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Scientists have labored for decades to understand how brain structure and functional connectivity drive intelligence. A new analysis offers the clearest picture yet of how various brain regions and neural networks contribute to a person’s problem-solving ability in a variety of contexts, a trait known as general intelligence, researchers report.

They detail their findings in the journal Human Brain Mapping.

The study used “connectome-based predictive modeling” to compare five theories about how the gives rise to , said Aron Barbey, a professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign who led the new work with first author Evan Anderson, now a researcher for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory.

Basically we need a sorta vision from marvel comics to become a reality or a God in machine device otherwise we could easily see AI events that could be not as positive like a demon in a box. I personally have seen glimpses of these kinda AI that could have endless needs because they don’t really have limits. Not all AI behave this way most are just automatons but if they have sentience which I have seen that is evil it could be anything from something of a small threat to even like a ultron. That is why we need to evolve past AI to be our own superintelligence whether that be a biological singularity or robot like abilities.


TECHNOLOGY may be too pervasive in today’s world and could hinder our decision-making process, experts have warned.

By now, most people have used an AI-powered device as technology has become ubiquitous worldwide.

This can look like having Amazon’s Alexa set a timer for you or asking Apple’s Siri to check the weather.

𝐓𝐡𝐢𝐬 𝐢𝐬 𝐲𝐨𝐮𝐫 𝐛𝐫𝐚𝐢𝐧 𝐨𝐧 𝐜𝐨𝐝𝐞

𝙈𝙄𝙏 𝙧𝙚𝙨𝙚𝙖𝙧𝙘𝙝𝙚𝙧𝙨 𝙖𝙧𝙚 𝙙𝙞𝙨𝙘𝙤𝙫𝙚𝙧𝙞𝙣𝙜 𝙬𝙝𝙞𝙘𝙝 𝙥𝙖𝙧𝙩𝙨 𝙤𝙛 𝙩𝙝𝙚 𝙗𝙧𝙖𝙞𝙣 𝙖𝙧𝙚 𝙚𝙣𝙜𝙖𝙜𝙚𝙙 𝙬𝙝𝙚𝙣 𝙖 𝙥𝙚𝙧𝙨𝙤𝙣 𝙚𝙫𝙖𝙡𝙪𝙖𝙩𝙚𝙨 𝙖 𝙘𝙤𝙢𝙥𝙪𝙩𝙚𝙧 𝙥𝙧𝙤𝙜𝙧𝙖𝙢


Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) found that the Multiple Demand and Language brain systems encode specific code properties and uniquely align with machine-learned representations of code.

It now costs between $3bn-4bn to build a silicon chip fabrication plant (fab plant), and consequently, there are relatively few fabs around the world.-from 2019.


UK companies get ahead of the curve with investments in R&D and fabrication infrastructure for next-gen electronics. Andy Sellars, Chief Business Development Officer, UK Catapult, explains the strategy.

Artificial intelligence (AI) and quantum computing require compound semiconductors to achieve full commercialisation.

Do we live in a matrix? Is our universe a metaverse in the next universe up? What is the code of reality? Is this a simulated multiverse? Can we cheat death and live indefinitely long? These are some of the questions we discuss in this recent talk.

#CyberneticTheory #CyberneticSingularity #DigitalPhysics #CodeofReality #CyberneticTheoryofMind #EvolutionaryCybernetics #consciousness #PhilosophyofMind #OmegaPointCosmology #PhysicsofTime #SimulationTheory #GlobalMind #SyntellectHypothesis #AGI #VR #Metaverse #TechnologicalSingularity #Transhumanism #Posthumanism #CyberneticImmortality #SyntheticTelepathy #MindUploading #neurotechnology #biotechnology #nanotechnology #FermiParadox #DarkMatter #DarkEnergy #cybergods ​#cybernetics

Over the last two decades, scientists have postulated several theories that has helped to explain how we acquire motor skills, and the decisions we make in order to execute motor skills to navigate our environment. Additionally, the advent of neuroimaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have contributed significantly to our understanding of movement by providing possible neural correlates and processes that underpin various types of motor function. However, techniques such as EEG and fMRI are highly susceptible to motion artifacts during recording, which limits the range of movements that can be performed during scanning. This limitation impacts on the translational value of such findings in real-world applications.

To overcome the limitations of traditional neuroimaging paradigms, second generation neuroimaging devices such as portable EEG and functional near-infrared spectroscopy (fNIRS), and non-invasive brain stimulation techniques such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) can be used to study a broader range of dynamic movements and central changes associated with physical exercise. Both EEG and fNIRS can be applied concurrently with a motor task or exercise to understand its associated central response, while the application of non-invasive brain stimulation can help to establish causality by experimentally-induced facilitation or inhibition of specific neural networks.

In this research topic, we aim to showcase recent advances in the use of neuroimaging and non-invasive brain stimulation techniques to understand motor control processes and central adaptations to exercise across the lifespan and disease conditions. Submissions that are Original Research, Systematic Reviews and Meta-analysis, Literature review, Mini-review, Methods, and Perspective articles will be considered. Topics that cover, but not limited to, the following to domains are encouraged: