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How is AI interfaced with the biological human brain?

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Artificial Intelligence refers to machines that have been programmed to imitate human cognitive function successfully, to perform similar tasks, flawlessly. It is prudent to note, however, that the machines must be programmed by humans to assimilate past performance and data, which allows them to create new strategies to overcome challenges and outperform, in comparison to the limited capabilities of humans. Although the processes are complex, the significant advancements in recent years have boosted AI-powered machines for unimaginably smooth transitions, paving the way for superior systems that require far less monitoring than before.  

Artificial Intelligence encompasses a wide range and variety of subtopics, a lot of which have proved effective and efficient in handling many of the core tasks and challenges, across commercial and industrial sectors with high output and performance. The superior noninvasive brain-computer interfaces have already begun to make waves in the community, with a wide range of possibilities and applications.  

Yet, there is the overwhelming task of integrating, AI with the human brain seamlessly; this is when the term Artificial General Intelligence comes into relevance, and is briefly discussed below for a clearer understanding of the matter. 

Artificial General Intelligence versus Artificial Intelligence

AI has already significantly taken over several tasks that require sifting through vast amounts of data and stringent analyses with accuracy; the probability of human errors and miscalculations are thereby reduced, drastically. Businesses have simplified and have more reliable systems with AI, and are streamlining their processes for improved customer experience, lead generation processes, and payment options for enhanced user experiences.  It is estimated up to 72% entrepreneurs are dedicated to working with AI, increasing their profit margins with higher success ratios, optimal analyses, and new improved strategies. 

Artificial General Intelligence, on the other hand, is referring to the ability to carry out and perform the same tasks as humans, without the preprogramming, a non-compromising essential for AI. The main goals of the AGI are to fine-tune the learning, reasoning, and perceptive processes to flawlessly perform human-like complex tasks. 

While the majority of the breakthroughs have been relevant for the healthcare industry, there several occasions where improvements can be made in the sports, pharmaceutical, chemical, and several other industries. Some great examples of AI-powered machines are, but not restricted to, are self-driving cars, and the IBM Watson supercomputer. Experts believe that in another forty to fifty years the technologies maybe streamlined effectively, for superior performance without too many challenges.

Animal experiments

It can be said that the first machine termed as a BCI was possibly in 1924, with the discovery of the electroencephalography (EEG). Much has changed and improved since then, including using BCI with monkeys and rats. Monkey and rat cerebral cortices, have proven that BCI operations are possible, and as far back as 2008. The University Of Pittsburg Medical Center in 2008 showed pictures of BCI operated by a monkey, by thinking. Monkeys have also been known to navigate computer cursors visually and operate robotic arms. While these breakthroughs are acceptable, human brain-computer interface is far more complicated than that. 

Brain-Computer Interfacing (BCI) for humans

The rapid evolvement of technology is consistently highlighting the efficiency and advantages of using AI, and the numerous benefits it poses for the society, overall. While even a decade ago, the BCI technology was just a concept it has evolved through the years, providing streamlined treatments in the healthcare industry, robotic prosthetics, and also enhanced experiences, such as improved video games.

BCI technology powered devices and instruments have high potential with the superb and near-faultless computational power with assimilated knowledge from quantum computers, combined with predictive technologies, allowing it to customize performance, as well as user experience for optimal outcomes and strategies. 

Invasive and non-invasive BCI

The BCI can be segregated into two categories, invasive and non-invasive BCI. The invasive procedures, which consists of a chip inserted into the brain, have the potential for remarkable results. AI assisted brain performance is sure to surpass the standards of accepted performance outcomes, across industries, globally. Two factors that are difficult to digitize, are contextual comprehension, alongside strategic and tactical intelligence; although, several AI-powered games involve strategic planning and execution, such as chess, have beaten the top human players, worldwide. 

Noninvasive AI controlled devices, use BCI, to track and follow commands. This is a breakthrough, particularly for physically challenged people, across the globe, as until recently, these devices could only be managed through implants, through invasive procedures. As of now, noninvasive, external sensor BCI provides poorer quality signals, resulting in imprecise control and lower resolutions. Despite the apparent drawbacks, researchers have chosen to pursue their studies to ensure patients across the globe have a choice, when possible.

While the favourable outcomes from the invasive procedures are much welcome, the noninvasive processes are the ultimate goal. Superior neural decoding, novel sensing, novel continuous pursuit paradigm, and advanced machine learning technology have enabled researchers to access the furthest reaches of the mind, enabling for the first time, clear noninvasive imaging, to beat the previously noisy EEG signals. Continuous 2D robotic device control can now be expected with the much-improved EEG based neural decoding, which is a significant improvement and big breakthrough towards the ultimate goal. 

How has this been achieved?

To achieve improved results, it was crucial to enhance the performance of the “computer”, as well as the “brains” of the BCI. This was done by increasing the spatial resolution of the neural imaging data through the EEG source imaging, enhanced user engagement, and through improved training. These efforts have been rewarded, as there has been a marked improvement in the BCI learning, up to nearly 60%, which is mostly for conventional centre-out tasks. 

It has also shown a remarkable improvement in the consistent and continuous tracking of the computer cursor, by 500%, which means, that several patients can now look forward to mind control devices encouraging interaction and better controlled environments, without invasive procedures, as was the case, till recently. It has also been studied, that BCI can help stroke patients communicate, even with significant damages to the mind, amongst various other mental and physical challenges that may help overcome. As of now, the researchers have managed to test the processes on 68 healthy adults, each with ten sessions of virtually controlled devices, and robotic arms with continuous pursuit, with remarkable and outstanding results. 

To sum it up

The bottom line is that the AI interfacing with the biological human brain is no longer a myth; however, the complex neural connections are far from easy to replicate through the noninvasive systems, although much improvements have already been made in this sector. While AI systems are interconnected inherently, it is yet to reach the state where the artificial general intelligence has reached its optimal performance, to seamlessly integrate into daily lives. 

Artificial Intelligence interfaced with the biological human brain through invasive processes is more popular and also reliable, in comparison to noninvasive procedures, and is expected to be well-established by 2030. The fast paced technological breakthroughs are extremely encouraging, and researchers are keen to tweak their existing processes with more reliable and relevant data for the best favourable outcomes, across industries, besides healthcare. Therefore, the next few decades will be a game-changer for AI-powered technologies. 

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Anurag

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