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The world of computing has taken a significant leap forward with the development of the “microwave brain” chip, a low-power microchip that can compute on both ultrafast data signals and wireless communication signals. This revolutionary innovation, created by researchers at Cornell University, marks the first time a processor has harnessed the physics of microwaves to perform real-time frequency domain computation.

Detailed in the journal Nature Electronics, this groundbreaking processor is the first true microwave neural network and is fully integrated on a silicon microchip. It can handle tasks like radio signal decoding, radar target tracking, and digital data processing while consuming less than 200 milliwatts of power – an impressive feat considering its speed and efficiency.

The secret behind this technology lies in its design as a neural network, modeled after the human brain’s interconnected modes produced in tunable waveguides. This allows it to recognize patterns and learn from data, unlike traditional digital computers that rely on step-by-step instructions timed by a clock. The microwave brain processor uses analog, nonlinear behavior in the microwave regime to handle data streams at speeds of tens of gigahertz – far faster than most digital chips.

“We’ve created something that looks more like a controlled mush of frequency behaviors that can ultimately give you high-performance computation,” says Alyssa Apsel, professor of engineering and co-senior author. Bal Govind, lead author and doctoral student, explains that the chip’s programmable distortion across a wide band of frequencies allows it to be repurposed for several computing tasks.

The microwave brain processor has achieved remarkable accuracy on multiple classification tasks involving wireless signal types, comparable to digital neural networks but with a fraction of the power and size. It can perform both low-level logic functions and complex tasks like identifying bit sequences or counting binary values in high-speed data.

With its extreme sensitivity to inputs, this chip is well-suited for hardware security applications like sensing anomalies in wireless communications across multiple bands of microwave frequencies. The researchers are optimistic about the scalability of this technology and are experimenting with ways to improve its accuracy and integrate it into existing microwave and digital processing platforms.

As the world becomes increasingly dependent on data-driven technologies, innovations like the microwave brain chip have the potential to revolutionize computing and redefine what is possible in the realm of artificial intelligence and machine learning.

The article discusses how scientists have developed tiny robots that use sound waves to coordinate into large swarms, exhibiting intelligent-like behavior. This innovative technology has the potential to revolutionize various fields, including environmental remediation, healthcare, and search and rescue operations.

Led by Igor Aronson, a team of researchers created computer models to simulate the behavior of these micromachines. They found that acoustic communication allowed individual robotic agents to work together seamlessly, adapting their shape and behavior to their environment, much like a school of fish or a flock of birds.

The robots’ ability to self-organize and re-form themselves if deformed is a significant breakthrough in the field of active matter, which studies the collective behavior of self-propelled microscopic biological and synthetic agents. This new technology has the potential to tackle complex tasks such as pollution cleanup, medical treatment from inside the body, and even exploration of disaster zones.

The team’s discovery marks a significant leap toward creating smarter, more resilient, and ultimately more useful microrobots with minimal complexity. The insights from this research are crucial for designing the next generation of microrobots capable of performing complex tasks and responding to external cues in challenging environments.

While the robots in the paper were computational agents within a theoretical model, rather than physical devices that were manufactured, the simulations observed the emergence of collective intelligence that would likely appear in any experimental study with the same design. The team’s findings have opened up new possibilities for the use of sound waves as a means of controlling micro-sized robots, offering advantages over chemical signaling such as faster and farther propagation without loss of energy.

This research has far-reaching implications for various fields, including medicine, environmental science, and engineering. It highlights the potential for microrobots to be used in complex tasks such as exploration, cleanup, and medical treatment, and demonstrates their ability to self-heal and maintain collective intelligence even after breaking apart.

The accelerated evolution engine known as T7-ORACLE has revolutionized the field of medicine and biotechnology by allowing researchers to evolve proteins with new or improved functions at an unprecedented rate. This breakthrough was achieved by Scripps Research scientists who have developed a synthetic biology platform that enables continuous evolution inside cells without damaging the cell’s genome.

Directed evolution is a laboratory process where mutations are introduced, and variants with improved function are selected over multiple cycles. Traditional methods require labor-intensive steps and can take weeks or more to complete. In contrast, T7-ORACLE accelerates this process by enabling simultaneous mutation and selection with each round of cell division, making it possible to evolve proteins continuously and precisely inside cells.

T7-ORACLE circumvents the bottlenecks associated with traditional approaches by engineering E. coli bacteria to host a second, artificial DNA replication system derived from bacteriophage T7. This allows for continuous hypermutation and accelerated evolution of biomacromolecules, making it possible to evolve proteins in days instead of months.

To demonstrate the power of T7-ORACLE, researchers inserted a common antibiotic resistance gene into the system and exposed E. coli cells to escalating doses of various antibiotics. In less than a week, the system evolved versions of the enzyme that could resist antibiotic levels up to 5,000 times higher than the original.

The broader potential of T7-ORACLE lies in its adaptability as a platform for protein engineering. Scientists can insert genes from humans, viruses, or other sources into plasmids and introduce them into E. coli cells, which are then mutated by T7-ORACLE to generate variant proteins that can be screened or selected for improved function.

This could help scientists more rapidly evolve antibodies to target specific cancers, evolve more effective therapeutic enzymes, and design proteases that target proteins involved in cancer and neurodegenerative disease. The system’s ease of implementation, combined with its scalability, makes it a valuable tool for advancing synthetic biology.

The research team is currently focused on evolving human-derived enzymes for therapeutic use and tailoring proteases to recognize specific cancer-related protein sequences. In the future, they aim to explore the possibility of evolving polymerases that can replicate entirely unnatural nucleic acids, opening up possibilities in synthetic genomics.