Alan Turing’s article “Computing Machinery and Intelligence,” published in the Mind Journal in 1950, is considered the first publication about AI. Seventy-five years later, the current AI hype reflects significant innovation. The landscape of artificial intelligence has changed drastically since 2025 got underway. Large language models, inventive artificial intelligence tools, and autonomous systems have skyrocketed. But along with these innovations comes an unavoidable growing concern about artificial intelligence’s enormous energy impact.
CyberSwarm’s narrative and vision focus on a more sustainable AI future in a year where global AI adoption has surged and energy costs have dominated headlines. We have been developing a ground-breaking method that could change the current paradigm.
But before we delve into what CyberSwarm is doing, let’s see some numbers.
You have most likely heard of large data centers running nonstop and using electricity as if it were limitless. A recent report from Gartner reveals that 40% of the world’s artificial intelligence (AI) data centers may face operational limitations due to power constraints. This is a result of the rapid growth of AI and generative AI, which is creating unprecedented energy demands worldwide.
Researchers estimate that artificial intelligence may consume 3.5% of all the electricity consumed worldwide by 2030. According to the International Energy Agency, a single request made through ChatGPT, an AI-powered virtual assistant, consumes 10 times more electricity than a standard Google search. AI cloud computing costs grew 35% in 2024, doubling resource consumption year-over-year.
That is not only a large figure but also a major obstacle to enable sustainable and accessible artificial intelligence. Is such sustained growth possible?
Looking to Nature for Answers
At CyberSwarm we asked ourselves: what if the answer has been right in front of us all along? Consider this: many of the computing problems we confront now have already been addressed by nature. Biological systems have evolved millions of years to provide remarkably effective means of information processing and situational adaptation. This realization set off our exploration of neuromorphic computing.
How We Got Here
CyberSwarm, Inc. Patents
Our founder, Mihai Raneti, initially focused on cybersecurity in 2017. However, the most significant discoveries often arise from unexpected places. While addressing a particularly complex hardware challenge, we recognized that conventional computing designs were inadequate. We needed a fundamentally different approach, one that could process data efficiently with minimal power consumption. Our solution involved developing hardware artificial neural networks capable of replicating the efficiency of biological systems. Similar to how natural systems adapt to their environments, we have created components that can learn and adapt autonomously.
The result: a neuromorphic engine – or, as we like to call it, a brain on a chip. This device can learn independently without an internet connection and can be deployed on silicon, IGZO glass, or flexible materials. It integrates analog and digital capabilities, supporting tens of thousands of algorithms.
The core technology is based on memristors, similar to resistance with memory, thus easily transformed into artificial synapses or neurons. Because we do not use traditional Von Neumann architecture, the energy cost is very low and it can store and process – similar to a biological brain. It works without internet connection and learns and adapts directly to the hardware, maintains sound and safe access to your data.
Traditional computing architectures utilize sequential data transfer, leading to latency and power consumption associated with each component handoff. Our method implements a concurrent, synchronized data processing paradigm. This ‘harmonized’ approach eliminates redundant transfers, enabling faster and more energy-efficient information flow.
For businesses and developers, this translates into direct benefits:
- lower computing costs
- enhanced data privacy (since it operates offline)
- reduced latency
- significantly lower power consumption.
Built for scalability, our flexible AI technology can be integrated across industries—from smart devices to industrial automation—offering a sustainable alternative to power-hungry AI models.
What’s Next?
We are not just building chips—we are designing a full AI hardware ecosystem. Our technology is set to power the next generation of AI-driven devices, industrial systems, and autonomous technologies.
Our ultimate goal? To develop an AI Companion—an intuitive, energy-efficient AI that seamlessly integrates with everyday life.
As George Dyson famously said:
“In the game of life and evolution, there are three players at the table: human beings, nature, and machines. I am firmly on the side of nature. But nature, I suspect, is on the side of the machines.”
At CyberSwarm, we are gathering everyone rather than choosing sides. We are creating something innovative by combining modern technology, nature’s genius, and human inventiveness. Consider it as nature’s design guide for improved computation. We are not only increasing the efficiency of artificial intelligence; we are also making it more natural, more sustainable, and more like us.
This isn’t just another technological innovation, it’s a new way of computing. And we invite you to be part of it.