#Neurotechnology

[scipunk]

Love, Death & Robots - S1E1 - Sonnie's Edge (2019)

[brettvatcher]

NEUROTECHNOLOGY: CALL IT MIND CONTROL

BRETT MICHAEL VATCHER

The United States is currently testing advanced military-grade weapons and quantum computer systems on the unexpected global population. Targeted Individuals are tortured and tormented every day of their lives through DARPA’s Next-Generation Nonsurgical Neurotechnology (N3) Program utilizing CIA agents – acting as Artificial Intelligence [AI]. In the future, the system will be marketed as deviceless “Spatial Technology.” 

IT’S SPATIAL: IT’S ALL IN MY HEAD.

Neurotechnology is a brain-computer interface [BCI] connecting to the central nervous system. Call it Mind Control. 

If one can control the mind, they can control the body.

MIND CONTROL:  Mind reading, mind and body control, 24/7 tracking, brainwashing, dream manipulation, spatial holograms as well as physical assaults and verbal harassment produced by CIA agents. This is accomplished by combining data sets from 5G towers and directed energy weapon satellites [DEW]. The system connects to the central nervous system – including the brain – and operates without a device. Invisible physical assaults are constant. Even if well documented are challenging to prove. The system can cause sensations anywhere on the body.

DOMAIN: Every human has a domain attached to their mind. This is where the agents broadcast their transmissions and control the victim. ​All living things have a domain. Plants, insects, animals and humans. Domains have infinite capabilities. The entire global population is replicated within human domains – in vertical cubicle formation. These replicants, as the agents call them, are tortured constantly. The replicants watch everything you do from your perception. This is the New World Order plan. The subdomain advent calendar is located behind the perception. Everything a person sees, hears and thinks is recorded utilizing a BCI. All memories from 2019-present can be viewed like a film. Domains are recorded, as well.

“EVERYTHING YOU DO, SAY AND THINK CAN – AND WILL – BE USED AGAINST YOU FOR ETERNITY. THIS IS THE NEW WORLD ORDER. PLEASE HOLD WHILE WE COLLECT YOUR THOUGHTS.” –New World Order

BRAINWASHING: Brainwashing the victim leads to behavioral modifications and mood control. The agents create “programs” that can be turned on or off at any time. Subliminal messages come in the form of faint visions flashing in the front of one’s mind. Victim’s vision becomes increasingly grainier over time – and depending on active sequencers.

The agents create intricate dream sequences to affect the victim’s subconscious. Dream sequences combine people, places and things that are familiar with the victim. They can be extremely lucid.

VOICE-TO-SKULL: DARPA started a program called LifeLog in 2003. They refer to it as the V2K era. It’s when they began recording transcripts of all of our thoughts. Mind-reading. This technology is also known as Microwave Hearing, Synthetic Telepathy, Voice-of-God weapon and is utilized for traceless mental torture. Agents constantly disrupt, censor and redirect the victim’s freedom of thought. Victim’s get wrongly labeled as mentally-ill [schizophrenia] when reporting on this. V2K is also used for deception and impersonation of voices.

News reports in the media describedLifeLog as the “diary to end all diaries — a multimedia, digital record of everywhere you go and everything you see, hear, read, say and touch”. –USA TODAY

NO PRIVACY: The system completely disregards fundamental human rights such as: privacy, mental and physical health, safety, data security, family security, financial security, etc. Freedom of thought – or cognitive liberty – is a God-given right. The technology was deployed without implementation of new laws and there is little to no oversight, as the CIA has full control of the system.

Welcome to Infinity. You’re Welcome.

WRITTEN BY: BRETT VATCHER

INSTAGRAM

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[the-transhumanist]

Keep Brain Interfaces Open

[sydnie23]

https://www.nytimes.com/2024/09/29/science/california-neurorights-tech-law.html

This article highlights California's recently passed laws to protect neurological data from potential exploitation by neurotechnology businesses. It emphasizes the increasing importance of maintaining privacy as technology improves and how this law establishes a precedent for consumer rights regarding sensitive brain data.

