MAROKO133 Update ai: US Navy’s ‘hellscape’ drone plan could complicate China’s Taiwan play

📌 MAROKO133 Hot ai: US Navy’s ‘hellscape’ drone plan could complicate China’s Taiw

The U.S. Navy’s plan to deploy thousands of autonomous drone vessels in the Indo-Pacific by 2030 has received cautious support from Taiwanese defense analysts.

While they agree the concept could increase costs for any Chinese military action against Taiwan, they warn that production timelines, logistics, and Taiwan’s own stalled drone programs may limit its effectiveness.

These assessments follow Capt. Garrett Miller’s confirmation that the Navy expects to field over 30 medium unmanned surface vessels in the Indo-Pacific by 2030, along with thousands of smaller drone boats and aerial systems operating from both manned and unmanned ships.

This initiative is part of a broader U.S. Indo-Pacific Command effort to create what Adm. Samuel Paparo has called a “hellscape,” saturating contested waters with autonomous systems to deter or counter any PLA action against regional targets, including Taiwan.

The case for drone boats around Taiwan

Taiwan faces a growing naval disadvantage compared to mainland China, so affordable, disposable uncrewed vessels are attractive. If the PLA has to track and attack many more targets, a swarm of drone boats could make a blockade or amphibious assault much more costly.

Zivon Wang, a military analyst at the Chinese Council of Advanced Policy Studies in Taipei, said these systems could also interfere with Beijing’s use of civilian fishing and commercial ships for grey-zone tactics at sea.

Wang added that if the U.S. can produce enough of them, they would be very useful in the Taiwan Strait and nearby waters.

Obstacles around the ‘hellscape’ plan

Unmanned surface vessels are substantially harder to mass-produce than aerial drones. They are larger, more expensive to store, more vulnerable to harsh sea conditions, and moving large flotillas across the Pacific would be difficult to conceal.

The Indo-Pacific, Wang noted, is enormous — only a limited number could realistically be deployed near Taiwan at any given time.

Max Lo, executive director of the Taiwan International Strategic Study Society, said the ‘hellscape’ idea makes sense as a strategy but is less certain in practice.

Unmanned vessels still need launch platforms, support ships, or nearby bases, which limits how far they can go. If they are sent too far from the action, they lose effectiveness. If they are too close, they could be destroyed by the PLA’s many anti-ship missiles.

The quarantine problem and Taiwan’s own drone gap

Former Taiwan defense ministry press secretary Lu De-yun raised another concern: it remains unclear whether drone boats could break a quarantine-style campaign that cuts Taiwan’s imports, exports, and energy supplies without a formal invasion.

Lu also noted that U.S. support would depend on whether Washington is managing one conflict or several at once, describing this as already the case in 2026 due to the ongoing war in Iran.

The debate also highlights significant gaps in Taiwan’s domestic defense planning.

Taipei’s military has proposed acquiring over 1,000 attack-capable unmanned surface vessels under a planned $40 billion special defense budget.

Broader drone plans reportedly include up to 200,000 unmanned aerial systems of various types, with software imported and hardware produced locally.

🔗 Sumber: interestingengineering.com

📌 MAROKO133 Hot ai: US: Princenton scientists make 3D bio-electronic hybrid system

Researchers at Princeton University have developed a 3-dimensional device that merges living brain cells with advanced electronics to perform computational tasks. 

In this new work, advanced fabrication was used to create a 3D mesh of microscopic metal wires and electrodes.

As per the study authors, these 3D biological neural networks serve a dual purpose. Beyond unlocking the brain’s computational mysteries, it provides a powerful new tool for understanding and developing treatments for neurological diseases.

Six-month stable 3D mesh

The research team employed advanced fabrication techniques to construct a 3D mesh consisting of microscopic metal wires and electrodes. This structure is supported by an ultra-thin, flexible epoxy coating that mimics the soft, delicate texture of actual brain tissue. 

Using the mesh as a scaffold, tens of thousands of neurons were grown directly, and allowed the electronics to interface with the biological network from the inside.

Remarkably, the system remained stable for over six months. The “inside-out” architecture allows the electronics to record and stimulate the cells, transforming a vast 3D cluster of living neurons into a programmable system capable of computation.

This long-term evolution culminated in the training of an algorithm capable of accurately interpreting and recognizing complex patterns of electrical pulses within the system.

Interestingly, it demonstrated its computational prowess by successfully distinguishing between distinct spatial sources (i.e., the locations where signals originate) and temporal electrical patterns (the timing of electrical pulses). These tests confirmed that the hybrid device can process both the where and when of incoming data, much like a natural brain. 

“The system correctly distinguished among the patterns in both tests. The researchers said they hope to scale the system to the point where it can do increasingly complex tasks,” the researchers noted. 

Although originally designed for neuroscience research, the project has applications in solving the energy crisis in modern AI. 

Data centers are consuming massive amounts of electricity to run the math required for digital intelligence. Researchers hope to solve the massive energy drain slowing down AI technology. 

The human brain is the most efficient computer in the known universe. It performs complex reasoning and pattern recognition while operating on a million times less power than digital computers. Using actual biological cells, the Princeton team is looking for a shortcut to ultra-low-power computing.

Advancing wetware computing

Princeton’s discovery is part of a fast-growing field called “Wetware Computing.” While other scientists have tried similar things, this new 3D design is latest in the line. 

Most attempts to harness brain cells for computing happen in flat petri dishes, which are 2D, fragile, and monitored from a distance.  In 2022, a startup called Cortical Labs created “DishBrain,” a flat, 800,000-neuron layer that learned to play the arcade game Pong in 5 minutes. While impressive, DishBrain was limited by its 2D geometry.

Instead of just sitting on top of the new device, the cells actually grew through the mesh and tangled with it. As the sensors are tucked right inside the cell cluster, researchers can detect their neuron signals more clearly than ever before.

The study was published in the journal Nature Electronics on April 23.

🔗 Sumber: interestingengineering.com