3,199 research outputs found

    Global Solutions vs. Local Solutions for the AI Safety Problem

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    There are two types of artificial general intelligence (AGI) safety solutions: global and local. Most previously suggested solutions are local: they explain how to align or “box” a specific AI (Artificial Intelligence), but do not explain how to prevent the creation of dangerous AI in other places. Global solutions are those that ensure any AI on Earth is not dangerous. The number of suggested global solutions is much smaller than the number of proposed local solutions. Global solutions can be divided into four groups: 1. No AI: AGI technology is banned or its use is otherwise prevented; 2. One AI: the first superintelligent AI is used to prevent the creation of any others; 3. Net of AIs as AI police: a balance is created between many AIs, so they evolve as a net and can prevent any rogue AI from taking over the world; 4. Humans inside AI: humans are augmented or part of AI. We explore many ideas, both old and new, regarding global solutions for AI safety. They include changing the number of AI teams, different forms of “AI Nanny” (non-self-improving global control AI system able to prevent creation of dangerous AIs), selling AI safety solutions, and sending messages to future AI. Not every local solution scales to a global solution or does it ethically and safely. The choice of the best local solution should include understanding of the ways in which it will be scaled up. Human-AI teams or a superintelligent AI Service as suggested by Drexler may be examples of such ethically scalable local solutions, but the final choice depends on some unknown variables such as the speed of AI progres

    Aquatic refuges for surviving a global catastrophe

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    Recently many methods for reducing the risk of human extinction have been suggested, including building refuges underground and in space. Here we will discuss the perspective of using military nuclear submarines or their derivatives to ensure the survival of a small portion of humanity who will be able to rebuild human civilization after a large catastrophe. We will show that it is a very cost-effective way to build refuges, and viable solutions exist for various budgets and timeframes. Nuclear submarines are surface independent, and could provide energy, oxygen, fresh water and perhaps even food for their inhabitants for years. They are able to withstand close nuclear explosions and radiation. They are able to maintain isolation from biological attacks and most known weapons. They already exist and need only small adaptation to be used as refuges. But building refuges is only “Plan B” of existential risk preparation; it is better to eliminate such risks than try to survive them

    On the delooping of (framed) embedding spaces

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    It is known that the bimodule derived mapping spaces between two operads have a delooping in terms of the operadic mapping space. We show a relative version of that statement. The result has applications to the spaces of disc embeddings fixed near the boundary and framed disc embeddings.Comment: arXiv admin note: text overlap with arXiv:1704.0706

    In Memory of My Friend and Colleague

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    Identification of clinical characteristics of large patient cohorts through analysis of free text physician notes

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    Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2005.Includes bibliographical references (p. 31-33).Background A number of important applications in medicine and biomedical research, including quality of care surveillance and identification of prospective study subjects, require identification of large cohorts of patients with specific clinical characteristics. Currently used conventional techniques are either labor-intensive or imprecise, while natural language processing-based applications are relatively slow and expensive. Specific Aims In this thesis we describe the design and formal evaluation of PACT - a suite of rapid, accurate, and easily portable software tools for identification of patients with specific clinical characteristics through analysis of the text of physician notes in the electronic medical record. Methods PACT algorithm is based on sentence-level semantic analysis. The major steps involve identification of word tags (e.g. name of the disease or medications exclusively used to treat the disease) specific for the clinical characteristics in the sentences of the physician notes. Sentences with word tags and negative qualifiers (e.g. "rule out diabetes") are excluded from consideration. PACT can also identify quantitative (e.g. blood pressure, height, weight) and semi-quantitative (e.g. compliance with medical treatment) clinical characteristics. PACT performance was evaluated against blinded manual chart review (the "gold standard") and currently used computational methods (analysis of billing data). Results Evaluation of PACT demonstrated it to be rapid and highly accurate. PACT processed 6.5 to 8.8x 10⁵ notes/hour (1.0 to 1.4 GB of text / hour).(cont) When compared to the gold standard of manual chart review, PACT sensitivity ranged (depending on the patient characteristic being extracted from the notes) from 74 to 100%, and specificity from 86 to 100%. K statistic for agreement between PACT and manual chart review ranged from 0.67 to 1.0 and in most cases exceeded 0.75, indicating excellent agreement. PACT accuracy substantially exceeded the performance of currently used techniques (billing data analysis). Finally, index of patient non-compliance with physician recommendations computed by PACT was shown to correlate with the frequency of annual Emergency Department visits: patients in the highest quartile for the index of non-compliance had 50% as many annual visits as the patients in the lowest quartile. Conclusion PACT is a rapid, precise and easily portable suite of software tools for extracting focused clinical information out of free text clinical documents. It compares favorably with computation techniques currently available for the purpose (where ones exist). It represents an important advance in the field, and we plan to continue to develop this concept further to improve its performance and functionality.by Alexander Turchin.S.M
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