Visualizing Future Geopolitical, Environmental, and Public
Health Events in Data and Imagery
NEW
YORK, Sept. 12, 2024 /PRNewswire/
-- Jumptuit is pleased to announce significant advances in its
Next Generation AI, Genesis J2T's Anticipatory Intelligence to
forecast and visualize through the mediums of data and imagery
probable geopolitical, environmental, and public health events for
corporate and government leaders.
Genesis J2T has substantially increased its range of coverage of
global atmospheric, terrestrial, and oceanic phenomena, and human
activity and artificial systems, from widely dispersed and varied
sensors, across the full EM spectrum, as well as hyper-localized
data sources that provide unfiltered up-to-date information on
human activity and artificial systems.
Genesis J2T has advanced its ability to extract reliable
cross-sector signals from a complex of diverse data sources and
increased its ability to anticipate probable events, reducing
exposure to incidents and, in so doing, mitigating the Cost of Risk
(COR). Genesis J2T's ever-expanding array of hyper-localized data
sources removes filters, provides greater clarity, and
observability of global phenomena and sector conditions as they
occur for any geolocation.
Genesis J2T synchronizes millions of realtime data endpoints via
its Global Sensory Intelligence (GSI) and its Global Data Nets
(GDNs) to retrieve realtime and near-realtime hyper-localized data,
and to assess geopolitical, environmental, and public health event
risk.
Genesis J2T removes algorithmic interference in data acquisition
and modeling, and provides transparency and traceability of the
data sources, variables, and processes used in generating risk
index indicators and probabilities of events.
Traditional AI
The benchmark for development of traditional AI has been human
intelligence, the starting point language models, and the design of
neural networks, an attempt at simulating human brain functions,
including complex processes of human-decision making. The inherent
limitations in this approach are modeling AI on human intelligence
and human characteristics and behavior, which embody a subjective
view of the Universe and its adjacent biases. The AI sector remains
largely focused on improving generative AI's capabilities of
mimicking human behavior, including the creation of "original
content" including text, images, audio, and video. Its most
effective commercial applications to date have been the automation
of repetitive tasks and improving accuracy with the goal of
increasing organizational efficiencies.
The Principles of Genesis J2T's Anticipatory
Intelligence
Genesis J2T: Observing the Physical Environment
Global synchronization of realtime data from sensors.
Expanding and extending the range of human sensory reception
into a new single perceptual frame that manifests as a new global
sensory system.
Exceeding the sensory capabilities of living organisms that
perceive stimuli beyond human range.
Synchronizing global observation across spectrums and
frequencies that surpass the narrow band perception through which
human beings experience the Universe.
Synchronizing millions of realtime data endpoints, globally
dispersed, to discover probable events through unbiased sensor
observation of co-occurring variables.
Genesis J2T: Observing Human Behavior
Reliable cross-sector signals from hyper-localized data
sources.
The ethical framework for Anticipatory Intelligence is the
sanctity of the observation process and the protection of the data
from bias.
Viewpoints are decoupled from the observation process.
Narratives are replaced with veracity through a neutral
observation process.
Search engine filtration and global news organization curation
are circumvented and augmented with realtime hyper-localized data
sources in every region of the world.
Forecasting Probabilities of Environmental and Geopolitical
Events
Realtime Data vs. Historical Data
Genesis J2T continuously searches for comparable data sets in
the present rather than search historical databases for perceived
similar events in the past. From a data standpoint, the
co-occurring variables or conditions leading up to and surrounding
events in the past are increasingly dissimilar the further one
travels back in time. Comparable data sets in the present do not
require virality or causation for parallel events to occur,
although Genesis J2T's models dynamically allow for both.
There are no explicit historical patterns. There is only the
next dynamic set of variables. Genesis J2T has demonstrated that
when cross-sector panoptic data sets are captured, even in
increments of seconds, in every instance there are variables that
disappear and new variables that emerge. Therefore, the assortment
and relative value of each data point is in a continuous state of
flux denoting waves of probable events. To forecast probable events
with reliability it is critical to capture and train on
cross-sector data sets as close to the present as possible, marking
an important step toward reducing dependencies on theories and
models designed to substitute for an absence of data.
"Solving the data puzzle of visualizing a future event requires
enough data puzzle pieces to work with in order to identify the
probable geolocation, event type, actors, and time frame," said
Jumptuit CEO and founder Donald
Leka. "Conformity to facts requires a decoupling of
viewpoints, interpretations and biases from the observation process
and the exclusion of narratives from the forecasting process. The
human and financial cost of miscalculations in forecasting is
immeasurable. AI-powered early-stage detection of global events
that impact global financial markets, jurisdictions, sectors,
industries and companies, will provide corporate and government
leaders with the ability to expedite and improve decision-making,
scheduling, planning and execution to proactively avoid,
circumvent, and bypass event risk."
Jumptuit Editorial Contact:
Jordan Glass
Jumptuit
914.584.5022
jglass@jumptuit.com
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SOURCE Jumptuit