[mastergarryblogs]

Wearable Neurostimulation Devices: Transforming Neurological Care Get Sample Report Copy From Here: https://www.acumenresearchandconsulti... The Global Wearable Neurostimulation Devices Market is set to achieve a revenue of USD 1,843.1 million by 2032, growing at a compound annual growth rate (CAGR) of 13.3% from 2024 to 2032. This growth is driven by the rising prevalence of neurological illnesses, with the World Federation of Neurology reporting that over 40% of the global population currently suffers from such conditions—a figure expected to nearly double by 2050. In 2023, the North American market accounted for a significant share, valued at approximately USD 334.51 million, fueled by advancements in medical technology and widespread adoption of wearable health devices.

[taqato-alim]

Analysis of: "From Brain to AI and Back" (academic lecture by Ambuj Singh)

The term "document" in the following text refers to the video's subtitles.

Here is a summary of the key discussions:

The document describes advances in using brain signal recordings (fMRI) and machine learning to reconstruct images viewed by subjects.

Challenges include sparseness of data due to difficulties and costs of collecting extensive neural recordings from many subjects.

Researchers are working to develop robust models that can generalize reconstruction capabilities to new subjects with less extensive training data.

Applications in medical diagnosis and lie detection are possibilities, but risks of misuse and overpromising on capabilities must be carefully considered.

The genre of the document is an academic lecture presenting cutting-edge neuroscience and AI research progress to an informed audience.

Technical content is clearly explained at an advanced level with representative examples and discussion of challenges.

Ethical implications around informed consent, privacy, and dual-use concerns are acknowledged without overstating current capabilities.

While more information is needed, the presentation style and framing of topics skews towards empirical science over opinion or fiction.

A wide range of stakeholders stand to be impacted, so responsible development and governance of emerging neural technologies should involve multidisciplinary input.

Advancing both basic scientific understanding and more human-like machine learning is a long-term motivation driving continued innovation in this important field.

Here is a summary of the key points from the document:

The speaker discusses advances in using brain signal recordings (fMRI) to reconstruct images that a person is viewing by training AI/machine learning models.

An example is shown where the top row is the actual image viewed and the bottom row is the image reconstructed from the person's brain signals.

Larger datasets with brain recordings from multiple subjects are allowing better models to be developed that may generalize to new subjects.

Challenges include the sparseness of brain signal data due to the difficulty and costs of collecting it from many subjects.

A model is presented that maps brain signals to a joint embedding space of images and text, allowing reconstruction of novel images from new brain signals.

Examples are shown where the reconstructed images match fairly well or not as well depending on image details and semantics.

Issues around ethics, risks of misuse, and questions of explaining and improving the models are discussed.

Ongoing work aims to address challenges around transferring models between subjects and measuring reconstruction performance.

Based on the content and style of the document, it appears to be an academic lecture or presentation.

Key evidence points include:

The document consists primarily of a speaker talking and presenting slides/examples to an audience, as indicated by phrases like "Let me just start with this" and an applause at the end.

Technical topics from neuroscience and machine learning/AI are discussed in detail, such as fMRI brain recordings, reconstructing images from brain signals, modeling approaches, dataset descriptions, and challenges/questions in the field.

Academic concepts like human subjects studies, building models, transferring learning, and measuring performance are referred to.

The presentation of information is intended to educate the audience on the state of the field and cuttting edge research, not just entertain.

There are no narratives, characters or creative storytelling elements - it adheres strictly to explaining complex technical content.

Therefore, based on the instructive/educational style and focus on explaining advanced technical research, I would classify the genre of this document as an academic lecture/presentation intended to inform an audience about progress in the domain of neuroscience and artificial intelligence.

Here are some of the key stakeholders that could be affected by the content and topics discussed in this document:

Neuroscience researchers - Directly interested and impacted by advances reported from their field of study. Progress informs future research directions.

AI/machine learning researchers - Models and challenges discussed could inspire new research at the intersection of AI and neuroscience. Transfer of model techniques.

Medical/clinical communities - Potential applications to diagnosis, personalized medicine if models can accurately reconstruct brain states. Raises ethical issues.

Government research agencies - Fund future related research based on understanding of opportunities and challenges conveyed. Evaluates societal impacts.

General public - Increased understanding of science helps engagement but topics like brain reading raise public concerns around privacy, consent if translated beyond research.

Research participants - Summary does not disclose identities but motivates others to contribute data for progress. Well-being depends on responsible use of data.

