Lifeboat Foundation

Researchers at Brown University have created a brain-computer interface (BCI) with 200 electrodes providing 48 megabits per second (Mbit/s) of neural signals.

A new, detailed model of the surface of the SARS-CoV-2 spike protein reveals previously unknown vulnerabilities that could inform development of vaccines. Mateusz Sikora of the Max Planck Institute of Biophysics in Frankfurt, Germany, and colleagues present these findings in the open-access journal PLOS Computational Biology.

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic. A key feature of SARS-CoV-2 is its spike protein, which extends from its surface and enables it to target and infect human cells. Extensive research has resulted in detailed static models of the spike protein, but these models do not capture the flexibility of the spike protein itself nor the movements of protective glycans—chains of sugar molecules—that coat it.

To support vaccine development, Sikora and colleagues aimed to identify novel potential target sites on the surface of the spike protein. To do so, they developed molecular dynamics simulations that capture the complete structure of the spike protein and its motions in a realistic environment.

Applied Materials CEO Gary Dickerson’s formula for success isn’t magic. “Being close to the customer,” he said, is the lesson that’s guided him.

In 2020, TSMC spent a record $18 billion on building new factories for their chips. TSMC just announced they are spending $100 billion on new factories over the next 3 years. This will radically change the chip landscape. Many other companies, including Samsung and Intel, are upping their spending as well.

Of course, at some point there will be a chip glut again but this greatly increased chip capacity will change the world that we live in. It will also make AGI (Artificial General Intelligence) that much closer to reality… (All this money gives companies an incentive to spend R&D on smaller transistors, etc.)

The Big Bang remains the best way to explain what happened at the beginning of the Universe. However, the incredible energies flowing during the early part of the bang are almost incomprehensive to our everyday experience. Luckily, computers aren’t so attached to normal human ways of thinking and have long been used to model the early universe right after the Bang. Now, a team from the University of Göttingen have created the most comprehensive model of what exactly happened in that very early stage of the universe – one trillionth of a second after the Big Bang.

Just because a computer can model it doesn’t really mean it is easy to explain, however. The model includes clumps of energy weighing grams, but which are one millionth the size of a single proton. These energy structures defined what would eventually become the structure of the universe today, with tiny variations in the original structure resulting in entire galaxies or complete voids, depending on the presence or absence of matter.

Throwing this much computing power at a physical space one millionth the size of a proton was no mean feat. “It is probably the largest simulation of the smallest area of the Universe that has been carried out thus far” says Professor Jens Niemeyer, who leads the group carrying out the research.

Star clusters are interesting inhabitants of the sky. They vary in sizes, distances, and number of stars, but almost all are spectacular to look at. And most of them are in the process of being torn apart. That is certainly the case for the Hyades star cluster – the closest one to Earth at only 153 light years away. The problem is, there is something causing a lot more destruction than would be expected given the mass and energy in the surrounding space. Now, a team of scientists from ESA have a theory as to what the cause of the destruction might be – a mysterious dark matter sub-halo.

This novel theory extends from findings gleaned from data collected by GAIA, ESA’s star mapping satellite. The GAIA team expected to see what are called “tidal tails” trailing and leading the star cluster as it moves throughout the galaxy. These tails are formed when some stars are forced to the outer edges of the cluster, and then pulled by the gravitational pull of the galaxy itself, pushing some stars forward in their journey through the galaxy, while other stars are pulled further behind.

The GAIA team did find tidal tails on either side of the Hyades cluster when they observed it. However, they were extraordinarily long – thousands of light years across the galaxy, each holding thousands of stars. Observing them in their entirety was only possible because of the GAIA data and a computer model that Dr. Tereza Jerabkova, an ESA research fellow, developed with her colleagues.

The qubit is the building block of quantum computing, analogous to the bit in classical computers. To perform error-free calculations, quantum computers of the future are likely to need at least millions of qubits. The latest study, published in the journal PRX Quantum, suggests that these computers could be made with industrial-grade silicon chips using existing manufacturing processes, instead of adopting new manufacturing processes or even newly discovered particles.

For the study, researchers were able to isolate and measure the quantum state of a single electron (the qubit) in a silicon transistor manufactured using a ‘CMOS’ technology similar to that used to make chips in computer processors.

Furthermore, the spin of the electron was found to remain stable for a period of up to nine seconds. The next step is to use a similar manufacturing technology to show how an array of qubits can interact to perform quantum logic operations.

Many of us have been wracking our brains why Nvidia would spend a fortune – a whopping $40 billion – to acquire Arm Holdings, a chip architecture licensing company that generates on the order of $2 billion in sales – since the deal was rumored back in July 2020. As we sat and listened to the Arm Vision Day rollout of the Arm V9 architecture, which will define processors ranging from tiny embedded controllers in IoT device all the way up to massive CPUs in the datacenter, we may have figured it out.

There are all kinds of positives, as we pointed out in our original analysis ahead of the deal, in our analysis the day the deal was announced in September 2020, and in a one-on-one conversation with Nvidia co-founder and chief executive officer Jensen Huang in October 2020.

We have said for a long time that we believe that Nvidia needs to control its own CPU future, and even joked with Huang that it didn’t need to have to buy all of Arm Holdings to make the best Arm server CPU, to which he responded that this was truly a once-in-a-lifetime opportunity to create value and push all of Nvidia’s technologies – its own GPUs for compute and graphics and Mellanox network interface chips, DPU processors, and switch ASICs – through an Arm licensing channel to make them all as malleable and yet standardized as the Arm licensing model not only allows, but encourages.

When the researchers used their system to measure the qubits’ state, they achieved an accuracy of 98 percent, exactly the same as when they carried out the measurement using a conventional electrical cable.

The authors acknowledge that work is already underway to try and reduce the heat produced by current approaches, including the development of thinner wires, proposals to replace wires with superconducting cables, or a process called multiplexing that makes it possible to send many signals over the same cable simultaneously.

But optical fiber is a well-established technology, and is already replacing electrical wires in many areas of computing thanks to its ability to carry far more data. The authors also point out that components used in this experiment were designed to work at room temperature, so optimizing them for cryogenic temperatures could provide significant performance gains.