April 1, 2017

Striim Announces “Pre-Time” Data Integration and Streaming Analytics

PALO ALTO, Calif., April 1, 2017 — After years of development, Striim is extremely excited to announce the alpha release of our new ICC, or “Inverse Chronology Converter,” for pre-time data integration and analytics. Striim has heard over-and-over from our customers how our real-time sub-millisecond latency for data stream processing and analytics still wasn’t fast enough. What customers really want is to have access to data BEFORE it is even created.

Although much of the science of time manipulation is speculative, Striim pursued every avenue to find an appropriate solution that could be used by our customers to see their data as it would be in the future.

Breakthrough Pre-Time Data Technology

The breakthrough was realizing that, while normal micro black holes will simply swallow everything on a path to the center of the earth, spinning charged micro black holes can be contained by a magnetic field, and their affects can be applied to data streams. Data, encoded as photons, can orbit such black holes in tight loops known as “Alfri Loops” (named after the mysterious Professor James Alfri) that move the photons in time, not space.

Inverse Chronology Converter Enables Pre-Time Data Integration and Analytics on Data Before It Is Created

The system consists of a spinning charged micro black hole housed in a vacuum chamber, contained by a magnetic field. A photon beam is directed at the black hole, and is guided into closed time-like paths by the intense gravitational field. The micro-black hole is so small that the gravitational effects are localized to inside the containment sphere. However, photons can get close enough to be affected.

The paths taken by the photons send them backwards in time, so they are detected before they are created. The frequency of the photons can be adjusted, which determines how many loops they make around the black hole, and how far into the past the photons are sent.

The device is constructed from a contemporary unibody aluminum shell, housing the vacuum chamber and all controls, in an elegant modern design. Convenient USB-C ports provide power, inputs and outputs, and control of the future window size. The input data is converted to a photon stream, sent into the past and emerges from the output port up to ten minutes earlier, giving the overall effect of seeing data in the future.

Pre-Time Data Analytics Brings the Future to Now

Imagine what can be done with data gathered, not just faster than competitors, but before the actions creating that data have even happened. It allows companies to not only predict their customers’ behavior, but to know exactly what they will do, and prepare ahead of time.

Navigation applications can direct people around future trouble-spots and even prevent accidents from ever happening (providing the Universe-Saving Paradox Avoidance (USPA) add-on is activated). Reporters can be first to press with the March Madness Championship results, including play-by-play information (although betting on the outcomes of such events is severely frowned upon).

The “Inverse Chronology Converter” is fully integrated into the Striim platform and works like any normal data window over our streams, except that it can be configured for periods that include the future. Simply dragging the UI slider into the future increases the photonic frequency and amplifies the time modification.

We have already utilized this device to analyze social feeds in future real-time, and used the results to optimize the content of this blog. Striim is currently seeking real-world customer use-cases. For ethical reasons, Striim is unable to entertain ideas that could crash the world stock markets, corrupt political processes, or endanger the very fabric of space-time itself.

Due to technological constraints, the current maximum window size is 10 minutes. However, Striim hopes to improve on that for future iterations, assuming Striim can circumvent certain world-swallowing issues with the black-hole containment.

Source: Striim

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