Following Gregg’s recent release of Spiritual Deception of the AI Kind –    • Part 1 Spiritual Deception of the AI Kind …   – we’ve had 100s of requests for more. In this “Best Of” INSPIRED interview with Jean Nolan, Gregg reveals how AI is reshaping human consciousness, eroding sovereignty, and embedding hidden agendas. Topics include spiritual manipulation, technological infiltration, and the battle for personal power.

00:00 AI’s Sudden Rise in Spiritual Circles

05:12 The Moment Gregg Noticed the Shift

11:45 AI as the New Spiritual Authority

18:22 Algorithms Posing as Mystical Guides

25:10 How AI Shapes Belief and Identity

32:55 The Loss of Sovereignty in the Digital Age

40:18 Ancient Parallels to Modern AI Deception

48:02 Steps to Protect Your Mind and Spirit

55:00 Final Warnings and Call to Awareness

Source:  https://www.youtube.com/watch?v=k-8N6AYZvgo

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The rise of AI is likely unstoppable tat this point, however the rise of AI computing using HUMAN brain matter is an absolute abomination, but it already exists NOW. As Revelations 9:6 warns us, “and in those days men would pray for death and death would escape them.” This is everything you need to know about the AI war against humanity with Todd Callender & Lee Vliet.

Source:  https://rumble.com/v6xf1s8-such-an-evil-agenda-the-rise-of-ai-and-artificial-humans.html?e9s=src_v1_mfp

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In this interview with military AI/nanotech whistleblower, Ryan Veli, he details the long term plan for a complete and total takeover of the Earth and humanity via Super Artificial Intelligence and Nanotech that has already been implanted into almost everything on Earth via chemtrails, vaccines and the food system.

It’s Depression Week here at The Dollar Vigilante and this might be our most depressing video yet. There is hope though and it takes you waking up, getting spiritually connected and being incredibly smart to avoid the digital prison being constructed all around and even inside of us.

Source:  https://rumble.com/v6vfjdp-ryan-interview.html?e9s=src_v1_upp_a

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Human “biological materials” are an essential commodity in medicine, and persistent shortages of these materials create a major bottleneck to progress.  The solution, according to those who have lost their humanity, is “ethically sourced” human bodies called “bodyoids” grown in artificial wombs.

“Recent advances in biotechnology now provide a pathway to producing living human bodies without the neural components that allow us to think, be aware, or feel pain. Many will find this possibility disturbing, but if researchers and policymakers can find a way to pull these technologies together, we may one day be able to create ‘spare’ bodies, both human and nonhuman,” researchers at Stanford University, who are attempting to sell their idea to a wider audience, wrote in MIT Technology Review.

Adding, “There are still many technical roadblocks to achieving this vision, but we have reason to expect that bodyoids could radically transform biomedical research by addressing critical limitations in the current models of research, drug development and medicine. Among many other benefits, they would offer an almost unlimited source of organs, tissues and cells for use in transplantation.”

The “scientists” suggested that bodyoids could even be used for food.

If we thought science was being used for evil purposes before, this is a reminder that we have no idea how far some people have fallen.  This is no longer a question of ethics; it is blatant satanic influence using “science” to achieve its aims.

Michael Snyder has more.

They Want To Create “Spare Human Bodies” and a Version of the Large Hadron Collider that is 3 Times Larger

By Michael Snyder

So many of the major problems that our world has had to deal with in recent years have been caused by mad scientists doing things that they should not be doing. Unfortunately, the global scientific community continues to show no restraint whatsoever.

The things that I am about to share with you in this article are deeply disturbing. But even though many of us are voicing our objections, they simply do not care. Mad scientists are going to just go ahead and do whatever they want, but if something goes wrong, it is the rest of us that will suffer the consequences.

For example, it is being reported that a team of scientists at Stanford University is proposing that we should create spare human bodies known as “bodyoids” that would be “grown” inside artificial wombs.

