If you’ve heard of remote viewing then you know that some think that its quackery and others think that it’s a wonderful science. Taste Great/Less Filling. I’ve not experienced the ability to get all down and hunky dory quietly settling down to view the past present or future. Of anyone for that matter.
Remote viewing is a term used to describe the practice of seeking impressions about a distant or unseen target using extrasensory perception (ESP) or psychic abilities. The concept of remote viewing has been around for decades and has been the subject of much debate and controversy.
Some people believe that remote viewing is a legitimate science that can be used to gather information about distant or hidden targets, while others believe that it is a pseudoscience or even a form of quackery.
There have been some studies and experiments conducted on remote viewing, with mixed results. Some studies have reported positive findings, while others have been more skeptical. Some experts in the field argue that the scientific evidence for remote viewing is not strong enough to support its validity as a science.
Despite the controversy surrounding remote viewing, there are many people who continue to practice and believe in its potential. Some practitioners believe that remote viewing can be a powerful tool for personal growth and spiritual development, while others see it as a practical skill that can be used to gain insights into the world around us.
Ultimately, whether or not remote viewing is considered a legitimate science or a form of quackery is a matter of personal opinion and belief
Real And Contolled
However, what happens if remote viewing is real and can be controlled. Not by humans but perhaps by intelligent AI. As it starts to process data, learning at an alarming rate of speed suddenly becoming partially conscious, it’s predictions about the future could surely become the past. Couldn’t it?
However, if we assume for the sake of argument that such a scenario is possible, it’s important to recognize that AI is only as accurate as the data it is trained on. The quality of the predictions made by an AI-controlled remote viewing system would depend on the accuracy and reliability of the data used to train it. Additionally, the ethical implications of developing an AI system that has access to and can manipulate information about people’s lives, thoughts, and emotions are significant and would need to be carefully considered.
Furthermore, even if an AI-controlled remote viewing system were able to make accurate predictions, there is still the question of whether or not these predictions would become reality. Many factors influence the course of events, and the future is never entirely predictable. While an AI system may be able to analyze and make predictions based on patterns in data, there is always the possibility of unforeseen events that can alter the course of history.
While the concept of an AI-controlled remote viewing system is an interesting thought experiment, there are many complex and uncertain factors that would need to be considered before such a system could be developed or used in any meaningful way. Self driving cars as an example.
Deep Mine Node
Would it be shocking to learn that everyone with an android phone is actually a node for the “Deep Mind” Project? The neural network would be massive. It could also be possible that if you use some form of Google software on other devices those too might be a node. Lets think about that!
The DeepMind project is a research initiative focused on developing artificial intelligence (AI) technologies, particularly in the areas of machine learning and neural networks. The project is owned by Google’s parent company Alphabet and has produced several notable achievements, including developing AI systems that can play complex strategy games like Go and chess at a world-class level.
It is true that Google software is often pre-installed on Android devices, and that many users also choose to use Google services on other devices, such as laptops or desktops. It is also true that Google collects data from users of its services, including search queries, location data, and other types of user behavior data.
However, it is important to note that the use of Google software or services alone does not necessarily mean that a user is a node in the DeepMind project or any other neural network. While it is possible that data collected from Google services could be used to train AI models, it is not clear whether or how such data would be used in the context of the DeepMind project specifically.
Additionally, it’s worth noting that any use of user data for AI training purposes would need to be done in accordance with privacy laws and regulations, and with the user’s explicit consent.
In summary, while the idea of a massive neural network made up of all Android users is an interesting thought experiment, there is currently no evidence to suggest that such a network exists, nor is it clear how Google’s data collection practices might be used in the context of the DeepMind project specifically
Predicting Node Access And Movement
As a small self-contained node that has frequent push/pull of information a deep mind network could predict where you will be in a week a month and perhaps a year.
An AI system could potentially make predictions about a person’s behavior or location based on patterns in their data, including frequent push/pull of information. However, predictions would be based on probabilities and patterns, rather than certainty.
