Intuition, intelligence, data compression

Kipper, Jens

doi:10.1007/s11229-019-02118-8

Cited by 6 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We further suggest that as data sets increase in temporal and spatial scales, data‐driven descriptors based on low‐dimensional structure are key for several reasons: (a) they provide sanity checks of intuitive notions or concepts common in sub‐disciplines that are otherwise quantitatively unfalsifiable (Kipper, 2021). For example, in hydrology the notions of “semi‐arid watersheds” and “snow‐driven watersheds” are commonly employed in the literature (Arheimer et al., 2017; Cosh et al., 2008; Manning et al., 2022; Poon & Kinoshita, 2018).…”

Section: Discussionmentioning

confidence: 99%

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

Brown

Fulerton

Kopp³

et al. 2023

Water Resources Research

View full text Add to dashboard Cite

River flow drives the structure and function of aquatic systems on sub-daily to decadal timescales, and sculpts landscapes on geological timescales from months to millennia (Fisher et al., 1998;Pinay et al., 2018;Tucker & Hancock, 2010). For people, variability in river flow regulates access to freshwater, with extreme flow events such as floods and droughts imposing immense personal and societal costs (

show abstract

Section: Discussionmentioning

confidence: 99%

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

Brown

Fulerton

Kopp³

et al. 2023

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…We further suggest that as biogeochemical datasets increase in temporal and spatial scales, data-driven descriptors based on low-dimensional structure are key for several reasons: 1) they provide sanity checks of intuitive notions or concepts common in sub-disciplines that are otherwise quantitatively unfalsifiable (Kipper, 2021). For example, in hydrology the notions of "semi-arid watersheds" and "snow-driven watersheds" are commonly employed in the literature (Arheimer et al, 2017;Cosh et al, 2008;Manning et al, 2022;Poon & Kinoshita, 2018).…”

Section: Low-dimensional Structure In Streamflow Timeseriesmentioning

confidence: 99%

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

Brown

Fulerton

Kopp³

et al. 2022

Preprint

View full text Add to dashboard Cite

River flows change on timescales ranging from minutes to millennia. These variations influence fundamental functions of ecosystems, including biogeochemical fluxes, aquatic habitat, and human society. Efforts to describe temporal variation in river flow—i.e., flow regime—have resulted in hundreds of unique descriptors, complicating interpretation and identification of global drivers of flow dynamics. Here, we used a cross-disciplinary analytical approach to investigate two related questions: 1. Is there a low-dimensional structure that can be used to simplify descriptions of streamflow regime? 2. What catchment characteristics are most associated with that structure? Using a global database of daily river discharge from 1988-2016 for 3,120 stations, we calculated 189 traditional flow metrics, which we compared to the results of a wavelet analysis. Both quantification techniques independently revealed that streamflow data contain substantial low-dimensional structure that correlates closely with a small number of catchment characteristics. This structure provides a framework for understanding fundamental controls of river flow variability across multiple timescales. Climate was the most important variable across all timescales, especially those lasting several weeks, and likely contributes as much as dams in controlling flow regime. Catchment area was critical for timescales lasting several days, as was human impact for timescales lasting several years. In addition, both methods suggested that streamflow data also contain high-dimensional structure that is harder to predict from a small number of catchment characteristics (i.e. is dependent on land use, soil structure, etc.), and which accounts for the difficulty of producing simple hydrological models that generalize well.

show abstract

“…20 In fact, all systems with limited resources that are located in a challenging environment and solve complex problems need to compress information. 21 In the nervous system, a computational benefit of information compression is that the transfer and utilization of a huge amount of sensory information would become much easier and less costly. Furthermore, information compression causes a significant reduction in the amount of memory required to store a body of information.…”

Section: Consciousness and Information Compressionmentioning

confidence: 99%

The QBIT Theory of Consciousness

Beshkar¹

2019

Preprint

View full text Add to dashboard Cite

The QBIT theory is an attempt toward solving the problem of consciousness based on empirical evidence provided by various scientific disciplines including Quantum mechanics, Biology, Information theory, and Thermodynamics. This theory formulates the problem of consciousness in the following four questions: (1) What is the nature of qualia? (2) How are qualia generated? (3) Why are qualia subjective? (4) Why does a quale have a particular quality or meaning?In sum, the QBIT theory proposes that (1) when certainty of an observer about an event exceeds a certain level, the observer becomes conscious of that event; (2) consciousness requires Maxwell demon-assisted quantum computation; (3) a quale is a dense pack of meaningful quantum information encoded in maximally entangled pure states; (4) a quale is generated when robustness of an internal representation exceeds a certain threshold; (5) the quality or meaning of a quale is determined by a process of information compression via the matching and unification of patterns; and (6) subjectivity of consciousness is due to the fact that maximally entangled pure states are private and unshareable.

show abstract

Intuition, intelligence, data compression

Cited by 6 publications

References 23 publications

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

The QBIT Theory of Consciousness

Contact Info

Product

Resources

About