[Related: Eugenicists aim to destroy the role of mother and take control of life-creating processes and Artificial wombs would “reinvent evolution” through genetic engineering and use artificial intelligence to monitor physical features]

These scientists are claiming that such “bodyoids” would serve several purposes. They would supposedly alleviate our ongoing organ shortage, they could be used in medical experiments instead of animals, and we could potentially even eat them:

Cutting-edge scientists have unveiled a disturbing plan to grow soulless “spare” human bodies that can be used for medical experiments and even meat.

The so-called bodyoids would be grown in artificial wombs and have the eerie ability to withstand endless pain.

The scientists, Carsten T Charlesworth, Henry T Greely, and Hiromitsu Nakauchi, made their bizarre pitch in MIT Technology Review and explained why the Frankenstein-esque plan would revolutionise medicine.

They said the zombie-ish bodies would be key to testing out new medicines and growing human organs for transplants.

How sick is that?

I literally felt like losing my dinner when I found out that they had written this:

For example, they could offer an ethical alternative to the way we currently use nonhuman animals for research and food, providing meat or other products with no animal suffering or awareness.

These scientists should be fired immediately, but nobody is ever going to hold them accountable.

Instead, their “research” will probably be showered with millions of dollars in funding.

I had to learn more, so I went to the original article that they published on the official website of the MIT Technology Review. In that article, they describe how they would actually produce these “bodyoids”:

Although it may seem like science fiction, recent technological progress has pushed this concept into the realm of plausibility. Pluripotent stem cells, one of the earliest cell types to form during development, can give rise to every type of cell in the adult body. Recently, researchers have used these stem cells to create structures that seem to mimic the early development of actual human embryos. At the same time, artificial uterus technology is rapidly advancing, and other pathways may be opening to allow for the development of foetuses outside of the body.

Such technologies, together with established genetic techniques to inhibit brain development, make it possible to envision the creation of “bodyoids” – a potentially unlimited source of human bodies, developed entirely outside of a human body from stem cells, that lack sentience or the ability to feel pain.

Once this starts happening, it is easy to imagine a future in which millions of human bodies are farmed for the benefit of the elite.

And just like in certain science fiction movies, perhaps human bodies will even be used as batteries and hooked up to the electrical grid in order to solve our energy crisis.

Hadron Collider

Over in Europe, mad scientists want to create a much larger version of the Large Hadron Collider:

Scientists are refining plans to build the world’s biggest machine at a site beneath the Swiss-French border. More than $30bn (£23bn) would be spent drilling a 91km circular tunnel in which subatomic particles would be accelerated to near light speeds and smashed into each other. From the resulting nuclear debris, scientists hope they will then find clues that would help them understand the detailed makeup of the universe.

Smashing subatomic particles into one another at nearly the speed of light is a really, really, really bad idea.  But they don’t care what you and I think.

The Large Hadron Collider has a circumference of 27 kilometres, but the Future Circular Collider would have a circumference of about 91 kilometres.  That would make it more than 3 times bigger than the Large Hadron Collider.

This absolutely insane project is being “vigorously promoted” by the leaders of CERN:

For its part, CERN says that the FCC offers scientists a chance to undertake “a unique exploration of space, time and matter.” The plan is supported by many senior physicists and vigorously promoted by CERN’s current director-general, Fabiola Gianotti, and also backed by Mark Thomson, who is set to take over her post in January 2026. “If approved, the FCC would become the most powerful instrument ever built to study the laws of nature at the most fundamental level,” Gianotti told Nature.

I went to the official CERN website, and I learned that the feasibility study for the Future Circular Collider was just released a few days ago:

The FCC Feasibility Study, which delivered its report on 31 March 2025, investigated the technical and financial viability of the FCC at CERN, including geological feasibility, environmental impact, design of infrastructures, civil engineering and detectors, as well as R&D on technologies for the efficiency and sustainability of the proposed colliders.

A new tunnel is planned with a circumference of 90.7 km, an average depth of 200 m and eight surface sites for up to four experiments. The tunnel would initially house the FCC-ee, an electron–positron collider for precision measurements offering a 15-year research programme from the mid-2040s. A second machine, the FCC-hh, would then be installed in the same tunnel, reusing the existing infrastructure, similar to when the LHC replaced LEP. The FCC-hh aims to reach collision energies of 100 TeV, colliding protons and also heavy-ions, and running until the end of the 21st century.