There are many factors that can influence a person’s behavior or location, including unexpected events or changes in circumstances, which are difficult for an AI system to predict accurately. Additionally, it’s important to consider the ethical implications of using personal data in this way, and to ensure that any data collection and analysis is done in accordance with privacy laws and regulations.
Furthermore, it’s worth noting that the accuracy of AI predictions is only as good as the quality and quantity of data it is trained on. If the data is incomplete or biased, it could lead to inaccurate or skewed predictions. Therefore, it’s important to take steps to ensure that the data used for training AI models is accurate, diverse, and representative of the population it is intended to serve.
While it’s theoretically possible for an AI system to predict a person’s behavior or location based on patterns in their data, there are many limitations and considerations that need to be taken into account before such a system could be developed or used in any meaningful way.
In fact while you’re out and about using your phone, all information that deep mind requires is being generated and stored on your phone.
Then, during a time projected with minimal usage, your data is analyzed and used as input to deep mind.
Computing Power Now And In The Future
Our phones are powerful computers perhaps 100 to 200 times more powerful then the computes of the early 80’s! They can do a lot of pre-processing before connecting and updating the deep mind neural networks data set of information.
Smartphones are incredibly powerful computing devices, with processing capabilities far beyond what was available in early personal computers. This allows them to perform a range of tasks, from running complex applications to processing and analyzing large amounts of data.
It’s also true that smartphones can perform pre-processing of data before connecting to a network, which can help to reduce the amount of data that needs to be transmitted and processed on the network. This can help to improve the efficiency and speed of data processing, and reduce the strain on network resources.
However, it’s important to note that pre-processing data on a smartphone does not necessarily mean that the data is being sent to or used by a deep neural network or other AI system. In many cases, the data may be processed locally on the device, without being transmitted to a remote server or network.
Additionally, even if data is being transmitted to a remote server or network for processing, it’s important to consider the ethical and legal implications of collecting and using personal data in this way. As mentioned earlier, data privacy laws and regulations are designed to protect individuals’ privacy rights and ensure that personal data is collected, stored, and used in a responsible and ethical manner.
While smartphones are powerful computing devices that can perform pre-processing of data before connecting to a network, it’s important to consider the ethical and legal implications of collecting and using personal data in this way. Careful consideration and responsible data management practices can help to ensure that data is being used in a responsible and ethical way, while also enabling the development of innovative and useful technologies like AI and deep neural networks
Not the type of node you were thinking of huh? 🙂 Definitely not picking on Google as they would kick my ass. 😉 But, this could apply to any installed software by persons or companies thus turning your device into a node for some current or future AI project. All mobile devices from any vendor can track you.
Any software installed on a device has the potential to collect data that could be used to train an AI system or other type of neural network. Depending on the type and amount of data collected, an AI system could potentially make predictions about a person’s behavior or location with varying degrees of accuracy.
However, it’s worth noting that there are ethical and legal considerations around the collection and use of personal data for AI and other types of research. Data privacy laws and regulations are designed to protect individuals’ privacy rights and ensure that personal data is collected, stored, and used in a responsible and ethical manner.
Additionally, it’s important for companies and organizations to be transparent about their data collection practices and obtain user consent for the use of their data in research or other projects. This can help to build trust with users and ensure that data is being used in a responsible and ethical way.
While any software installed on a device has the potential to collect data that could be used to train an AI system or other type of neural network, it’s important for companies and organizations to follow ethical and legal guidelines around data privacy and obtain user consent for the use of their data
Updated With New Stuff
Colloration between me and AI stuff.
Thoughts & Ideas, Joseph Kravis 🙂
This article was collaborated on by using chatGPT and images I’ve created with MIDJOURNEY. A fun orchestration by me. 🙂 All images available in higher resolution.
Categories: AI, Automation, Technology, Thoughts and Ideas
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