills represent 10+ philosophies of 'how to do research.' From hyperresearch's persistent vault to jamoeight v2's Co-Scientist 6-agent, from adversarial verification to benchmark alignment. This article puts them all on one table.
Open-Source Tools Overview: GPT-Researcher, STORM, smolagents...
The deep research open-source ecosystem has evolved from 'single frameworks' to 'tool clusters.' This article compares 12+ projects: GPT-Researcher emphasizes multi-agent collaboration, STORM simulates expert conversations, smolagents focuses on state management. Each tool solves different problems.
AI Agent Cloud Sandbox Product Landscape & Selection Matrix
The cloud landscape post (order 7) of the Sandbox Series. Summarizes positioning, pricing, cold start, isolation strength, and applicable scenarios for E2B, Daytona, Runloop, Vercel, Cloudflare, Modal, AWS Bedrock AgentCore, Alibaba OpenSandbox, Azure Container Apps — with a selection decision matrix.
RAG vs Fine-tuning: It's Not Either/Or
RAG and Fine-tuning solve different problems. RAG gives the model new knowledge; Fine-tuning changes the model's behavior and style. In most cases you use both, not pick one.