Status: In Progress
Description:
This program aims to modernize the power and application of sigils. A sigil is a symbolic representation of an intention created by combining letters or symbols and used to manifest desires. Similar to FieldREG data, Intentional Datasets are created using Random Number Generators that are producing data during sessions in which meditators focus on a specific intention. These data serve as symbolic representations of the intention, becoming digital versions of traditional sigils. Using custom software tools developed at the Institute, the collected data can be processed into images, sounds, 3D printable shapes, or utilized in computer applications locally or online. This program explores the impact of intentional datasets on individuals and devices.
Resulting Publications/Presentations/Applications:
Impact of Intentional Datasets on Nonbiological Systems
Boccuzzi, M. (2016, June). Applying Machine Learning to Psi Research: An example of using a deep machine learning image classifier to analyze seemingly random visualized FieldREG data collected during sessions with meditators. 35th Annual Meeting of the Society for Scientific Exploration and 59th Annual Convention of the Parapsychological Association Joint Meeting. Boulder, Colorado.
This presentation investigates the distinctions between two intentional datasets (“Love” and “Hate”) through visualization. Machine image recognition software analyzed the visualized data, extracted details, and classified them based on visual attributes. The software successfully grouped the majority of the “Hate” images together, revealing an unnoticed characteristic. This exploratory research uncovers an intriguing interaction among the datasets, their underlying intention, and the visualization software.
Impact of Intentional Datasets on Biological Systems
Boccuzzi, M. (2018, June). Datasets as vectors for intention: Measuring the impact of intention-entangled datasets on the happiness scores of online gamers. Poster presented at the 37th Annual Meeting of the Society for Scientific Exploration (joint conference with the International Remote Viewing Association). Las Vegas, Nevada.
In a prior study, FieldREG data from random event generators were collected while experienced meditators focused on Love and Hate. These datasets were converted into images using custom visualization software. Deep learning-based image analysis revealed a unique feature in four of the five Hate images, despite no apparent differences in the datasets. This finding prompts two questions: Does the intention behind the dataset influence how visualization software interprets it? And can people interacting with such datasets be influenced by their original intentions? To investigate, the current exploratory study employed Love, Hate, and Neutral datasets to drive an online app, examining their impact on user mood.
To address these questions, the current exploratory study used the Love and Hate datasets and a new Neutral intention to drive the gameplay of an online app in order to determine if the intention associated with each dataset impacted the mood of the app’s users.
Visualizing Intention: Art Informed by Science
Boccuzzi, M (2015)
Can the power of our thoughts influence the physical world around us? What if we could see our intentions, hopes, and fears displayed before us? Could these images allow us to connect with our deeper selves, others, and departed loved ones? Windbridge Institute husband and wife research team, Mark Boccuzzi and Julie Beischel, PhD, spent a year exploring these and other questions relating to consciousness's extended nature and the connections between our minds and the physical world.
Intentional Datasets: From Data to Art
Intentional datasets can be visualized, sonified (turned into music), and transformed into 3D-printed objects.
PsiForms: Mindfulness Meditation Cards
The images, called PsiForms, were created from data that were collected from a Random Event Generator (REG) while a group of meditators focused their intention on the specific ideas that are listed on each card. Researchers Julie Beischel, PhD, and Mark Boccuzzi developed these meditations and the specialized software that converts the binary data from the REGs into the images displayed on the cards.
The set contains: 12 full-color cards ~ 1 instruction booklet ~ 1 12-sided die ~ 7 colored cubes (Choking Hazard! Keep out of reach of children!) ~ 1 drawstring storage pouch.
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