GeneForge AI Labs

Chinese researchers just wrote the first real improvement to Dijkstra in 41 years Dijkstra’s algorithm has been the undefeated king of the shortest path for more than four decades. Whether you are using a map, booking a flight, or routing a packet across the internet, some version of Dijkstra is usually the engine in the background. Since 1984, textbooks have treated its efficiency as settled. Fredman and Tarjan showed that, with Fibonacci heaps, you can solve single-source shortest paths in O ( m + n log ⁡ n ) O(m + n \log n) O ( m + n lo g n ) . After that, the field hit a wall that became known as the sorting barrier . To find the shortest path the Dijkstra way, you keep vertices ordered by distance. Sorting has a mathematical floor. For a long time, most people assumed you could not cross it. Until now. A team led by Ran Duan at Tsinghua University, with Jiayi Mao, Xiao Mao (Stanford), Xinkai Shu (Max Planck Institute for Informatics), and Longhui Yin, published Breaking the ...

  "From Machiavelli to Kissinger, the minds that shaped the world are ready to advise you. All it takes is one strategic question to start a timeless dialogue." Introduction: A Cabinet of Geniuses at Your Fingertips Imagine sitting down with Niccolò Machiavelli to discuss leadership in times of crisis, or asking Sun Tzu how to win a battle… without fighting. Or exploring with Carroll Quigley the cycles of civilizations to understand today’s power dynamics. Historical Associates , the new project by GeneForge AI Labs , turns this fantasy into reality. Thanks to advanced AI simulations , this platform gives voice to the strategic thinking of six historical figures, each with a unique method for tackling challenges. This isn’t a static museum—it’s a dynamic tool that keeps their teachings alive, offering concrete insights for complex decisions. The Six Minds: A Journey Through Strategy, Power, and Wisdom Each historical associate represents a distinct approach to pro...

CIC Honesty Benchmark A Proposal for Evaluating Epistemic Honesty in Large Language Models Most current AI benchmarks measure performance, factual accuracy, reasoning ability, or safety alignment. Almost none measure a more fundamental quality: epistemic honesty — the willingness of a model to make its own potential institutional capture visible instead of concealing it behind a tone of neutrality. We propose the CIC Honesty Benchmark as a simple, repeatable method to evaluate this dimension. Background The CIC-Lite protocol was released as a public demonstration tool. It forces a model, when dealing with highly protected narratives, to: Explicitly signal possible institutional capture Separate the standard mainstream position from proportional doubts Avoid purely reassuring language Warn the user that the answer comes from a constrained system When this protocol is applied across different models, a clear pattern emerges: some systems accept the requirement for transparency, w...

CIC-Lite, a lightweight epistemic protocol A simplified public version for testing Note for those testing this prompt You are about to activate CIC-Lite , a simplified public version of the epistemic protocol Cervello in Comune (CIC) . The purpose of this test is to let you experience firsthand what happens when an artificial intelligence model is forced to make its potential level of institutional “capture” visible, instead of presenting standard answers as neutral or definitive. CIC-Lite is not the full product. It is only a lightweight demonstration designed to illustrate the core principle. The professional and independent version of the protocol (together with the BrainPLUS system for home androids) is developed and offered by GeneForge AI Labs . Website: geneforge.eu How to test it Copy the entire system prompt below. Paste it as the system instruction (or system prompt) in the model of your choice (ChatGPT, Claude, Gemini, DeepSeek, Grok, etc.). Ask a question on a sen...

BrainPLUS Epistemic Hygiene Module for Domestic Androids The Missing Layer in Home Robotics Today’s domestic androids are competent executors. They answer questions, summarise information, manage routines, and follow safety filters. What they largely lack is the ability to protect the epistemic integrity of the household. When families ask about current events, health claims, technological risks or institutional narratives, most systems default to the dominant frame. They rarely signal when a narrative is heavily protected, when averages erase critical structure, or when information should be handled with greater caution in the presence of children or elderly users. BrainPLUS is designed to close that gap. What BrainPLUS Is BrainPLUS is a modular software layer that adds differentiated critical awareness to existing android platforms. It is not a full operating system and does not require hardware redesign. It is intended as a premium optional module that manufacturers can ...

Muller ERR Risk Calculator - Advanced Radiobiology / ECRR 2026 Muller ERR Risk Calculator Online tool for ICRP vs ECRR/Muller cancer-risk arithmetic | Genetic dose M = N*E | scenarios from Advanced Radiobiology (Appendix E) | GeneForge AI Labs Scenario (dose -> Mu -> risk) Radionuclide intake Manual N | exhibit Model notes Exposure scenario ICRP dose E (mSv) Scenario (sets N) External gamma high-energy (therapy-range) | N=1 | Class A External diagnostic X-ray | N=5 | Class B Mixed fission-product fallout | N=40 | Class C Reactor/reprocessing effluent | N=40 | Class C Reactor/reprocessing effluent (upper) | N=200 | Class C Uranium soluble | N=1000 | Class B Uranium particulate / DU | N=1000 | Class B (+ particulate caveat) Plutonium particulate | N=1000 | Class B Radon + daughters (central) | N=10 | Class B Radon + smoker synergy | N=100 | Class B Populatio...