Sökning: "Artificial training data"

Visar resultat 1 - 5 av 274 uppsatser innehållade orden Artificial training data.

  1. 1. "The Uphill AI Contract Challenge The Intra-Active Task: Reimagining Contracts"

    Magister-uppsats, Göteborgs universitet/Juridiska institutionen

    Författare :Filip Seiborg Wikström; [2024-02-16]
    Nyckelord :AI; Contract Law; New Materialism; Karen Barad; Intra-Action; Spacetimemattering; Ethico-Onto-Epistem-Ology; Cartesian-Newtonian paradigms; Antimethodology; Agency; Machine Learning;

    Sammanfattning : The traditional contract theories are insufficient to handle the challenges Artificial Intelligence (AI) is currently causing and will continue to cause to contract law. These challenges involve problems concerning the subject/object divide, agency, the embedding of legal code into interactive programming code, and ethical aspects concerning the transfer of power away from lawyers. LÄS MER

  3. 2. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Lisa Linard Pedersen; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

  4. 3. Transforming Chess: Investigating Decoder-Only Architecture for Generating Realistic Game-Like Positions

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :William Pettersson; [2024]
    Nyckelord :Transformer; Decoder; Decoder-only; AI; Artificial intelligence; Generating; generative model; Chess;

    Sammanfattning : Chess is a deep and intricate game, the master of which depends on learning tens of thousands of the patterns that may occur on the board. At Noctie, their mission is to aid this learning process through humanlike chess AI. A prominent challenge lies in curating instructive chess positions for students. LÄS MER

  5. 4. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

    Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Alexander Florean; [2024]
    Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

    Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

  7. 5. Designprocessen och maskininlärning: Framtiden för användarcentrerad design

    Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Lisa Marie Karin Gärdhammar; [2024]
    Nyckelord :Artificial Intelligence; Machine Learning; Design process; Journey Mapping; Empathy; User experience; Customer experience; Artificiell intelligens; Maskininlärning; Designprocessen; Journey Mapping; Empati; Användarupplevelse; Kundupplevelse;

    Sammanfattning : Artificiell intelligens (AI) och i synnerhet maskininlärning (ML) har inom UX-design visat potential att förbättra designprocessen genom att exempelvis identifiera användargrupper från stora datamängder, effektivisera idégenerering och automatisera repetitiva uppgifter. Det råder dock oenighet kring hur tekniken kan integreras i designprocessen. LÄS MER