The processing time for videos is not an exact science, primarily due to the dynamic nature of content feeds. Several factors influence the approximate time it takes to process a video through the system.

Firstly, the Frames Per Second (FPS) plays a significant role. Videos are broken down into individual frames, and each frame is analyzed separately. A video with a higher FPS, such as 60 FPS, will generally take longer to process compared to a video with a lower FPS, like 25 FPS. However, other elements come into play as well.

The complexity of the video content also affects processing time. For instance, a 25 FPS video that features five people communicating may require more processing time than a 60 FPS video with only one person. This is because the system needs to extract and analyze numerous individual data points from the media, which is a time-consuming process.

Additionally, the processing time increases when multi-agent algorithms come into play. These algorithms are responsible for connecting derived data markers to the contextual aspects of the conversation or discussion in the video. Incorporating this step can significantly prolong the overall processing time.

On average, for every 60 seconds of video, the processing time amounts to approximately 1 hour and 6 minutes. It is important to understand that this estimation may vary depending on the specific characteristics of the video being processed.

It is ironic that we were previously involved in discussions with representatives of a sitting president regarding their interest in utilizing the system for an upcoming election. They were interested in using the system to discredit their opposition by manipulating specific points to show “Deception.” We informed them that such manipulation was not possible due to ethical considerations and technical limitations. Manually overlaying frames would require a significant amount of time, much more than the averaged computational approach of approximately 1 hour and 6 minutes for every 60 seconds of video. In theory, it would take at least 6 hours to process each frame and assemble them, making it obvious that the video was altered.

To alleviate concerns on this matter, we recommend watching a sped-up demonstration of the process for one video, which initially took around 5 hours. This will provide a clearer understanding of the process and hopefully address any remaining doubts.

[Truth] Serum, as described in https://en.wikipedia.org/wiki/Multi-agent_system, is a genuine example of a Multi-Agent Artificial Intelligence (AI) System.

Its classification as a True Multi-Agent AI System stems from its utilization of multiple sub-routine processes that actively engage with one another to generate practical and applicable intelligence.

The reason why the vocal (voice) may not always be in sync with the person in the videos processed by the system is due to the way the system operates. The system downloads videos from platforms like Twitter or YouTube, which have varying frame rates per second (FPS). As the system analyzes each frame and vocal segment against the frames, the analytical side is not affected. However, when it comes to presenting the video to the user, a common FPS encoding is used to stitch the frames back together.

Sometimes, this standardized FPS encoding can conflict with the original frame rate of the video. Since this stitching process is automated, it can occasionally result in blemishes such as the vocal being out of sync with the visual content.

In the future, there are plans to address this issue by implementing a dynamic aspect for stitching based on the raw video files. By doing so, the system will be able to better synchronize the audio and visual components. However, since this syncing issue is primarily cosmetic and occurs infrequently, it is not currently the highest priority for improvement.