Is there any relationship between ambiguity and uncertainty in predictive coding?5 answersAmbiguity and uncertainty are related in predictive coding. In natural language processing tasks, such as word sense disambiguation (WSD) and neural sequence models, ambiguity refers to the multiple possible outputs for a given input. This ambiguity leads to intrinsic uncertainty, which affects the distribution learned by the models. The degree of overlap between references in multi-reference test sets is used to measure sentence-level uncertainty. Tasks with high levels of ambiguity, such as machine translation (MT), exhibit well-known pathologies like a high number of beam search errors and the inadequacy of the mode. In contrast, less uncertain tasks like grammatical error correction (GEC) do not show these pathologies. The model uncertainty is also affected by intrinsic uncertainty, as the probability mass tends to be overly spread out for uncertain tasks and sentences.
What is ambiguity?5 answersAmbiguity is a non-biunivocal form-meaning relationship that imposes an impossible choice on the hearer/reader. It arises from homonymy or polysemy and can be found at all levels of linguistic analysis. Different strategies are used by the hearer/reader and the speaker/writer to deal with ambiguity depending on the situation. Ambiguity is also a characteristic aspect of artistic thinking and plays a significant role in the artistic creation process. It allows for multiple interpretations and opens up the endless field of meaning in literature. In decision-making, ambiguity refers to situations where the available information is insufficient to form a probabilistic view of the world. It has led to the departure from the Subjective Expected Utility (SEU) paradigm and the development of non-expected utility models.
What uncertainties do?4 answersUncertainties refer to unknown factors or events that create unpredictability or lack of knowledge about the future. They can arise in various fields such as environmental and human health, engineering, economic factors, and energy management systems. In the context of emerging technologies, uncertainties revolve around the risks and benefits associated with these technologies and how regulators and policymakers manage them. In engineering, uncertainties are present in any task and can be ignored if predictions align with test results, but become crucial when there is disagreement. Economic factors are also subject to uncertainties due to unpredictable phenomena, leading to unpredictability in the market and potential risks and gains for investors. In energy management systems, uncertainties in supply or load, particularly in renewable generation, are addressed through forecasting and stochastic control techniques. Overall, uncertainties introduce challenges and require specific approaches to assess and manage risks in different domains.
What is uncertainty in stock portfolio?5 answersUncertainty in stock portfolios refers to the presence of unknown or unpredictable factors that can affect the performance and behavior of the stocks within the portfolio. It is the lack of certainty or predictability in the future returns of the stocks. Uncertainty can arise from various sources such as market conditions, economic factors, political events, and investor sentiment. The presence of uncertainty makes it challenging for investors to accurately estimate the future performance of their portfolios and make informed investment decisions. Studies have shown that uncertainty factors, such as variance risk premium and economic uncertainty, can have a significant impact on stock returns and can be used to predict the time-series and cross-sectional variation in stock returns. Investment strategies that consider uncertainty and incorporate measures such as randomness, fuzziness, and λ-weighting functions have been proposed to optimize portfolio performance. Additionally, it has been observed that the assumption of normality and constant correlation in asset class return distributions can underestimate the risk associated with a portfolio, highlighting the importance of considering uncertainty in portfolio management.
Does risk and uncertainty align in a business setting?5 answersRisk and uncertainty are important elements in a business setting as they can impact decision-making and the stability of a company. Businesses, including agricultural cooperatives, employ various strategies to mitigate risk and uncertainty. Uncertain taxes can also affect investment decisions and distort the overall investment landscape. In today's rapidly changing social and economic environment, understanding and managing risk is crucial for businesses to thrive. Business models, which are subject to risk and uncertainty, require effective risk management processes to make informed decisions. Overall, risk and uncertainty play a significant role in the management and governance of businesses, and addressing them appropriately can lead to better outcomes and opportunities for growth.
What is confidently uncertain?3 answersConfidently uncertain refers to the state of having knowledge or information that is surrounded by significant uncertainty. It is the recognition that while there may be some understanding or evidence available, there are still uncertainties and limitations in making predictions or drawing conclusions. This concept is relevant in various fields such as evidence-based policy, development economics, and statistical analysis. Researchers and analysts aim to extrapolate causal effects from experiments to new populations, but they must acknowledge and manage the uncertainties that arise from assumptions and limitations in the data. The support graph approach is a novel method that allows analysts to systematically and unifiedly articulate and manage uncertainty in extrapolation. Uncertainty theory is a branch of mathematics that models human uncertainty and provides tools for quantifying and analyzing uncertain elements, risks, and reliability.