Show HN: Kerns – An AI space to understand anything (www.kerns.ai)

Kerns is a new AI workspace aimed at helping users “understand anything” by turning collections of documents into coherent, navigable knowledge maps. The platform emphasizes multi-source synthesis—merging insights across papers, articles, and books—while providing systematic tools to compare and contrast academic findings and theoretical frameworks. It also offers efficient book-processing workflows to extract key ideas and assemble them into structured overviews, and it codifies a research methodology for deeper topic exploration powered by AI-driven source synthesis. For the AI/ML community, Kerns matters because it tackles the tedious but essential work of literature synthesis and critical comparison. By combining multi-document summarization, structured knowledge mapping (think entity/claim linking and argument mapping), and hierarchical extraction for long-form sources, the tool promises faster, more reproducible literature reviews, hypothesis generation, and cross-disciplinary discovery. Technical implications include improved provenance-aware synthesis (trackable source attribution), scalable book and corpus chunking for retrieval-augmented workflows, and systematic contrastive analyses that surface agreement and disagreement across studies—useful for meta-analyses, research planning, and informed model development.