Dalmo Cirne

Dalmo Cirne

Denver Metropolitan Area
777 followers 500+ connections

About

I specialize in technology and leadership of engineering teams in the creation of…

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Experience

  • Workday Graphic

    Workday

    Boulder, Colorado, United States

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    Boulder, Colorado, United States

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    Greater New York City Area

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    Greater New York City Area

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    Greater New York City Area

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    Greater New York City Area

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    Bristol, CT

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    Greater New York City Area

Education

  • State University of New York Empire State College

Licenses & Certifications

Publications

  • Fostering Trust and Quantifying Value of AI and ML

    arXiv

    Artificial Intelligence (AI) and Machine Learning (ML) providers have a responsibility to develop valid and reliable systems. Much has been discussed about trusting AI and ML inferences (the process of running live data through a trained AI model to make a prediction or solve a task), but little has been done to define what that means. Those in the space of ML- based products are familiar with topics such as transparency, explainability, safety, bias, and so forth. Yet, there are no frameworks…

    Artificial Intelligence (AI) and Machine Learning (ML) providers have a responsibility to develop valid and reliable systems. Much has been discussed about trusting AI and ML inferences (the process of running live data through a trained AI model to make a prediction or solve a task), but little has been done to define what that means. Those in the space of ML- based products are familiar with topics such as transparency, explainability, safety, bias, and so forth. Yet, there are no frameworks to quantify and measure those. Producing ever more trustworthy machine learning inferences is a path to increase the value of products (i.e., increased trust in the results) and to engage in conversations with users to gather feedback to improve products. In this paper, we begin by examining the dynamic of trust between a provider (Trustor) and users (Trustees). Trustors are required to be trusting and trustworthy, whereas trustees need not be trusting nor trustworthy. The challenge for trustors is to provide results that are good enough to make a trustee increase their level of trust above a minimum threshold for: 1- doing business together; 2- continuation of service. We conclude by defining and proposing a framework, and a set of viable metrics, to be used for computing a trust score and objectively understand how trustworthy a machine learning system can claim to be, plus their behavior over time.

    Other authors
    See publication
  • Fostering Trust on Machine Learning Inferences

    IARIA - International Academy, Research, and Industry Association

    Artificial Intelligence (AI) and Machine Learning (ML) providers have a tremendous responsibility to develop valid and reliable systems. Much is discussed about trusting AI and ML inferences, but little has been done to define what that means. Those who work in the space of ML-based products, have familiarity with the topics of transparency, explainability, safety, bias, and so forth, yet there are no frameworks to quantify and measure such items. Producing ever more trustworthy machine…

    Artificial Intelligence (AI) and Machine Learning (ML) providers have a tremendous responsibility to develop valid and reliable systems. Much is discussed about trusting AI and ML inferences, but little has been done to define what that means. Those who work in the space of ML-based products, have familiarity with the topics of transparency, explainability, safety, bias, and so forth, yet there are no frameworks to quantify and measure such items. Producing ever more trustworthy machine learning inferences is a path to increase the value of products (i.e., increased trust in the results) and to engage in conversations with users to gather feedback to further improve products. In this paper, we begin by examining the dynamic of trust between a provider (Trustor) and users (Trustees). Trustors are required to be trusting and trustworthy, whereas trustees need not be trusting nor trustworthy. The challenge for trustors is to provide results that are good enough to make a trustee increase their level of trust above a minimum threshold for: 1- doing business together; 2- continuation of service. Then, we conclude by proposing a framework to capture quantitative metrics to be used to objectively understand how trustworthy an AI and ML system can claim to be, and their trend over time.

    ISBN: 978-1-68558-089-6

    See publication
  • Convergence rank and its applications

    WITPress

    In this paper, we explore an algorithm to determine the relevance of each item in a finite set of items in reference to each other to address an item you have to first go through a convergence or proxy item. If we imagine a media streaming company (convergence item) and all its available genres for playback (items in a finite set), how relevant is each music genre at different moments in time? Or with a sports broadcasting company and the covered sports, how does the relevance of each sport…

    In this paper, we explore an algorithm to determine the relevance of each item in a finite set of items in reference to each other to address an item you have to first go through a convergence or proxy item. If we imagine a media streaming company (convergence item) and all its available genres for playback (items in a finite set), how relevant is each music genre at different moments in time? Or with a sports broadcasting company and the covered sports, how does the relevance of each sport changes throughout the year as sports seasons begin and end?
    As the algorithm gets developed in the paper, we introduce an artificial node to the relationship graph, which brings a disproportional weight in importance. Later, we show how to remove the artificial node from the final rank vector to obtain a ranking of items in the set without any distortions.
    In addition to the ranking of a single point in time, the algorithm expands to analyze a sequence of consecutive convergence rankings, infers the behavior of trends and allows for the forecasting of near-future or cyclical ranks.
    The applications of this algorithm are immediate and plentiful in possibilities. In its essence, this algorithm can help to understand the usage behavior of services by its users based on non-invasive simple data collection. From its results, it is possible to better plan the allocation of resources.

    See publication
  • ARGEOM - Augmented Reality Geolocation Math

    Augmented reality combined with modern day smartphones equipped with cameras, magnetometers, and with the ability to display maps on the screen make a powerful tool that can be used in a plethora of different applications. This paper explores the math that goes behind such apps and the implementation of a completely functional project.

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  • Forward Iterators

    In this article we will see a simple way of using iterators to traverse a raw memory container of pretty much anything, without departing from the familiarity of Objective-C code. We will use a simple class derived from NSObject and delegation to implement a forward iterator.

