Beyond Science Fiction: How hybrid systems are becoming a reality?

Hybrid machines combining human anatomy with AI are becoming a reality with the recent innovations of hybrid transistors and biocomputers.

By Faisal Khan | 13 December 2023
Medium

(Image Credit: Lexica.art)

From automating routine tasks to making complex decisions, intelligent machines have already proven their worth in various industries. However, the integration of these machines into our daily lives goes beyond mere automation. We are witnessing the birth of a new era where humans and machines collaborate seamlessly, with each complementing the strengths and compensating for the weaknesses of the other. These systems combine the cognitive abilities of humans with the computational efficiency of machines, creating a symbiotic relationship that has the potential to revolutionize the way we live, work, and interact with the world.

As we delve into this transformative journey, it becomes apparent that the impact of hybrid systems extends far beyond the realms of convenience. Smart cities are emerging, driven by the efficiency of intelligent machines in managing resources, optimizing traffic flow, and enhancing overall urban living. The workplace is undergoing a metamorphosis, with job roles evolving to accommodate the strengths of both human creativity and machine precision. And the list goes on.

Coming back to the topic of hybrid machines, scientists have taken major strides in that direction recently. A few weeks ago, researchers at Tufts University Silklab innovatively replaced the insulating material in transistors with biological silk. Their findings, detailed in Advanced Materials, showcase the unique properties of silk fibroin — the structural protein of silk fibers. This material can be precisely deposited onto surfaces and easily modified with various chemical and biological molecules, allowing for versatile adjustments to its properties.

By functionalizing silk in this manner, the team developed hybrid transistors capable of picking up and detecting a broad range of components from the body or the environment. The initial prototype device demonstrated the potential of these transistors by creating a highly sensitive and ultrafast breath sensor, specifically detecting changes in humidity.

With further modifications to the silk layer, these transistors could extend their applications to detect cardiovascular and pulmonary diseases, and sleep apnea, or analyze carbon dioxide levels and other gases in the breath, offering valuable diagnostic information. When utilized with blood plasma, these silk-enhanced transistors might provide insights into oxygenation levels, glucose concentrations, circulating antibodies, and more.

To top this, scientists more recently integrated a “brain organoid” into an artificial intelligence system, leveraging the neural tissue to aid in performing computational tasks. This experiment represents a potential advancement toward the development of “biocomputers.” To enhance the computational capabilities of artificial intelligence (AI), scientists have merged conventional machine learning with an advanced 3D model of the human brain composed of various types of lab-grown brain tissue.

In this novel approach, standard computing hardware is employed to input electrical data into the organoid. The organoid, functioning as the “middle layer” in the computing process, deciphers its activity to generate an output. The system devised by the researchers is named ‘Brainoware’, utilizing brain organoids — clusters of tissue resembling human cells commonly used in research to replicate organs.

These organoids, derived from stem cells with the ability to specialize into various cell types, were transformed into neurons similar to those present in the human brain. The creation of Brainoware involved placing a single organoid onto a plate equipped with thousands of electrodes, establishing a connection between the brain tissue and electric circuits. Researchers then converted input information into a pattern of electric pulses, delivering it to the organoid.

A sensor captured the tissue’s response, which was subsequently decoded using a machine-learning algorithm. To assess Brainoware’s capabilities, the team conducted voice recognition tests by training the system on 240 recordings of eight individuals speaking. The organoid exhibited distinct patterns of neural activity in response to each voice. The AI effectively learned to interpret these responses, achieving a speaker identification accuracy of 78%, according to research published in the Journal of Nature Electronics.

As we navigate the uncharted territory of hybrid intelligence, ethical considerations come to the forefront. Questions about privacy, job displacement & the potential misuse of technology must be addressed to ensure a future that is not only technologically advanced but also socially equitable. As we stand on the precipice of this technological revolution, one thing is certain — the future belongs to those who can navigate the delicate balance between man & machine, ushering in an era where the boundaries between the natural & the artificial blur into a seamless tapestry of progress.

Reprinted with permission from the author.

Faisal Khan is a prolific Canada-based tech blogger and influencer. He is the founder and editor of the Technicity publication which focuses on technical, scientific and financial knowledge sharing. Follow him on Twitter @fklivestolearn.

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