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Category: robotics/AI – Page 1,824

You can live to 150? Scientists create app that shows human lifespan could nearly double

An iPhone app that estimates biological aging discovered that life expectancy has the capacity to be almost double the current norm.

GEYLANG, Singapore — Have you made any plans for the 22nd century yet? A new study finds you might want to think about it because it’s possible for humans to live to see their 150th birthday!

Scientists in Singapore have developed an iPhone app that accurately estimates biological aging. It discovered that life expectancy has the capacity to be almost double the current norm. The findings are based on blood samples from hundreds of thousands of people in the United States and United Kingdom.

The instrument, called DOSI, uses artificial intelligence to work out body resilience, the ability to recover from injury or disease. DOSI, which stands for dynamic organism state indicator, takes into account age, illnesses, and lifestyles to make its estimates.

Strange robotic thumb can impact how the hand is represented in the brain

UCL researchers have created a strange robotic “third thumb” that attaches to the hand and adds a large extra digit on the opposite side of the hand from the thumb. Researchers found that using the robotic thumb can impact how the hand is represented in the brain. For the research, scientists trained people to use an extra robotic thumb and found they could effectively carry out dexterous tasks such as building a tower of blocks using a single hand with two thumbs.

Researchers said that participants trained to use the extra thumb increasingly felt like it was part of their body. Initially, the Third Thumb was part of a project seeking to reframe the way people view prosthetics from replacing a lost function to becoming an extension of the human body. UCL Professor Tamar Makin says body augmentation is a growing field aimed at extending the physical abilities of humans.

The World’s First Robot Chef Is Finally Here, and It Even Cleans Up After Itself

Anyone who spends a lot of time in the kitchen knows that there’s at least one gadget out there for every single step in the cooking process. But there has never been an appliance that could handle them all. Until now, that is.

Later this year, London-based robotics company Moley will begin selling the first robot chef, according to the Financial Times. The company claims the ceiling-mounted device, called the Moley Robotics Kitchen, will be able to cook over 5000 recipes and even clean up after itself when it’s done.

Samsung Develops a Very Fast 512GB DDR5 Memory Module

2 sticks of RAM giving you 1TB of memory will be the norm soon.

While consumers today typically use computers with 8GB or 16GB of DDR4 RAM inside, Samsung is pushing ahead with the next generation of memory modules. Its latest stick of RAM is a 512GB DDR5 module running at 7200Mbps.

The new module will be used in servers performing “the most extreme compute-hungry, high-bandwidth workloads.” That means supercomputers, artificial intelligence, and machine learning. It was made possible thanks to advanced HKMG technology, which Samsung adopted back in 2018 for its GDDR6 memory. Basically, HKMG replaces the insulator layer in DRAM structures. The high dielectric material contained in the layer reduces current leakage and therefore allows higher performance. At the same time, Samsung managed to reduce power usage in the new module by 13%.

“Samsung is the only semiconductor company with logic and memory capabilities and the expertise to incorporate HKMG cutting-edge logic technology into memory product development,” said Young-Soo Sohn, Vice President of the DRAM Memory Planning/Enabling Group at Samsung Electronics. “By bringing this type of process innovation to DRAM manufacturing, we are able to offer our customers high-performance, yet energy-efficient memory solutions to power the computers needed for medical research, financial markets, autonomous driving, smart cities and beyond.”

New Dark Matter Map Reveals Hidden Bridges Between Galaxies

A new map of dark matter in the local universe reveals several previously undiscovered filamentary structures connecting galaxies. The map, developed using machine learning by an international team including a Penn State astrophysicist, could enable studies about the nature of dark matter as well as about the history and future of our local universe.

Dark matter is an elusive substance that makes up 80% of the universe. It also provides the skeleton for what cosmologists call the cosmic web, the large-scale structure of the universe that, due to its gravitational influence, dictates the motion of galaxies and other cosmic material. However, the distribution of local dark matter is currently unknown because it cannot be measured directly. Researchers must instead infer its distribution based on its gravitational influence on other objects in the universe, like galaxies.

“Ironically, it’s easier to study the distribution of dark matter much further away because it reflects the very distant past, which is much less complex,” said Donghui Jeong, associate professor of astronomy and astrophysics at Penn State and a corresponding author of the study. “Over time, as the large-scale structure of the universe has grown, the complexity of the universe has increased, so it is inherently harder to make measurements about dark matter locally.”

Rich people are spending millions on underground bunkers equipped with robot security and movie theaters after a year of man-made and natural threats

Interest in such plush panic rooms is skyrocketing, he said. His firm started offering high-end shelters and the like a decade ago — of the 232 it’s built so far, 200 were commissioned in the last five years.

One $14 million panic-room project built in the San Jose Valley includes a bowling alley and indoor pool.

3D printing stem cells to transform neuroscience

3D printing, also called additive manufacturing, has become widespread in recent years. By building successive layers of raw material such as metals, plastics, and ceramics, it has the key advantage of being able to produce very complex shapes or geometries that would be nearly impossible to construct through more traditional methods such as carving, grinding, or molding.

The technology offers huge potential in the health care sector. For example, doctors can use it to make products to match a patient’s anatomy: a radiologist could create an exact replica of a patient’s spine to help plan surgery; a dentist could scan a patient’s broken tooth to make a perfectly fitting crown reproduction. But what if we took a step further and apply 3D printing techniques to neuroscience?

Stems cells are essentially the body’s raw materials; they are pluripotent elements from which all other cells with specialized functions are generated. The development of methods to isolate and generate human stem cells, has excited many with the promise of improved human cell function understanding, ultimately utilizing them for regeneration in disease and trauma. However, the traditional two-dimensional growth of derived neurones–using flat petri dishes–presents itself as a major confounding factor as it does not adequately mimic in vivo three-dimensional interactions, nor the myriad developmental cues present in real living organisms.

To address this limitation in current neuronal culturing approaches, the FET funded MESO-BRAIN project, led by Aston University, proposed a highly ambitious interdisciplinary enterprise to construct truly 3D networks that not only displayed in vivo activity patterns of neural cultures but also allowed for precise interaction with these cultures. This allows the activity of individual elements to be readily monitored and controlled through electrical stimulation.

The ability to develop human-induced pluripotent stem cell derived neural networks upon a defined and reproducible 3D scaffold that can emulate brain activity, allows for a comprehensive and detailed investigation of neural network development.

The MESO-BRAIN project facilitates a better understanding of human disease progression, neuronal growth and enables the development of large-scale human cell-based assays to test the modulatory effects of pharmacological and toxicological compounds on neural network activity. This can ultimately help to better understand and treat neurological conditions such as Parkinson’s disease, dementia, and trauma. In addition, the use of more physiologically relevant human models will increase drug screening efficiency and reduce the need for animal testing.

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