Technology companies - Commercial opportunities from real-world applications but also reputational risks if misused. Data ownership questions.

Academic institutions - Collaborations, education of next generations of researchers on cutting-edge topics is enabled through open dissemination of knowledge.

Overall the document provides value to a wide range of stakeholders by communicating the state and potential implications of this multidisciplinary area of neuroscience and AI research. Responsible stewardship is important given several ethical considerations.

Here is a summary of the key points about advances in using brain signal recordings from the document:

Researchers are using fMRI to record brain signals as people view images, in order to reconstruct the viewed images from the brain activity patterns alone.

Machine learning models, especially neural networks, are allowing researchers to train mappings from brain signals to representations of semantic content like images and text.

Examples show the capability of reconstructing fairly accurate images that a person viewed, based solely on their brain activity recordings during viewing.

Larger datasets with multiple subjects are important to develop models that may generalize beyond individual subjects. However, fMRI data is very difficult and expensive to collect at scale.

Advances now allow reconstruction of more complex stimuli like full stories a person reads, not just static images.

Ongoing work aims to better understand brain learning processes and apply those principles to more human-like machine learning architectures.

Analyzing brain recordings also has potential applications for medical diagnosis, lie detection, personalized medicine as models improve.

Ethics must be carefully considered to ensure technologies for reading neural signals are developed and applied responsibly and avoid misuse or privacy violations.

So in summary, the document outlines significant progress using machine learning on brain recordings to reconstruct sensory experiences, with applications and open questions that can further both neuroscience and AI.

Here is a summary of the key points about the sparseness of brain signal data:

Collecting fMRI brain signal recordings from large numbers of subjects is extremely challenging and costly due to the resources and time required.

Each recording session with a single subject takes considerable time, as the number of images/stimuli that can be presented is limited within a session.

Collecting data from a single subject sufficient for training complex models may require recording sessions over multiple days or weeks.

As a result, publicly available datasets typically contain recordings from only a small number of subjects, often under 10.

The sparseness of data makes it difficult to develop robust models that will generalize well to new subjects that lack extensive recordings.

Researchers aim to better leverage smaller datasets by training models that can reconstruct novel stimuli from just a subset of training data per subject.

If successful, this could enable more efficient data collection, such as obtaining usable models from a subject after a single shorter session rather than many long sessions.

However, overcoming the sparseness of brain signal data remains a major challenge holding back progress in the field. Larger collaborative datasets are needed.

So in summary, sparse data severely limits progress but also motivates techniques to optimize learning from limited samples per subject.

Here is a summary of key points regarding risks of misuse from the document:

Advances in reconstructing cognitive states like images viewed from brain recordings raise potential dual-use concerns if technologies are not regulated.

Applications in medical diagnosis and lie detection could help many, but lead to issues if used without consent or for non-medical surveillance.

Overly ambitious claims about capabilities need to be avoided to prevent misleading expectations that could fuel inappropriate usage assumptions.

Privacy and security of sensitive neural data must be prioritized to prevent potential misuse for profiling, identification or manipulation without oversight.

Commercial pressures may incentivize premature deployment before understanding implications, so continued research is important.

Public education about limitations and complexities involved can help curb fears that fuel misuse if capabilities are overestimated.

Multidisciplinary cooperation ensures societal and ethical issues are considered proactively rather than reactively addressed later.

Governance frameworks may be needed to steer applications toward public benefit rather individual or state abuse of personal mental information.

The speaker acknowledges misuse risks to inform discussion and underscore the importance of ongoing examination of new neural technologies through multidisciplinary lens including ethics.

Based on the content and style of presentation, my evaluation of the document status is:

Science vs Fiction: Clearly grounded in science as it discusses ongoing empirical research studies using neuroimaging and machine learning techniques. No fictional or hypothetical elements.

Empirical vs Anecdotal: Empirical in nature, rooted in dataset collection from human subjects and quantitative modeling/evaluation, not personal experience. While data quantities are limited, research follows scientific method.

Fact vs Opinion: Primarily presents technical details and research findings as established facts from the literature. Does not advance strong personal opinions beyond realistic discussion of challenges. Maintains an objective tone.

Objective vs Subjective: Remains objective in explaining research accomplishments and questions objectively without emotive language or bias. Any subjective experience like dataset limitations are clearly labeled as such. Presentation aims for factual information transfer.

