The Dawn of Neuromorphic Computing: A Promising Frontier or a Dangerous Path?
In Blade Runner 2049, replicants blend seamlessly into society, mirroring the humans they were designed to imitate, while in Westworld, hyper-intelligent robots evolve beyond their creators. The anime Pluto reflects a similar cautionary tale, portraying a world where robots, indistinguishable from humans, become part of everyday life. These fictional portrayals offer stunning and eerie glimpses into a future where machines are not just tools but sentient beings. As we advance toward groundbreaking technologies, should we be inspired or heed these warnings?
This past summer, I discovered the field of neuromorphic computing. Often described as the next revolution in AI, neuromorphic computing draws inspiration from the architecture of the human brain. While traditional computers use transistors and binary logic (0s and 1s) to process information in a linear, step-by-step manner, neuromorphic systems attempt to replicate how neurons and synapses work (TechTarget 2024). In the human brain, neurons are the basic units that transmit information. Each neuron connects to thousands of other neurons via synapses, forming a vast, interconnected network (NCBI 2023). Neuromorphic computers emulate this concept by using artificial neurons and synapses. Instead of processing data in binary form, they use electrical signals—similar to neurons firing in the brain. The key difference from traditional computing is that these systems process information in parallel, like the brain, rather than linearly. This parallelism makes neuromorphic computers much more efficient at tasks that require real-time adaptation and learning, such as recognizing patterns or making split-second decisions. But why does this matter? Neuromorphic computing could simulate hippocampal networks to explore how memories are formed and recalled, shedding light on conditions like Alzheimer's disease (Front. Neural Circuits 2023). Additionally, they can model abnormal brain activity, helping scientists understand neurological disorders like epilepsy or Parkinson's disease. Their rapid adaptability also makes them effective in high-risk and unpredictable terrains, perfect for autonomous systems like drones which are essential for reconnaissance or combat scenarios (Science Robotics 2024). Amid the excitement of innovation, we must remain cautious. The very technologies that offer the potential for creating machines with human-like cognition also bear striking resemblance to the dystopian visions laid out in our favorite science fiction. In Westworld, for instance, what starts as human control over advanced AI quickly unravels into chaos when the robots become too intelligent, developing desires, emotions, and, ultimately, the will to rebel. Neuromorphic systems could unlock forms of AI that are no longer dependent on human input and evolve at a pace beyond our understanding. Once AI systems achieve autonomy, how do we maintain authority over them? And at what point does that authority slip away? While we are not yet at the precipice of robot revolutions, we must recognize that advanced AI could bring about unforeseen ethical challenges. As these machines become more capable of independent thought, will they deserve rights? How will we regulate their actions, especially in high-stakes environments like military operations? Moreover, neuromorphic computing, by its very nature, is meant to mimic the flexibility and adaptability of the human brain. But this raises another important concern: our brains are not just machines, they are embedded with empathy, emotion, and morality. In their attempt to emulate human thought, will neuromorphic systems also adopt human flaws? Could they misinterpret data, make biased decisions, or be vulnerable to manipulation? That said, it's important not to view neuromorphic computing solely through a lens of fear. In fields like climate science, autonomous robotics, or precision medicine, neuromorphic computing could drive AI systems that make discoveries faster and more efficiently than any human team ever could. The implementation of sentient robots would fundamentally alter societal dynamics by challenging concepts of human rights, labor, and autonomy. While neuromorphic computing is an extension of existing knowledge, its effect on our society would be revolutionary, redefining human-machine relationships and reshaping global power structures. As John Horgan states in his article "Huge Study Confirms Science Ending! (Sort Of)," revolutionary science challenges the prevailing paradigm, or status quo, whereas normal merely extends it. The worlds of Blade Runner 2049, Westworld, and Pluto aren't just entertaining fantasies. They are stories crafted by human imagination to reflect our deepest fears about technology surpassing our control. As we continue to pursue invention for the sake of invention, there is one thing we should keep in mind: the future we create will depend on our wisdom in ensuring these machines remain our allies, not our adversaries.
Works Cited
Barney, Nick, and Ben Lutkevich. “What Is Neuromorphic Computing?: Definition from TechTarget.” Neuromorphic Computing, TechTarget, 26 Aug. 2024,
Caire MJ, Reddy V, Varacallo M. Physiology, Synapse. [Updated 2023 Mar 27]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.
F. Paredes-Vallés et al. ,Fully neuromorphic vision and control for autonomous drone flight.Sci. Robot.9,eadi0591(2024).
Horgan, John. “Huge Study Confirms Science Ending! (Sort Of).” John Horgan (The Science Writer), John Horgan (The Science Writer), 18 Apr. 2024.
Kanagamani T, Chakravarthy VS, Ravindran B and Menon RN (2023) A deep network-based model of hippocampal memory functions under normal and Alzheimer’s disease conditions. Front. Neural Circuits 17:1092933.
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