Tesla is poised for significant growth and expansion, driven by advancements in its Full Self-Driving technology, robotaxi initiatives, and strategic partnerships, which could lead to a major increase in its stock value ## ## Questions to inspire discussion.
Tesla’s FSD and Robotaxi Advancements.
🚗 Q: What major update is coming to Tesla’s Full Self-Driving (FSD) system? A: A new FSD model with 10x more parameters is expected to be ready for public release by the end of next month, offering a big leap forward in capabilities.
🛣️ Q: How much safer is Tesla’s FSD compared to human drivers? A: Tesla’s FSD is reported to be 10x safer than human drivers, with the new model expected to provide a magnitude increase in safety and features.
🚕 Q: How is Tesla’s Robotaxi service expanding? A: Tesla’s Robotaxi service is expanding rapidly, with the geofenced area in Austin quadrupled to 80 square miles in just 42 days, and ride-hailing launched in California.
Tesla’s Strategic Moves.
A team of researchers from the Spanish National Research Council has made a significant advance in plant biotechnology by developing a new method for silencing genes. The novel technique uses ultra-short ribonucleic acid (RNA) sequences carried by genetically modified viruses to achieve genetic silencing, allowing the customization of plant traits. The work, published in the Plant Biotechnology Journal, opens up new avenues for crop improvement, functional genomics, and sustainable agriculture.
Viral vector technology involves modifying viruses, removing the genetic material that causes disease, to turn them into vehicles that carry the RNA sequence to be introduced into an organism. This technique, when applied to plants, has already proven effective under experimental conditions in inducing flowering and accelerating the development of improved crop varieties, modifying plant architecture to facilitate adaptation to mechanization, improving drought tolerance, and producing metabolites beneficial to human health, among other applications.
Now, the method developed by the CSIC, together with the Valencian University Institute for Research on the Conservation and Improvement of Agrodiversity (COMAV) and the Italian Department of Applications and Innovation in Supercomputing (Cineca), represents an optimization of technological platforms to accelerate the development and validation of agricultural applications based on viral vectors.
The first black hole images stunned the world in 2019, with headlines announcing evidence of a glowing doughnut-shaped object from the center of galaxy Messier 87 (M87 —55 million light years from Earth. Supercomputer simulations are now helping scientists sharpen their understanding about the environment beyond a black hole’s ‘shadow,’ material just outside its event horizon.
This report reviews the construction and potential use of FTQC (Fault Tolerant Quantum Computing) computers to reliably perform complex calculations by overcoming the problems posed by the errors and noise inherent in quantum systems.
After recalling the reality of the quantum advantage and its needs, the report describes the use of error-correcting codes in the design of FTQCi computers. It then reports on the progress of the five most advanced physical technologies in the world for building such computers and the obstacles they will have to face in order to achieve the transition to scale necessary for the execution of useful applications. Finally, it discusses the technical and economic environment for quantum computers, how their performance can be compared and evaluated, and their future coexistence with other computing technologies (3D silicon, AI) or with supercomputers.
Used as a versatile material in industry and health care, magnesium oxide may also be a good candidate for quantum technologies. Research led by the U.S. Department of Energy’s (DOE) Argonne National Laboratory and published in npj Computational Materials reveals a defect in the mineral that could be useful for quantum applications.
Researchers are exploring possible building blocks, known as qubits, for systems that could exploit quantum properties. These systems could operate in various devices that may outperform classical supercomputers, form unhackable networks or detect the faintest signals.
Unlocking the potential of qubits for applications such as quantum computing, sensing and communications requires an understanding of materials on the atomic scale.
Scientists have been studying a fascinating material called uranium ditelluride (UTe₂), which becomes a superconductor at low temperatures.
Superconductors can carry electricity without any resistance, and UTe₂ is special because it might belong to a rare type called spin-triplet superconductors. These materials are not only resistant to magnetic fields but could also host exotic quantum states useful for future technologies.
However, one big mystery remained: what is the symmetry of UTe₂’s superconducting state? This symmetry determines how electrons pair up and move through the material. To solve this puzzle, researchers used a highly sensitive tool called a scanning tunneling microscope (STM) with a superconducting tip. They found unique signals—zero-energy surface states—that helped them compare different theoretical possibilities.
Their results suggest that UTe₂ is a nonchiral superconductor, meaning its electron pairs don’t have a preferred handedness (like left-or right-handedness). Instead, the data points to one of three possible symmetries (B₁ᵤ, B₂ᵤ, or B₃ᵤ), with B₃ᵤ being the most likely if electrons scatter in a particular way along one axis.
This discovery brings scientists closer to understanding UTe₂’s unusual superconducting behavior, which could one day help in designing more robust quantum materials.
UTe₂ currently operates at very low temperatures (~1.6 K), so raising its critical temperature is a major goal.
Scaling up production and integrating it into devices will require further material engineering.
Scientists at the University of Stuttgart’s Institute of Aerodynamics and Gas Dynamics (IAG) have produced a novel dataset that will improve the development of turbulence models. With the help of the Hawk supercomputer at the High-Performance Computing Center Stuttgart (HLRS), investigators in the laboratory of Dr. Christoph Wenzel conducted a large-scale direct numerical simulation of a spatially evolving turbulent boundary layer.
Using more than 100 million CPU hours on Hawk, the simulation is unique in that it captures the onset of a canonical, fully-developed turbulent state in a single computational domain. The study also identified with unprecedented clarity an inflection point at which the outer region of the turbulent boundary layer begins to maintain a self-similar structure as it moves toward high Reynolds numbers. The results appear in a new paper published in the Journal of Fluid Mechanics.
“Our team’s goal is to understand unexplored parameter regimes in turbulent boundary layers,” said Jason Appelbaum, a Ph.D. candidate in the Wenzel Lab and leader of this research. “By running a large-scale simulation that fully resolves the entire development of turbulence from an early to an evolved state, we have generated the first reliable, full-resolution dataset for investigating how high-Reynolds-number effects emerge.”