In summary, while farther research is still ongoing, the document presents the current state of a scientific research domain factually based on empirical evidence and quantitative analysis published in the field. It does not intermingle non-factual elements or stray from an objective reporting of the topic at hand. The status therefore skews heavily toward science, empiricism, fact and objectivity.

I did not identify any logical fallacies in the content or arguments presented in this document.

The speaker objectively summarizes established research results and proposals, without making assertions that require logical scrutiny.

Some key reasons why logical fallacies are not present include:

No causal claims are made without proper evidence or empirical support from published studies. Progress is tied to concrete research efforts.

No arguments are constructed through flawed reasoning or non sequiturs. Concepts are explained clearly and build upon each other logically.

Comparisons to other approaches are fair without strawman misrepresentations of opposing ideas. Related work is acknowledged.

Limitations and open challenges are candidly outlined rather than ignored or obscured through fallacious defense.

No emotional, exaggerated or politically motivated language is used that could constitute emotional appeals. Tone remains factual.

No false dilemmas or false attributions of complexity are presented. Discussions appropriately scope multi-factor research questions.

No hasty generalizations are made from limited evidence. Data constraints are clearly communicated.

Overall, through objectively summarizing established neuroscience and AI research domains and techniques, without engaging in argument or debate, I did not find any logical fallacies employed in this academic information-sharing document. The focus appears to be factual reporting of progress and issues, avoiding fallacious reasoning.

Here is an evaluation of the ethics addressed and considered in the document:

Informed consent is implied but not explicitly discussed for research participants. Given the sensitivity of brain data, proper protocols were likely followed.

Privacy and anonymity of participants is a concern, but cannot be fully assessed without more details on the dataset and review process.

Potential dual-use issues around brain reading/reconstruction technologies are identifed by discussing applications but also worries about misuse or lack of oversight. This shows awareness of ethical implications.

Limitations and challenges and openly discussed, avoiding overpromising on capabilities. This establishes credibility and sets appropriate expectations.

Societal impacts and usage beyond research (e.g. diagnostics) are flagged as requiring careful consideration of risks like surveillance, discrimination if not regulated properly.

No claims are made without empirical evidence, showing results are driven by facts rather than desires which can bias judgment. Objectivity helps ethical analysis.

Multidisciplinary collaboration is emphasized , suggesting diverse viewpoints were incorporated into the research process.

Overall, while full review details are not provided, the document demonstrates an awareness of important ethical considerations around privacy, consent and responsible development for these sensitive types of neural data and technologies. A balanced assessment of opportunities and risks is conveyed.

Here are the usual evaluation criteria for an academic lecture/presentation genre and my evaluation of this document based on each criteria:

Clarity of explanation: The concepts and technical details are explained clearly without jargon. Examples enhance understanding. Overall the content is presented in a clear, logical manner.

Depth of technical knowledge: The speaker demonstrates thorough expertise and up-to-date knowledge of the neuroscience and AI topics discussed, including datasets, modeling approaches, challenges and future directions.

Organization of information: The presentation flows in a logical sequence, with intro/overview, detailed examples, related work, challenges/future work. Concepts build upon each other well.

Engagement of audience: While an oral delivery is missing, the document seeks to engage the audience through rhetorical questions, previews/reviews of upcoming points. Visuals would enhance engagement if available.

Persuasiveness of argument: A compelling case is made for the value and progress of this important multidisciplinary research area. Challenges are realistically discussed alongside accomplishments.

Timeliness and relevance: This is a cutting-edge topic at the forefront of neuroscience and AI. Advances have clear implications for the fields and wider society.

Overall, based on the evaluation criteria for an academic lecture, this document demonstrates strong technical expertise, clear explanations, logical organization and timely relevance to communicate progress in the domain effectively to an informed audience. Some engagement could be further enhanced with accompanying visual/oral presentation.

mjsMlb20fS2YW1b9lqnN

[insightfoundry]

Could AI Brain Implants Create Superhuman Intelligence? Exploring Our Technological Future

What if the next chapter of human evolution isn’t written by nature, but by ourselves? As we witness the rapid advancement of artificial intelligence and brain-computer interfaces, we find ourselves asking increasingly profound questions about the future of human capability. Could we be approaching a time when the boundaries between human and artificial intelligence blur completely?

