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Self Fuelled Transformable Liquid Metal Machine

Synthetic self-fuelled motors, which can spontaneously convert chemical energy into mechanical activity to induce autonomous locomotion, are excellent candidates for making self-powered machines, detectors/sensors, and novel robots. The present lab (Zhang et al. in Adv Mater 27:2648–2655, 2004 [1]). discovered an extraordinary self-propulsion mechanism of synthetic motors based on liquid metal objects. Such motors could swim in a circular Petri dish or different structured channels containing aqueous solution with a pretty high velocity on the order of centimeters per second, and surprisingly long lifetime lasting for more than one hour without any assistance of external energy. The soft material liquid metal enables the motors to self-deform, which makes them highly adaptable for accomplishing tough missions in special environment. Interestingly, the motors work just like biomimetic mollusk since they closely resemble the nature by “eating” aluminum as “food”, and can change shape by closely conforming to the geometrical space it voyages in. From practical aspect, one can thus develop a self-powered pump based on the actuation of the liquid metal enabled motor. Further, such pump can also be conceived to work as a cooler. Apart from different geometrical channels, several dominating factors, including the volume of the motor, the amount of aluminum, the property of the solution and the material of the substrate etc., have been disclosed to influence the performance of the autonomous locomotion evidently. This artificial mollusk system suggests an exciting platform for molding the liquid metal science to fundamentally advance the field of self-driven soft machine design, microfluidic systems, and eventually lead to the envisioned dynamically reconfigurable intelligent soft robots in the near future. In this chapter, the typical behaviors and fundamental phenomena of the self fuelled transformable liquid metal machines were illustrated.

Elon Musk announces date for Neuralink presentation -‘AI symbiosis while u wait’

The Chief Executive Officer of SpaceX and Tesla, Elon Musk, founded Neuralink, a company that is developing a brain-machine interface that could one day restore a variety of brain-related issues, including restoring eyesight and limb functionality, solve memory loss, even cure depression via a brain chip implant. Musk initially aims to focus on the medical aspect of the neural interface, like solving mobility issues with paralyzed individuals. Ultimately, his team aims to achieve ‘symbiosis’ with Artificial Intelligence (AI).

5G is accelerating factory automation that could add trillions to the global economy

Imagine a manufacturing plant in which all the production equipment is continually changing in response to market needs. Robots churning out widgets, for instance, would reconfigure themselves based on data coming in from all points of the widget supply chain, as well as sensors monitoring the factory itself. The result is a smart factory that’s more agile and autonomous than previous generations of automation.

Also known as Industry 4.0, the smart factory runs on data and artificial intelligence, but connectivity forms the backbone of operations. The new fifth generation of mobile networks (5G) is a catalyst for this new industrial revolution because it offers much greater speed and bandwidth than previous networks, as well as low latency, or time required for data to travel between two points. 5G will work with and in some cases replace existing fixed, wired connections, making manufacturing more flexible and ready to implement innovations.

5G could replace wired Ethernet as well as Wi-Fi and 4G LTE networks that connect devices in factories, but one 5G supplier is starting with the basics: powering mobile devices and robots. At a new factory in Lewisville, Texas, Swedish telecom Ericsson has been turning out 5G infrastructure equipment with the aid of a 5G network in the plant itself. Ericsson, which is supplying 5G equipment to telecoms in the U.S. such as AT&T, Verizon, Sprint and T-Mobile, has forecast 190 million 5G subscribers by the end of 2020 and 2.8 billion by the end of 2025.

And as in most applications of #MachineLearning, healthcare #AI systems are extremely data-hungry

Very true.


And as in most applications of #MachineLearning, healthcare #AI systems are extremely data-hungry.

Fortunately, a slew of new sensors and data acquisition methods — including over 302 million wearables shipped in 2019 — are bursting onto the scene to meet the massive demand for medical data.

From ubiquitous biosensors, to the mobile healthcare revolution, to the transformative power of the Health Nucleus and their 100+ program, converging exponential technologies are fundamentally transforming our approach to #healthcare.

The F-16’s Replacement Won’t Have a Pilot at All

Innovation.


The U.S. Air Force plans to have an operational combat drone by 2023. The service plans to build out a family of unmanned aircraft, known as Skyborg, capable of carrying weapons and actively participating in combat. The Air Force’s goal is to build up a large fleet of armed, sort-of disposable jets that don’t need conventional runways to take off and land.

The Air Force, according to Aviation Week & Space Technology, expects to have the first operational Skyborg aircraft ready by 2023. Skyborg will be available with both subsonic and supersonic engines, indicating both attack and fighter jet versions. The basic design (or designs) will likely be stealthy, carrying guided bombs, air defense suppression missiles, and air-to-air missiles inside internal weapons bays. Interesting, according to AvWeek, the Air Force is considering Skyborg as a replacement not only for the MQ-9 Reaper attack drone but early versions of the F-16 manned fighter.

Using astrocytes to change the behavior of robots controlled by neuromorphic chips

Neurons, specialized cells that transmit nerve impulses, have long been known to be a vital element for the functioning of the human brain. Over the past century, however, neuroscience research has given rise to the false belief that neurons are the only cells that can process and learn information. This misconception or ‘neurocomputing dogma’ is far from true.

An is a different type of cell that has recently been found to do a lot more than merely fill up spaces between neurons, as researchers believed for over a century. Studies are finding that these cells also play key roles in brain functions, including learning and central pattern generation (CPG), which is the basis for critical rhythmic behaviors such as breathing and walking.

Although astrocytes are now known to underlie numerous brain functions, most existing inspired by the only target the structure and function of neurons. Aware of this gap in existing literature, researchers at Rutgers University are developing brain-inspired algorithms that also account for and replicate the functions of astrocytes. In a paper pre-published on arXiv and set to be presented at the ICONS 2020 Conference in July, they introduce a neuromorphic central pattern generator (CPG) modulated by artificial astrocytes that successfully entrained several rhythmic walking behaviors in their in-house robots.

Robot scientist discovers a new catalyst

The robot seen here can work almost 24–7, carrying out experiments by itself. The automated scientist – the first of its kind – can make its own decisions about which chemistry experiments to perform next, and has already discovered a new catalyst.

With humanoid dimensions, and working in a standard laboratory, it uses instruments much like a human does. Unlike a real person, however, this 400 kg robot has infinite patience, and works for 21.5 hours each day, pausing only to recharge its battery.

This new technology – reported in the journal Nature and featured on the front cover – is designed to tackle problems of a scale and complexity that are currently beyond our grasp. New drug formulations could be autonomously discovered, for example, by searching vast and unexplored chemical spaces.

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