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  • Multithreading: An Extensive Study on Linux, OpenSolaris, and Windows

    There are many reasons why one may choose a particular operating system to run on their computer: availability of software, technical skills, etc. Among those reasons one may choose the operating system with the best performance, or the one with the lowest cost per transaction. This paper examines three operating systems (Linux, OpenSolaris, and Windows) and their respective capabilities of taking advantage of the multiple cores present in modern processors by executing operations with…

    There are many reasons why one may choose a particular operating system to run on their computer: availability of software, technical skills, etc. Among those reasons one may choose the operating system with the best performance, or the one with the lowest cost per transaction. This paper examines three operating systems (Linux, OpenSolaris, and Windows) and their respective capabilities of taking advantage of the multiple cores present in modern processors by executing operations with integers, floating points and math, and I/O in a multithreaded way, achieving parallelism in the execution of those operations, and then tries to reason the measurements from the experiments in the economics of an operating system.

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  • Convergence of Information: How Corporations Can Dramatically Enhance the Decision-Making Process.

    A company has to understand and measure its processes in order to properly manage the business. This is not an easy task, since the information is spread among various systems in an heterogeneous computational environment. Convergence of Information deals with the challenge of providing a single entry point where all key metric elements can be accessed, giving agility to management and executives, and enhancing the overall performance of the corporation.

    See publication
  • A Different Approach to a Window System: The Modeling and Applications of a Non-Overlapping Window Environment.

    The era of Web 2.0 allowed us to implement and use windows inside a web browser, without impact neither on performance nor usability. The possibility of desktop-like experience while using web applications, broads the horizon of programs that can benefit from all the advantages that come with the Internet.

    In this paper we are going to explore a different approach to how a dynamic window system can function and behave. Windows squeeze and expand, resembling an accordion. This way…

    The era of Web 2.0 allowed us to implement and use windows inside a web browser, without impact neither on performance nor usability. The possibility of desktop-like experience while using web applications, broads the horizon of programs that can benefit from all the advantages that come with the Internet.

    In this paper we are going to explore a different approach to how a dynamic window system can function and behave. Windows squeeze and expand, resembling an accordion. This way, windows give a little space to other windows (when required) , or request a larger area, within the canvas, to allow the user to concentrate his/hers focus, without loosing the sight of what is in the other windows.

    See publication
  • Outsourcing Middle Management

    Is it feasible to outsource the middle management team of a company? One might argue that it is impossible, because they play a critical role in the company’s operation. They communicate the strategy, help to set goals, manage projects, and report the results back to the executives. Business intelligence combined with a management methodology and dashboards can make the strategy communication, goal set, proper management, and result feedback cycle less dependent on the human factor. Under such…

    Is it feasible to outsource the middle management team of a company? One might argue that it is impossible, because they play a critical role in the company’s operation. They communicate the strategy, help to set goals, manage projects, and report the results back to the executives. Business intelligence combined with a management methodology and dashboards can make the strategy communication, goal set, proper management, and result feedback cycle less dependent on the human factor. Under such a scenario one can imagine a smaller, more efficient, and less costly middle management team.

    See publication
  • Cash Processing and Handling

    This system was develop back in 2001 by me in cooperation with De La Rue after we identified the need of treasury rooms to process different kinds of forms of payment, in different processing cells, but all working together and in a collaboratively way.

    You can watch a short 5-minute documentary at http://www.youtube.com/watch?v=Qj2r-kZ9weg

    See publication

Patents

  • IN-PROCESS ENGINE IMPLEMENTATION USING SDK EXTENSIONS FIELD OF THE INVENTION

    Issued 11341363

    A system for optimizing results of processed assets for provision to software applications based on determined sequences of operation is disclosed, the system having a cloud-based engine and a plurality of models that are each usable by the engine to provide artificial intelligence in connection with software applications. Multiple software extensions are executed by the engine in accordance with a respective model for at least one of the general-purpose software applications. Input data are…

    A system for optimizing results of processed assets for provision to software applications based on determined sequences of operation is disclosed, the system having a cloud-based engine and a plurality of models that are each usable by the engine to provide artificial intelligence in connection with software applications. Multiple software extensions are executed by the engine in accordance with a respective model for at least one of the general-purpose software applications. Input data are processed as a function of at least one of the models and a set of the plurality of extensions, wherein a given sequence of executing the set of extensions on one of the inputs impacts results provided by the engine. The engine is configured by executing each of the extensions in different sequences to grade a respective degree of inference and selecting an optimum sequence, which is communicated to the general-purpose software application.

    Other inventors
    See patent
  • Genetic Algorithm for Territory Optimization

    Filed 17/818472

  • Anomaly Detection of Miscoded Tags in Data Fields

    Filed 17/698458

  • Correlating Request and Response Data Using Supervised Learning

    Filed 17/695180

Projects

  • Speaker at IARIA 2024. Lecture on RAG and session on quantifying Trust in AI/ML

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    https://www.iaria.org/conferences2024/ProgramIARIACongress24.html

  • Speaker at Apache Big Data 2016

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    Presented the research from the paper I authored: "Convergence rank and its applications" - http://www.witpress.com/elibrary/dne-volumes/11/3/1191

    See project
  • Speaker at 360|iDev 2013

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    Augmented Reality Geolocation Math – http://dalmocirne.blogspot.com/2013/05/argeom-augmented-reality-geolocation.html

    See project
  • Speaker at iOSDevUK 2013

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    Augmented Reality Geolocation Math – http://dalmocirne.blogspot.com/2013/05/argeom-augmented-reality-geolocation.html

    See project
  • Speaker at LinuxCon Europe 2011

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    Multithreading: An Extensive Study on Linux, OpenSolaris, and Windows – http://dalmocirne.blogspot.com/2010/04/multithreading-extensive-study-on-linux.html

    See project

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