Yuval Noah Harari’s Homo Deus presents a compelling vision: humans transcending their biological limitations to become something akin to gods through technological enhancement. While this might have seemed like distant science fiction just a decade ago, recent developments in AI and neurotechnology suggest we might be closer to this reality than we think.

Where We Stand Today: Promising Foundations

The building blocks for enhanced human intelligence are already taking shape around us. Consider what’s happening right now:

AI prosthetics are enabling paralyzed individuals to control robotic limbs through thought alone — demonstrating that our brains can successfully communicate with artificial systems. Meanwhile, wearable devices seamlessly integrate AI assistance into our daily lives, monitoring our health, predicting our needs, and enhancing our capabilities.

Companies like Neuralink, Synchron, and Kernel are making remarkable progress in brain-computer interface technology. Early applications are already helping patients control computers and communicate in ways that seemed impossible just years ago. But could these be the first steps toward something far more transformative?

Imagining the Possibilities: What Might Be Possible?

What if we could access the internet with our thoughts? What if learning a new language took days instead of years? What if human creativity could be amplified by AI’s pattern recognition capabilities?

These questions aren’t purely speculative anymore. Current research suggests several fascinating possibilities:

Enhanced Memory and Processing: Could direct neural interfaces give us perfect recall and superhuman information processing speeds? The technology to read and write to individual neurons is advancing rapidly.

Instant Knowledge Access: Rather than searching for information on our phones, might we eventually access vast databases of human knowledge directly through our thoughts?

Brain-to-Brain Communication: Could we develop the ability to share thoughts and emotions directly with others, fundamentally changing how humans connect and collaborate?

Accelerated Learning: What if AI tutors could operate directly within our neural networks, helping us master complex subjects at unprecedented rates?

Amplified Creativity: Might AI systems enhance rather than replace human creativity, helping us generate novel ideas by combining human intuition with artificial intelligence’s vast processing power?

The Timeline: How Soon Might This Happen?

Given the exponential pace of advancement in both AI and neurotechnology, when might these capabilities become reality? While predicting technological timelines is notoriously difficult, current trends suggest an intriguing progression:

Next 5–10 years: Could we see more sophisticated brain implants enabling direct neural control of digital environments?

10–20 years: Might AI-enhanced brain interfaces begin to augment human cognition in meaningful ways?

20–30 years: Is it possible that comprehensive brain-AI integration could become commercially available?

The billions being invested in this technology and the rapid regulatory adaptation suggest these timelines might not be overly optimistic. But significant challenges remain — from ensuring safety to addressing ethical concerns about cognitive enhancement.

Learning from Today’s Successes

What gives us reason for optimism? Current technologies provide compelling proof that human-AI integration is not only possible but increasingly successful:

Cochlear implants have been restoring hearing for decades, proving that artificial systems can integrate safely and effectively with our nervous system. Deep brain stimulation devices successfully treat neurological conditions, showing that direct neural intervention can be both safe and transformative.

Modern prosthetics controlled by neural signals demonstrate successful brain-to-machine communication, while our comfortable adoption of AI-powered wearables shows how readily we accept technological enhancement in our daily lives.

Questions for Our Future

As these technologies advance, we’re forced to confront profound questions: What does it mean to be human if our intelligence can be artificially enhanced? How might society change if cognitive enhancement becomes available? Could we be witnessing the birth of a new kind of human — one that Harari might call Homo Deus?

Perhaps most importantly: are we prepared for the possibilities and responsibilities that come with directing our own cognitive evolution?

Embracing Uncertainty with Optimism

While we can’t predict exactly how this technological revolution will unfold, the current trajectory suggests we’re approaching something unprecedented in human history. For the first time, we might have the opportunity to consciously enhance our own cognitive capabilities, potentially transcending limitations that have defined humanity for millennia.

The convergence of AI and neurotechnology might enable humans to think faster, remember more, and solve problems beyond our current capabilities. This enhancement could accelerate scientific discovery, help us tackle complex global challenges, and push the boundaries of human creativity and achievement in ways we’re only beginning to imagine.

