In a first, scientists have recreated the formation of the first ever molecules in the universe to learn more about early star formation.
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Terra Quantum Brings Quantum Gravity to Quantum Computing: Advance Reduces Errors Without Added Complexity
Terra Quantum has published a groundbreaking advance in quantum error correction that redefines how we scale quantum computing. In the peer-reviewed paper “QMM-Enhanced Error Correction: Demonstrating Reversible Imprinting and Retrieval for Robust Quantum Computation”, Terra Quantum scientists present QMM-Enhanced Error Correction, a hardware-validated, measurement-free method for suppressing quantum errors, based on principles derived initially from quantum gravity.
At the heart of this innovation is the Quantum Memory Matrix (QMM), a cosmology-inspired concept that models space-time as a lattice of finite-dimensional memory cells. Terra Quantum has now translated this deep theoretical idea into a functional quantum circuit. Validated on IBM’s superconducting processors, the QMM layer functions as a lightweight, unitary “booster” that enhances fidelity without mid-circuit measurements or added two-qubit gates, offering a powerful alternative to traditional surface codes.
“We have taken a concept rooted in quantum gravity and made it plug-and-play for today’s quantum processors,” said Florian Neukart, Chief Product Officer at Terra Quantum. “QMM-enhanced error correction works out of the box on existing hardware, requires no architectural changes, and delivers measurable gains. For industries building quantum solutions now, not in 10 years. This is a game-changer.
Terra Quantum has introduced QMM-Enhanced Error Correction, a hardware-validated, measurement-free method that suppresses quantum errors.
Johns Hopkins APL Takes a Quantum Approach to Tracking Online Trends
Researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, have demonstrated that a quantum algorithm can be used to speed up an information analysis task that classical computers struggle to perform.
The innovation tackles a key element of information operations: tracking and attributing topics and narratives as they emerge and evolve online, which can help analysts spot indications of potential terrorist acts, for example. This involves using computers to perform what’s known as semantic text similarity analysis, or comparing the similarities within a textual dataset — not just the similarity of the words, but the meaning behind them, which makes it possible to identify related texts even if they don’t share any common keywords.
“The amount of open-source text data online — on social media platforms especially — is growing dramatically, and our ability to analyze all of that data has not kept pace with our ability to collect it,” said Roxy Holden, a mathematician at APL and principal investigator of this effort. “Intelligence analysts have limited resources, so finding better ways to automate this kind of analysis is critical for the military and the intelligence community.”
APL researchers have demonstrated that a quantum algorithm can be used to speed up an information analysis task that classical computers struggle to perform.
World First: Scientists Film The Exact Moment a Human Embryo Implants
Scientists have for the first time ever filmed a crucial step that leads to new human life – cracking open a ‘black box’ of early development, and potentially helping with fertility treatments.
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A research team headed by the University of Zurich has developed a powerful new method to precisely edit DNA by combining cutting-edge genetic engineering with artificial intelligence. This technique opens the door to more accurate modeling of human diseases and lays the groundwork for next-generation gene therapies.
Precise and targeted DNA editing by small point mutations as well as the integration of whole genes via CRISPR/Cas technology has great potential for applications in biotechnology and gene therapy. However, it is very important that the so-called gene scissors do not cause any unintended genetic changes, but maintain genomic integrity to avoid unintended side effects. Normally, double-stranded breaks in the DNA molecule are accurately repaired in humans and other organisms. But occasionally, this DNA end joining repair results in genetic errors.
Gene editing with greatly improved precision Now, scientists from the University of Zurich (UZH), Ghent University in Belgium and the ETH Zurich have developed a new method which greatly improves the precision of genome editing. Using artificial intelligence (AI), the tool called Pythia predicts how cells repair their DNA after it is cut by gene editing tools such as CRISPR/Cas9. “Our team developed tiny DNA repair templates, which act like molecular glue and guide the cell to make precise genetic changes,” says lead author Thomas Naert, who pioneered the technology at UZH and is currently a postdoc at Ghent University.
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This “smart coach” helps LLMs switch between text and code
Large language models (LLMs) excel at using textual reasoning to understand the context of a document and provide a logical answer about its contents. But these same LLMs often struggle to correctly answer even the simplest math problems.
Textual reasoning is usually a less-than-ideal way to deliberate over computational or algorithmic tasks. While some LLMs can generate code like Python to handle symbolic queries, the models don’t always know when to use code, or what kind of code would work best.
LLMs, it seems, may need a coach to steer them toward the best technique.
Enter CodeSteer, a smart assistant developed by MIT researchers that guides an LLM to switch between code and text generation until it correctly answers a query. (Strangely like a text editor “CodeSteer”🤔)
CodeSteer is a smart assistant from MIT that automatically guides large language models to switch between generating text and code, and to refine its response, until it answers a query correctly.
Dark Matter: A Parallel Universe? New Breakthrough Explained! | WION Podcast
A groundbreaking new study suggests that dark matter, one of the universe’s biggest mysteries, could be the result of a parallel universe. Researchers argue that the unseen, gravitationally interacting matter might be the interaction between our universe and another, previously undetected one. The study explores how this hypothesis could explain the effects of dark matter that have been observed in galaxies and cosmic structures. The idea challenges the current understanding of physics and opens new avenues for research into the nature of reality. This revelation could transform our approach to cosmology, potentially leading to a deeper understanding of the universe and its fundamental forces. The implications of such a discovery could revolutionize how we perceive space, time, and matter.
#science #space #wionpodcast.
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