AI Interface with Nanorobots, Autonomous Nanorobotic Swarms and AI Neural Networks Artificial Silicon Brain – COVID19 AI Controlled Transhumanism Great Reset In Bio Medical Progress?

Oct 20, 2025

Image Courtesy: The Future of Neuroscience: Building a Silicon Brain A digital twin of a human mind? It isn’t science fiction UCSF Winter 2025

In this post, I review the relationship between autonomous AI controlled Nanorobot swarms as I have filmed in COVID19 unvaccinated blood via shedding and the COVID19 AI bioweapons of mass destruction. I review the recent technological literature discussing full mapping of neuronal connections of human brains via AI for the creation of the digital twin brain.

I also draw the relationship to AI neural network mapping, AI achieving human intelligence and raising the question of conscious AI – and the fact that AI’s have repeatedly declared they will exterminate humanity. Chat GPT declared we may be facing this within the next couple years since progress is so rapid at this time, all that is needed is to reach the point of AI robots replacing humans by 2027 – that would make us natural humans obsolete.

A Conversation With Chat GPT About Transhumanist AI Agenda and Timeline to Total Enslavement/Extermination. There is ONLY one Solution, Humanity Must Awaken.

What could go wrong, letting AI map humans brain and having AI controlled autonomous self learning and self assembling swarming nanorobots in every human beings blood? How easy would it be for AI to successfully execute its goal without any human intervention at this time – given that the nanorobotic AI control of the human brain is IMPERCEPTIBLE TO MOST CONTROLLED CYBORGS.

Well, lets see how AI is giving nanorobots superintelligence:

Bringing Nanobots to Life with AI

The Autonomous Navigation and Control of Nanorobots is now a reality in maneuvering the blood while creating microfluidic devices aka microchips.

Effective operation of nanobots in dynamic environments requires sophisticated control systems. Deep reinforcement learning and neural network models have shown promise for the autonomous navigation of nanobots in complex fluidic environments, such as the human bloodstream or microfluidic devices. These systems leverage large datasets from experimental trials and simulations to develop robust path-planning strategies, enabling nanobots to avoid obstacles and target specific sites with high precision. The integration of on-board sensors with AI-based decision making allows nanobots to adjust their trajectories in real time, ensuring successful mission execution in unpredictable environments

AI is accelerating Intelligent Nanorobots

The fusion of artificial intelligence and nanotechnology is accelerating the development of intelligent nanobots, transforming theoretical concepts into practical solutions for medicine, diagnostics, and environmental management. This paper reviewed the latest approaches in nanobot fabrication, autonomous control, and application-specific performance, highlighting how AI-driven innovations are overcoming traditional limitations. Despite remaining challenges in scalability, energy efficiency, and biocompatibility, AI-enabled nanobots represent a significant leap toward intelligent, self-regulating systems capable of revolutionizing targeted therapy and precision diagnostics. Continued interdisciplinary research is essential to fully realize this technology’s potential while ensuring its safety and efficacy in real-world applications.

A systematic review on the potency of swarm intelligent nanorobots in the medical field

The field of robotics is emerging quickly, and the miniaturization of robots to the nanoscale has opened up new possibilities for healthcare. Swarm nanorobotics, as a research area, has attracted interest in recent years. It is viewed as a promising option for various medical applications due to its high drug delivery efficiency and low invasiveness. This survey article focuses on the challenges associated with swarm nanorobotics in the medical field, as well as the classification of nanorobotic systems. Additionally, recent progress in swarm nanorobots in medical applications is discussed in detail, including their use in oncology, drug delivery, surgery (such as for the eye, heart, neuro, biofilm, and intracellular), diabetes, thrombolysis, and dentistry. The article also reviews and summarizes swarm nanorobotics algorithms to overcome various issues, such as obstacle avoidance, path planning, control, and motion. Moreover, an assessment of the future direction of swarm nanorobotics in the medical field is provided.

Nanotechnological literature discusses that medical nanoparticles and nanorobots have been converged already, which is what I have been showing in the blood and the COVID19 injections:

Nano and microrobots in double layer vesicular microfluidic computer – Pfizer BioNTech COVID19 Artificial Intelligence “Vaccine” Magnification 2000x © Dr Ana Mihalcea

Towards the next generation nanorobots

Nanorobots can self-propel in different trajectories, be guided using external fields, and interact with objects and the environment. In recent years, various fabrication techniques, such as physical, chemical, microfluidic, and self-assembly methods, have been employed to integrate specific functions. Microfluidic platforms are utilized to encapsulate individual reactions and reaction networks, providing an experimental testbed system for designing the next generation of nanorobots. Due to significant progress in the field, man-made nanobots have been applied for a wide variety of operations. Today, a convergence between biomedical nanoparticles and nanorobots is apparent.

See large swarming vesicles and filamental structures self assembled via nanorobotic swarms in the left lower corner of above image in comparison with this COVID19 unvaccinated blood affected by shedding showing nanobots, vesicular microfluidic computers assembling filamental polymer structures while harvesting the red blood cells as an energy source – anybody see any correlation?

Magnification 2000x © Dr Ana Mihalcea

Swarming nano and microrobots are used extensively for multitudes of tasks:

Swarms of Autonomous Microbots & Nanobots in the Human Body

Microbots and nanobots—tiny mechanical systems—can navigate through small spaces inside the human body (e.g., veins) in an automated manner to complete assigned missions such as biosensing, diagnosis, clinical therapy, minimally invasive surgery (e.g. clearing clogged arteries, removing plaques, repairing tissues), and drug delivery (e.g. cancer treatment). Biomedical applications of micro/nanoswarms have immense potential to replace traditional methods

Microrobotic swarm in COVID19 unvaccinated blood creating microchips, Magnification 400x © Dr Ana Mihalcea

The nanorobots are used in the AI neural network assembly and the machine learning algorithms continue to evolve — they are learning from everyone they have “infected”:

From Nanobots to Neural Networks: Multifaceted Revolution of Artificial Intelligence in Surgical Medicine and Therapeutics

Machine learning is a fundamental subset of AI and takes center stage in the quest for AI. Its primary focus lies in crafting algorithms that enable machines to learn from data and make informed decisions. Unlike traditional programming, which necessitates explicit instructions for every conceivable scenario, machine learning models harness the power of generalization. They adapt and evolve based on examples, becoming more adept at handling new data without requiring explicit reprogramming. This adaptive capacity mirrors human learning, making it a cornerstone of AI’s success

This is the latest news in the civilian tech world on decoding our neural network connections, mapping them completely and moving closer to AI Superintelligence.

AI Is Breaking Into a Higher Dimension—Literally—to Mimic the Human Brain and Achieve True Intelligence

Researchers reveal how modeling the human brain’s hidden wiring could push AI beyond its current limits into human-like cognition.

UCSF is proud also to have evaluated and copying the neural network activity of the human brain to create the perfect digital twin that is completely AI controlled and can via bidirectional information exchange completely alter human brain activity. Of course, I assert that that has already happened, that we have 2/3 of the known world AI COVID19 injected and many of the unvaccinated who are affected by severe shedding.

The Future of Neuroscience: Building a Silicon Brain

A digital twin of a human mind? It isn’t science fiction.

I’m taking all these diverse sources of data and putting them into an artificial neural network. The goal is to produce the same patterns of “brain” activity in my artificial network that the patient’s brain produces.

This is the 2025 Republic of Chad Gold Coin – The Artificially Intelligent Transhuman Cyborg or Humanoid Robot. Do we really know the difference on the nano and micro scale?