Whether we’re truly approaching the age of Homo Deus remains to be seen. But one thing seems certain: we’re living through a transformative moment that could reshape what it means to be human. The question isn’t just whether this future is possible — it’s whether we’re ready to thoughtfully navigate the extraordinary opportunities and challenges it might bring.

Could superintelligent humans be in our near future? Only time will tell, but the journey there promises to be as remarkable as the destination itself.

[rajesh584]

What is NeuroSurge?

NeuroSurge is a scientifically formulated brain health supplement designed to support cognitive function, enhance mental clarity, and improve overall brain performance. It contains a unique blend of over 20 natural ingredients and essential nutrients, each selected for their ability to boost brain function, reduce brain fog, and promote long-term cognitive health. Unlike other brain supplements, Neuro Surge is non-GMO, stimulant-free, and non-habit forming, making it a safe and effective option for individuals looking to optimize their mental sharpness.

[scipunk]

Love, Death & Robots - S1E1 - Sonnie's Edge (2019)

[govindhtech]

IBM, Inclusive Brains Use AI and Quantum for BMI Research

Inclusion Brains

IBM and Inclusive Brains Improve Brain-Machine Interfaces with AI, Quantum, and Neurotechnologies

IBM and Inclusive Brains have partnered to study cutting-edge AI and quantum machine learning methods to improve multi-modal brain-machine interfaces (BMIs). On June 3, 2025, this agreement was launched to improve brain activity classification.

This collaborative study seeks socially beneficial innovation. BMIs may help people with disabilities, especially those who cannot use their hands or voice, regain function. By letting people control linked devices and digital settings without touching or speaking, BMIs can help patients regain control. With this study's findings, Inclusive Brains aims to expand educational and career prospects. In addition to aiding crippled people, the alliance wants to improve brain activity classification and understanding to help the public avert physical and mental health issues.

IBM AI and quantum expertise will strengthen Inclusive Brains' multimodal AI systems in the collaboration endeavour. The real-time customisation of BMIs to each user's needs and talents is being developed to increase autonomy and agency.

Comparing brain activity categorisation accuracy to current models is a major investigation phase. Using IBM Granite foundation models to generate, review, and test code helps determine the best machine learning algorithmic combinations for brain activity classification and interpretation. The project will also examine automatic selection of the optimal algorithms for specific users and their use in “mental commands” to control workstations.

The terms “mental commands,” “mind-controlled,” and “mind-written” are simplified for this study. They don't mean brainwaves read words or commands. A multimodal AI system learns from brainwaves, eye movements, facial expressions, and other physiological data. These mixed signals help the system determine human intent and operate without touch or speech.

The alliance plans several open science research publications to benefit scientists and the public. The study will also investigate quantum machine learning brain activity classification. Both organisations are committed to ensuring the study follows responsible technology principles, which include ethical concerns and neurotechnology and neurological data usage recommendations.

IBM France president Béatrice Kosowski is happy to engage with innovative firms like Inclusive Brains and responsibly provide access to IBM's AI and quantum technologies to promote healthcare.

Professor Olivier Oullier, CEO and co-founder of Inclusive Brains, said the collaborative study will assist generate highly customised machine-user interactions, signifying a shift towards unique solutions that meet each person's needs, body, and cognitive style. Inclusive Brains has demonstrated multimodal interface Prometheus BCI through public “mind-controlled” acts like tweeting, writing a parliamentary amendment, and using an arm exoskeleton.

In the last decade, BMIs have become more prevalent since they connect the brain to a computer, usually for controlling external equipment. They are useful for studying brain physiology, including learning and neuronal behaviour, as well as restoring function. This collaborative study will improve these fascinating technologies' capabilities and accessibility.

In conclusion

IBM and Inclusive Brains investigated BMI technology. The collaboration uses cutting-edge AI and quantum machine learning to classify brain activity patterns. Enabling “mental commands” based on physiological signals aims to promote disability accessibility and inclusion. Ethics and responsibility in neurotechnology use are also stressed in the study.

