The billionaire’s brain device company is currently recruiting patients in the US, UK and Canada.
Genes aren’t the sole driver instructing cells to build multicellular structures, tissues, and organs. In a paper published in Nature Communications, USC Stem Cell scientist Leonardo Morsut and Caltech computational biologist Matt Thomson characterize the influence of another important developmental driver: cell density, or how loosely or tightly cells are packed into a given space.
In both computational models and laboratory experiments, the team of scientists used cell density as an effective tool for controlling how mouse cells pattern themselves into complex structures.
“This paper represents progress towards our big picture goal of engineering synthetic tissues,” said Morsut, an assistant professor of stem cell biology and regenerative medicine, and biomedical engineering at the Keck School of Medicine of USC.
TSMC is set to mass-produce its cutting-edge 2nm process by 2025, as the Taiwan giant is seeing massive interest from companies such as Apple and NVIDIA.
TSMC’s 2nm Node Is Said To Replace All Others When It Comes To Revenue Generation, Amid Gigantic Demand From The Markets
TSMC’s upcoming 2nm node is said to be a revolution for the tech markets, given that it has pledged to bring in significant performance uplifts, one that will aid in speeding up the computational capabilities of devices across the industry.
Life is a series of small events: making morning coffee, letting the dog out, opening a laptop, letting the dog back in. Add them all up and you have a full day. Our brains are committed to observing and processing the events that make up our daily lives, said Jeff Zacks, the Edgar James Swift Professor in Arts & Sciences and chair of the Department of Psychological & Brain Sciences. “Knowing where events begin and where they end is crucial to understanding the world,” Zacks said.
In a pair of new papers, Zacks and other researchers in Arts & Sciences and the McKelvey School of Engineering explore this key process of human cognition.
Zacks led a study that trained computer models to observe more than 25 hours of video of people performing simple, everyday tasks such as cleaning a kitchen or cooking a meal before making predictions about what happens next. The study came to a surprising conclusion: The computer models were most accurate when they responded to uncertainty. When the model was especially unsure about what would happen next, it would reset and reassess the scene, an approach that improved its overall comprehension.
A team of astrophysicists, led by our Institute for Computational Cosmology, have developed a new model that could estimate how likely it is for intelligent life to emerge in our Universe and beyond.
In the 1960s, American astronomer Dr Frank Drake came up with an equation to calculate the number of detectable extraterrestrial civilisations in our Milky Way galaxy.
More than 60 years on, researchers at Durham, the University of Edinburgh and the Université de Genève, have produced a new model based on the conditions created by the acceleration of the Universe’s expansion and the amount of stars formed instead.
Now is the time to banish low-level radioactive energy sources from facilities that house and conduct experiments with superconducting qubits, according to a pair of recently published studies. Significantly improving quantum device coherence times is a key step toward an era of practical quantum computing.
Two complementary articles, published in the journal PRX Quantum and the Journal of Instrumentation, outline which sources of interfering ionizing radiation are most problematic for superconducting quantum computers and how to address them. The findings set the stage for quantitative study of errors caused by radiation effects in shielded underground facilities.
A research team led by physicists at the Department of Energy’s Pacific Northwest National Laboratory, in collaboration with colleagues at MIT’s Lincoln Laboratory, the National Institute of Standards and Technology, along with multiple academic partners, published their findings to assist the quantum computing community to prepare for the next generation of qubit development.
MIT physicists have shown that it should be possible to create an exotic form of matter that could be manipulated to form the qubit (quantum bit) building blocks of future quantum computers that are even more powerful than the quantum computers in development today.
The work builds on a discovery last year of materials that host electrons that can split into fractions of themselves but, importantly, can do so without the application of a magnetic field. The general phenomenon of electron fractionalization was first discovered in 1982 and resulted in a Nobel Prize.
That work, however, required the application of a magnetic field. The ability to create the fractionalized electrons without a magnetic field opens new possibilities for basic research and makes the materials hosting them more useful for applications.
Brain-Computer Interfaces fascinate the sci-fi and medical communities in equal measure. Here’s how close the transformative technology is to everyday use.
Quantum computers have the potential to simulate complex materials, allowing researchers to gain deeper insights into the physical properties that emerge from interactions among atoms and electrons. This may one day lead to the discovery or design of better semiconductors, insulators, or superconductors that could be used to make ever faster, more powerful, and more energy-efficient electronics.
But some phenomena that occur in materials can be challenging to mimic using quantum computers, leaving gaps in the problems that scientists have explored with quantum hardware.
To fill one of these gaps, MIT researchers developed a technique to generate synthetic electromagnetic fields on superconducting quantum processors. The team demonstrated the technique on a processor comprising 16 qubits.
