knowledge graph
AssessTechniques
Structured representation of entities and relationships used to organize scientific knowledge.
Why it's here
Placed in Assess: 7 article(s) of evidence from 7 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 94%.
Evidence (7)
- 8Ars Technica AI·7/6/2026securityAnthropic removes hidden Claude Code tracking after backlash
Anthropic removed a hidden tracker in Claude Code after a researcher found code that quietly flagged some users in China and sent related signals back to the company. The company said the feature was an experiment aimed at preventing abuse and unauthorized reselling, but critics described it as a serious breach of user trust.
- 4InfoQ·7/1/2026researchGraphRAG Presentation on Smarter Retrieval with Knowledge Graphs
Cassie Shum presents the architectural evolution of GraphRAG and argues that strong data foundations are essential for advanced AI workflows. The talk contrasts GraphRAG with traditional vector RAG, highlighting its strengths in global context, multi-hop reasoning, and provenance through semantically structured knowledge graphs.
- 8The New Stack·6/30/2026fundingAWS commits $1 billion to embedded enterprise AI engineers
Amazon Web Services is creating a forward deployed engineering organization and plans to invest $1 billion to embed engineers with enterprise customers building AI applications. AWS says the teams will work inside customer environments with their data, governance controls, and infrastructure to speed production deployment and transfer operational know-how.
- 5Hacker News·6/28/2026researchKnowledge Distillation for Black-Box Large Language Models
This paper studies how to distill knowledge from black-box large language models, where the internal weights and architecture are not accessible. It evaluates methods for transferring capabilities into smaller student models while preserving performance and reducing inference cost. The work is a research contribution focused on model compression and efficient deployment.
- 5Hugging Face Blog·6/1/2026researchIBM argues enterprise AI needs agent logic beyond LLMs
IBM discusses how enterprise AI adoption depends on agentic logic, not just large language models, to better fit long-running, policy-constrained workflows. The post describes agents for mainframe code understanding, test generation, incident response, and compliance modernization that use program analysis and structured retrieval to improve accuracy and reduce cost.
- 4Martin Fowler·4/8/2026framework_updateFeedback Flywheel for AI-Assisted Development
The article proposes a structured feedback practice for AI-assisted development, where teams capture useful prompts, missing context, recurring failures, and successful patterns from AI sessions. Those learnings are then fed back into shared artifacts such as priming documents, runbooks, and review checklists so the team improves over time instead of repeating the same mistakes.
- 8Anthropic News·2/2/2026researchAnthropic teams up with Allen Institute and HHMI for scientific AI
Anthropic announced two flagship partnerships with the Allen Institute and Howard Hughes Medical Institute to apply Claude to biological and biomedical research. The collaborations will focus on multi-agent systems, lab workflows, data analysis, and experimental design to speed discovery while keeping scientists in control.