Engineering the tunability of protein assembly in response to pH changes within a narrow range is challenging. Here the authors report the de novo computational design of pH-responsive protein filaments that exhibit rapid, precise, tunable and reversible assembly and disassembly triggered by small pH changes.
The third proof point is both the increase in manufacturing capacity investment and the change in how that investment will be managed. With the interest in governments to secure future semiconductor manufacturing for both supply security and economic growth, Mr. Gelsinger went on a spending spree with investment in expanding capacity in Oregon, Ireland, and Israel, as well as six new fabs in Arizona, Ohio, and Germany. Most of the initial investment was made without the promise of government grants, such as the US Chips Act. However, Intel has now secured more than $50B from US and European government incentives, customer commitments starting with its first five customers on the 18A process node, and its financial partners. Intel has also secured an additional $11B loan from the US government and a 25% investment tax credit.
In addition to it’s own investment in fab capacity, Intel is partnering with Tower Semiconductor and UMC, two foundries with long and successful histories. Tower will be investing in new equipment to be installed in Intel’s New Mexico facility for analog products, and UMC will partner with Intel to leverage three of the older Arizona fabs and process nodes, starting with the 12nm, to support applications like industrial IoT, mobile, communications infrastructure, and networking.
The second side of this investment is how current and future capacity will be used. As strictly an IDM, Intel has historically capitalized on its investments in the physical fab structures by retrofitting the fabs after three process nodes, on average. While this allowed for the reuse of the structures and infrastructure, it eliminated support for older process nodes, which are important for many foundry customers. According to Omdia Research, less than 3% of all semiconductors are produced on the latest process nodes. As a result, Intel is shifting from retrofitting fabs for new process nodes to maintaining fabs to support extended life cycles of older process nodes, as shown in the chart below. This requires additional capacity for newer process nodes.
A team of MIT researchers has addressed significant barriers to the practical application of 2D magnetic materials. This innovation will enable the development of the next generation of energy-efficient computers.
The team achieved a notable breakthrough by developing a “van der Waals atomically layered heterostructure” device. The device connects two 2D materials: tungsten ditelluride and iron gallium telluride, a 2D van der Waals magnet.
By Jade Boyd, Rice University
Rice University physicists have discovered a phase-changing quantum material—and a method for finding more like it—that could potentially be used to create flash-like memory capable of storing quantum bits of information, or qubits, even when a quantum computer is powered down.
Microsoft is on the verge of a major quantum computing breakthrough in collaboration with Quantinuum. In a recent announcement, the tech giant indicated that it ran more than 14,000 experiments without encountering a single error.
The company attributes this to Quantinuum’s ion-trap hardware alongside its new qubit-virtualization system. It unlocked this impressive feat because the system allows the team to check logical qubits, thus presenting an opportunity to correct any errors without affecting the progress.
The researchers behind the breakthrough spread the quantum information across groups of connected quantum bits to form logic qubits. Per the report, the team used 30 qubits to make four logical qubits. It was through this process that the team was able to run countless experiments without encountering any errors.
The human brain is a remarkably complex organ, consisting of billions of interconnected neurons. It can be divided into distinct regions, each with specific functions, such as memory and decision-making. Cognition, which includes processes like perception, memory, language, and problem-solving, is all orchestrated by the brain. It’s through these cognitive processes that we perceive and interact with the world around us.
What is special about the structure of the brain compared to other organs? What is the principled way of understanding how the brain works? How does the brain contribute to our sense of Self? Is it possible to compare the brain with the computer? Is it possible to enhance the way that the brain works? What is the brain-basis of language?
Continue reading “Exploring the Brain: from Synapses to Cognition” »
Our everyday electronic devices, such as living room lights, washing machines, and televisions, operate thanks to electrical currents. Similarly, the functioning of computers is based on the manipulation of information by small charge carriers known as electrons. Spintronics, on the other hand, introduces a unique approach to this process.
Instead of the charge of electrons, the spintronic approach is to exploit their magnetic moment, in other words, their spin, to store and process information – aiming to make the computers of the future more compact, fast, and sustainable. One way of processing information based on this approach is to use the magnetic vortices called skyrmions or, alternatively, their still little understood and rarer cousins called ‘merons’. Both are collective topological structures formed of numerous individual spins. Merons have to date only been observed in natural antiferromagnets, where they are difficult to both analyze and manipulate.
David Kaplan has developed a lattice model for particles that are left-or right-handed, offering a firmer foundation for the theory of weak interactions.
David Kaplan is on a quest to straighten out chirality, or “handedness,” in particle physics. A theorist at the University of Washington, Seattle, Kaplan has been wrestling with chirality conundrums for over 30 years. The main problem he has been working on is how to place chiral particles, such as left-handed electrons or right-handed antineutrinos, on a discrete space-time, or “lattice.” That may sound like a minor concern, but without a solution to this problem the weak interaction—and by extension the standard model of particle physics—can’t be simulated on a computer beyond low-energy approximations. Attempts to develop a lattice theory for chiral particles have run into model-dooming inconsistencies. There’s even a well-known theorem that says the whole endeavor should be impossible.
Kaplan is unfazed. He has been a pioneer in formulating chirality’s place in particle physics. One of his main contributions has been to show that some of chirality’s problems can be solved in extra dimensions. Kaplan has now taken this extra-dimension strategy further, showing that reducing the boundaries, or edges, around the extra dimensions can help keep left-and right-handed particle states from mixing [1, 2]. With further work, he believes this breakthrough could finally make the lattice “safe” for chiral particles. Physics Magazine spoke to Kaplan about the issues surrounding chirality in particle physics.
Scientists used a technique called ‘active syndrome extraction’ to build four logical qubits from 30 physical ones and run 14,000 experiments without detecting a single error.
A theory of consciousness should capture its phenomenology, characterize its ontological status and extent, explain its causal structure and genesis, and describe its function. Here, I advance the notion that consciousness is best understood as an operator, in the sense of a physically implemented transition function that is acting on a representational substrate and controls its temporal evolution, and as such has no identity as an object or thing, but (like software running on a digital computer) it can be characterized as a law. Starting from the observation that biological information processing in multicellular substrates is based on self organization, I explore the conjecture that the functionality of consciousness represents the simplest algorithm that is discoverable by such substrates, and can impose function approximation via increasing representational coherence. I describe some properties of this operator, both with the goal of recovering the phenomenology of consciousness, and to get closer to a specification that would allow recreating it in computational simulations.