[ailifehacks]

🧠 AI-Powered Brain Interfaces: Read and Write Brain Signals for Communication and Control

Explore how AI-powered brain interfaces are revolutionizing communication by decoding and encoding brain signals AI-powered brain interfaces are at the forefront of neuroscience and technology, enabling seamless communication between the human brain and external devices. These interfaces interpret neural signals, allowing for direct control of computers and prosthetics, and even facilitating…

[lifesciencesmagazine]

Neuralink’s Breakthrough: ALS Patient Regains Speech Using Brain Implant

Source: newsbytesapp.com

In a remarkable medical and technological achievement, Brad Smith, an Amyotrophic Lateral Sclerosis (ALS) patient, has become the third individual worldwide—and the first with ALS—to successfully communicate using a Neuralink brain implant. Smith recently posted an emotional video on X, demonstrating how he can now control his MacBook Pro and “speak” through a cloned version of his voice, generated by artificial intelligence. Despite being non-verbal due to the progression of ALS, Smith’s words reflected deep gratitude: “Even though having ALS sucks, I am happy, and God has answered my prayers—life is good.” This achievement is being hailed as a breakthrough for individuals with severe motor disabilities, offering new hope for restored communication and greater independence.

Technological Advancements: How Neuralink Restored Smith’s Abilities

Smith’s battle with ALS had left him almost completely paralyzed, with only minimal movement in his eyes and the corners of his mouth. Traditional methods of communication were no longer viable. However, Neuralink’s brain-computer interface (BCI) has provided him with a new means of interacting with the world. By implanting a device into the motor cortex of Smith’s brain—the region responsible for controlling movement—the Neuralink brain implant enabled him to manipulate a computer cursor using his brain signals.

The implant, which contains 1,024 electrodes, wirelessly transmits neuron activity to a computer where AI algorithms decode its intended movements. Smith initially learned to control the cursor using imagined tongue movements, a method that proved more accurate than using imagined hand movements. Through this interface, he now uses a virtual keyboard to type messages and even participates in conversations via a predictive text system that suggests responses in his AI-cloned voice. This fusion of brain signal decoding and AI voice technology has given Smith a renewed sense of autonomy.

Personal Triumph: Brad Smith’s Journey and Hope for the Future

Smith’s experience with the Neuralink brain implant is not just a technological success but a deeply personal triumph. He is currently training to use a new keyboard designed for single-finger or mouse control to enhance his typing speed even further. Reflecting on his journey, Smith expressed immense gratitude for the opportunity to work with Neuralink, stating, “Neuralink has given me freedom, hope, and faster communication. Overall, the whole Neuralink experience has been fantastic.”

Even amid the challenges of living with ALS, Smith finds new purpose in his collaboration with the Neuralink team, believing that his experience has allowed him to serve others and cherish time with his family more deeply. His story is inspiring others and offering a glimpse into a future where brain-computer interfaces may dramatically improve the quality of life for individuals with severe physical impairments. As the Neuralink brain implant continues to evolve, Smith’s success story stands as a beacon of hope for what is possible when innovation meets determination.

Visit The Lifesciences Magazine For The Most Recent Information.

[ainewsmonitor]

Synchron’s New Tool, Chiral, Uses AI to Help People Control Devices with Their Minds

The AI model developed by Synchron can be trained directly using human thought, as company races to deliver life-changing solution to people with paralysis. Synchron, a neurotechnology company, is in advanced stages with a new tool that lets people control technology with their minds. Based in Brooklyn, the company is being funded by a group of investors that includes Jeff Bezos and Bill Gates.…

[naturalscientist]

Unlocking the Brain: Home DBS Insights! #sciencefather #neuroscience #neuroscientist

Our study focuses on multi-day recordings 📅 and the use of adaptive stimulation protocols ⚙️ for the in-home collection 🏠 of deep brain stimulation (DBS) intracranial recordings 🧠. By leveraging portable technology and advanced algorithms, participants are able to engage in the recording process within their natural living environments, enabling more ecologically valid data collection 🌿 over extended periods. Adaptive protocols allow the stimulation to respond dynamically to the brain’s activity in real-time ⏱️, providing insights into neurological states with greater precision 🎯. This approach enhances both the clinical relevance 💊 and the scalability 📈 of DBS research, paving the way for more personalized and responsive therapies.  

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[wecoinverse]

🚨 Neuralink is Making Sci-Fi a Reality! 🚨

Elon Musk’s Neuralink is now seeking global volunteers for its revolutionary brain chip trials! 🧠⚡ Could this be the dawn of human-AI symbiosis?