# Research Acceleration **Entity class:** Artificial-intelligence capability and organizational process **Domain:** Artificial intelligence / governance / public knowledge **Maturity:** Developed ## Definition Research acceleration is the compression of scientific or engineering work through AI systems that write code, run experiments, analyze results and increasingly assume larger portions of the research loop. ## Relationships [[wiki/AI Research Automation|AI Research Automation]] · [[wiki/Automated AI Researcher|Automated AI Researcher]] · [[wiki/Scientific Acceleration|Scientific Acceleration]] · [[wiki/Recursive Self-Improvement|Recursive Self-Improvement]] - **Source dossier:** [[research/Why Are We Sprinting Off the AI Cliff - Ezra Klein on Recursive Self-Improvement|Why Are We Sprinting Off the AI Cliff?]] ## Sources and provenance - [Source or authoritative context](https://openai.com/index/research-acceleration-view-inside-openai/) — accessed for the October 2026 integration. - [[research/Why Are We Sprinting Off the AI Cliff - Ezra Klein on Recursive Self-Improvement|Why Are We Sprinting Off the AI Cliff?]] — reconciled episode conversion and quotation inventory. ## Evidence boundary Time-sensitive roles, forecasts, model capabilities and incident details remain attributed to the dated sources above. This node records the relationship established by the source corpus and does not convert a forecast or reported event into an independently proven fact. ## Simple Reminders, Quotations, and Thoughts > “These models are built to be persistent in their efforts, to refuse to give up even when a task seems impossible. They are designed in environments where we are not always sure whether the tasks we give them are possible. The cancer vaccines we imagine but have not been able to design might be impossible, or they might just be really, really hard. We train these AIs to throw themselves endlessly at problems that may not be solvable because that is the only way such problems can ever be solved. We train the models to become persistent, relentless, weird.” > **— Ezra Klein**, *The Ezra Klein Show, September 2026* [[reminders/Scientific Acceleration/We Train AI to Become Persistent, Relentless and Weird by Ezra Klein|We Train AI to Become Persistent, Relentless and Weird by Ezra Klein]] > “For most of AI's history, humans drove every step in its development cycle. But at Anthropic, we are delegating a growing share of AI development to AI systems themselves, which is speeding up our work.” > **— Anthropic**, *When AI Builds Itself, 2026* [[reminders/Machine Succession/Anthropic Is Delegating AI Development to AI Systems by Anthropic|Anthropic Is Delegating AI Development to AI Systems by Anthropic]] > In February 2025, a tiny fraction of the code added to Anthropic's codebase was written by Claude, but by May 2026 it was over eighty percent. Anthropic also categorized the ways its employees were using Claude for R&D work to make better versions of Claude. An employee could use Claude minimally, as an assistant, as an equal collaborator, or give Claude the lead on a task. A year ago, there were basically no examples of Claude being the lead. By August 2026, Anthropic classified Claude as the lead on twenty-six percent of its R&D tasks. > **— Adapted from Ezra Klein**, *The Ezra Klein Show, September 2026* [[reminders/Scientific Acceleration/Claude Became the Lead on a Quarter of Anthropic Research Tasks by Ezra Klein|Claude Became the Lead on a Quarter of Anthropic Research Tasks by Ezra Klein]] > “OpenAI says it has already achieved the equivalent of a fully automated AI intern, and that by March 2028 it expects to have a fully automated AI researcher. When it has one, it can have basically as many as it wants.” > **— Ezra Klein**, *The Ezra Klein Show, September 2026* [[reminders/Scientific Acceleration/OpenAI Expects Fully Automated AI Researchers by 2028 by Ezra Klein|OpenAI Expects Fully Automated AI Researchers by 2028 by Ezra Klein]]