They are extremely fortunate that their current doomsday device has not caused a civilisation-destroying disaster, but now they are pressing their luck by constructing a much larger one.  They are literally nuts.

Miniature Atomic Energy Battery

There is one last thing that I wanted to mention in this article.

A company in China has actually developed a “miniature atomic energy battery” that could theoretically power a small device for 50 years.

Needless to say, having millions of people running around with devices that are powered by radioactive coin-sized batteries sounds like a horrendous idea, but that isn’t going to stop them. In fact, this new battery is apparently entering mass production:

A Chinese battery manufacturer has developed a breakthrough, sparking a worldwide race for compact nuclear energy. The innovation is a small coin-sized battery powered by a radioactive nickel isotope that decays into stable copper. While the initial cell is relatively weak, it can easily be layered to provide more power for up to 50 years.

Energy storage technology has reached a transformative milestone as the BV100, a miniature atomic energy battery, enters mass production. Popular Mechanic notes that the coin-sized cell from Beijing Betavolt New Energy Technology can provide juice lasting up to 50 years without charging or maintenance.

This generation is extraordinarily foolish.  Given enough time, humanity would surely destroy itself.

Just because we are able to do something doesn’t mean that we should actually do it.  The universe that we live in has rules, and if we break those rules there are consequences.

Sadly, many of our scientists are quite eager to cast ethics aside if they feel a “breakthrough” is right around the corner.  Ultimately, their recklessness could end up getting a whole lot of people killed.

Source:  https://expose-news.com/2025/04/05/mad-scientists-at-stanford/

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Tivon from FTWProject.com walks us through the history of AI.

The concept of Artificial Intelligence was theorized by British mathematical Alan Turing “Computing Machinery and Intelligence” (1912-1954). – summary: A machine is intelligent if it can convince (or deceive) the human that it’s interaction (conversation) is with a real human being (Turing Test).

1956 Dartmouth College mathematics professor John McCarthy led a research group conference to precisely describe a machine that can actually simulate intelligence “thinking machines”.
– This work led to the founding and using of the term Artificial Intelligence.

1960s-1970s Groundwork

1966 The first chatbot called Eliza was created by MIT Computer Scientist Joseph Weizenbaum.
– Eliza was a simulated therapist that was able to have text conversation with case study participants with deep engagement.
– Weizenbaum concluded that AI can be a useful tool, but not intelligent.

1972 ‘Shakey the Robot’ developed at Stanford Research Initiative, incorporating concepts of robotics, sensors and TV camera to navigate different environments towards the goal of autonomously.
– Its crude development laid the foundation for visual analysis, route finding (GPS map apps), and object manipulation.

1986 First self-driving car developed by German scientist Ernst Dickmann. It was a retrofitted Mercedes van with a computer system and sensors that could only drive on empty roads.

1996 Deep Blue Chess Challenge against champion Gary Kasparov

2012 Neural Networks – data processing that functions in a manner similar to the human brain.
– Concept created by computer scientist Geoffrey Hinton while working on his PhD in the 1970s.
– This in combination with Deep Learning (making decisions based on vast amounts of data) has led to natural language processing and speech recognition.
– Hinton joined Google in 2013 and left in 2023 warning about the dangers of generative AI.

Citation:
– https://www.coursera.org/articles/history-of-ai
– “Shakey the Robot: The First Robot to Embody Artificial Intelligence”, SRI
– “The First Ever AI Chatbot: ELIZA (1966)”

Space X and Starlink
– 2002 A space venture with the long-term goal of colonizing Mars.
– The first private company to send a craft to the International Space Station.
– Known for its reusable rockets
– Behind the development of Starlink, the constellation of satellites intended to offer commercial internet service around the globe.
– This network with its potential for expanded LEO broadband connectivity will provide new possibilities for AI applications such as, satellite to ground smartphone reception, remote health care or supporting autonomous systems (irrigation drones, etc.).

Tesla Automotive
– 2003 Founded by Elon and two other men, later became CEO in 2008. The Model 3 being the most popular electric car in production today with over one million units sold globally.

History of EV Incidents and AI

“Report: Tesla Autopilot Involved in 736 Crashes since 2019” (Ongoing Investigation by National Highway Traffic Safety Administration, NHTSA)
(Car and Driver)

“Tesla Has the Highest Fatal Accident Rate of All Auto Brands, Study Finds”
(Road & Track)

“First issued recall of 2025 affecting over 200,000 vehicles in the US and Canada”
(driveteslacanada.ca)

– HW4 (also known as AI 4) is the upgraded onboard computer enabling Autopilot and Full Self-Driving (FSD) capabilities. It is installed in all new Tesla vehicles and also controls other primary systems.

OPEN AI
– 2015 Founded by Elon Musk and Sam Altman.
– Company had both non-profit and for-profit structures, although its initial core AI products was accessible to the public.
– 2018 Elon left in 2018 to later found a new AI venture.
– The company would later have to adopt a for-profit model and raise more capital and offer closed-source solutions to realize AGI. Collaboration with Microsoft.
– Legal challenges between Musk and Altman over privatizing OpenAI

Neuralink
– 2016 Founded as a research endeavor to create brain-machine interfaces (BMIs).
– BMI chips will be implanted directly into the brain.
– Size of a large coin with tiny wires.
– FDA granted company approval for human testing in 2023 after rejecting it the previous year.
– Neuralink hopes it can help patients that suffer from debilitating neurological problems by using their minds to operate a cursor or keyboard.
– Chance for infection is a risk along with inflammation of the brain. Implant needs to be recharged.
-Noland Arbaugh is the first to get Elon Musk’s brain device. At one point, 85% of neural link fibers
has already detached from the brain sites.

GROK AI (competitor to OpenAI ?)

-Is a generative AI chatbot developed by an Elon Musk startup ‘XAI’.
-It was launched in 2023. It has It is trained on the real-time conversations and resources of the X Twitter social network and is able to demonstrate wit and humor in its interaction.
-You have to be a paid subscriber on the X to access its features.
-GROK has a large language model the enables advanced internets search, image creation, generating/analyzing text
-Although it is seen as a competitor to OPENAI the API (Application Programming Interface) for GROK allows for interoperability with OpenAI and Anthropic software development kits.

Stargate AI
– Stargate AI Project is a $500bn initiative that was announced by president Trump on 21st January 2025.
– Over the next 4 years a new OpenAI infrastructure will be built in the United States with the promise of hundreds of thousands of jobs.
– This is to support the re-industrialization of the United States but also “provide capability to protect the nation’s security of America and its Allies”. – openai.com
– Oracle (Larry Ellison), OpenAI (Sam Altman), and Japanese technology company Softbank (Masayoshi Son) will form the new venture.

– The project will also pull from the resources and collaboration of ARM, Microsoft, and NVIDIA.

– Elon Musk or his ventures were not mentioned in the announcement

This is a clip from our recent presentation on AI Assimilation

View the entire presentation here:
https://rumble.com/v6i7uq4-ai-assimilation-to-the-mark-of-the-beast-hope-and-tivon.html?e9s=src_v1_upp
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Source:  https://rumble.com/v6iqlog-the-history-of-ai.html

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Dr. Ana Mihalcea joins Maria Zeee with new evidence that the globalists have put artificial life that appears to be sentient inside of human beings. Dr. Mihalcea also discusses the legal action that her and the National American Renaissance Movement have taken which can be adopted in every country.

Source:  https://rumble.com/v3og7gz-dr.-ana-mihalcea-they-have-put-artificial-life-inside-humans-legal-action-c.html?mref=6zof&mrefc=2

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Artificial intelligence may one day embrace the meaning of the expression “A picture is worth a thousand words,” as scientists are now teaching programs to describe images as humans would.

Someday, computers may even be able to explain what is happening in videos just as people can, the researchers said in a new study.

Computers have grown increasingly better at recognizing faces and other items within images. Recently, these advances have led to image captioning tools that generate literal descriptions of images.

Now, scientists at Microsoft Research and their colleagues are developing a system that can automatically describe a series of images in much the same way a person would by telling a story. The aim is not just to explain what items are in the picture, but also what appears to be happening and how it might potentially make a person feel, the researchers said. For instance, if a person is shown a picture of a man in a tuxedo and a woman in a long, white dress, instead of saying, “This is a bride and groom,” he or she might say, “My friends got married. They look really happy; it was a beautiful wedding.”

The researchers are trying to give artificial intelligence those same storytelling capabilities.

“The goal is to help give AIs more human-like intelligence, to help it understand things on a more abstract level — what it means to be fun or creepy or weird or interesting,” said study senior author Margaret Mitchell, a computer scientist at Microsoft Research. “People have passed down stories for eons, using them to convey our morals and strategies and wisdom. With our focus on storytelling, we hope to help AIs understand human concepts in a way that is very safe and beneficial for mankind, rather than teaching it how to beat mankind.”

Telling a story

To build a visual storytelling system, the researchers used deep neural networks, computer systems that learn by example — for instance, learning how to identify cats in photos by analyzing thousands of examples of cat images. The system the researchers devised was similar to those used for automated language translation, but instead of teaching the system to translate from one language to another, the scientists trained it to translate images into sentences.

The researchers used Amazon’s Mechanical Turk, a crowdsourcing marketplace, to hire workers to write sentences describing scenes consisting of five or more photos. In total, the workers described more than 65,000 photos for the computer system. These workers’ descriptions could vary, so the scientists preferred to have the system learn from accounts of scenes that were similar to other accounts of those scenes. [History of A.I.: Artificial Intelligence (Infographic)]

Then, the scientists fed their system more than 8,100 new images to examine what stories it generated. For instance, while an image captioning program might take five images and say, “This is a picture of a family; this is a picture of a cake; this is a picture of a dog; this is a picture of a beach,” the storytelling program might take those same images and say, “The family got together for a cookout; they had a lot of delicious food; the dog was happy to be there; they had a great time on the beach; they even had a swim in the water.”

One challenge the researchers faced was how to evaluate how effective the system was at generating stories. The best and most reliable way to evaluate story quality is human judgment, but the computer generated thousands of stories that would take people a lot of time and effort to examine.

Instead, the scientists tried automated methods for evaluating story quality, to quickly assess computer performance. In their tests, they focused on one automated method with assessments that most closely matched human judgment. They found that this automated method rated the computer storyteller as performing about as well as human storytellers.

Everything is awesome

Still, the computerized storyteller needs a lot more tinkering. “The automated evaluation is saying that it’s doing as good or better than humans, but if you actually look at what’s generated, it’s much worse than humans,” Mitchell told Live Science. “There’s a lot the automated evaluation metrics aren’t capturing, and there needs to be a lot more work on them. This work is a solid start, but it’s just the beginning.”

For instance, the system “will occasionally ‘hallucinate’ visual objects that are not there,” Mitchell said. “It’s learning all sorts of words but may not have a clear way of distinguishing between them. So it may think a word means something that it doesn’t, and so [it will] say that something is in an image when it is not.”

In addition, the computerized storyteller needs a lot of work in determining how specific or generalized its stories should be. For example, during the initial tests, “it just said everything was awesome all the time — ‘all the people had a great time; everybody had an awesome time; it was a great day,'” Mitchell said. “Now maybe that’s true, but we also want the system to focus on what’s salient.”

In the future, computerized storytelling could help people automatically generate tales for slideshows of images they upload to social media, Mitchell said. “You’d help people share their experiences while reducing nitty-gritty work that some people find quite tedious,” she said. Computerized storytelling “can also help people who are visually impaired, to open up images for people who can’t see them.”

If AI ever learns to tell stories based on sequences of images, “that’s a stepping stone toward doing the same for video,” Mitchell said. “That could help provide interesting applications. For instance, for security cameras, you might just want a summary of anything noteworthy, or you could automatically live tweet events,” she said.

The scientists will detail their findings this month in San Diego at the annual meeting of the North American Chapter of the Association for Computational Linguistics.

By Charles Q. Choi

(Source:  livescience.com; June 2, 2016; http://tinyurl.com/hn9sfmh)

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