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Attosecond science, honored with the 2023 Nobel Prize in Physics, is transforming our understanding of how electrons move in atoms, molecules, and solids. An attosecond—equivalent to a billionth of a billionth of a second—enables “slow-motion” visualization of natural processes occurring at extraordinary speeds.

However, until now, most attosecond experiments have been limited to spectroscopic measurements due to the constraints of attosecond light pulse sources.

Using the powerful X-ray Free Electron Laser (FEL) at SLAC National Laboratory in California, the Hamburg team studied how interact with nanoparticles. They uncovered a previously unexplored phenomenon: transient ion resonances that enhance image brightness.

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Researchers at the University of Maine have managed to 3D print an organic building material with the strength of steel.

The SM2ART Nfloor is printed as a single piece in about 30 hours, which is a third faster than building something comparable by hand according to TechXplore.

The nice thing about this set-up is that these panels can be printed in bulk off-site and get shipped to the construction area. Since there are already channels in the floor for electrical and plumbing, the only other thing that needs to be applied by hand is soundproofing and floor covering.

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When 3D printing was first introduced in 1985, it marked a major turning point for the manufacturing industry. In addition to being cheaper than traditional manufacturing technologies, it also promised the ability to customize designs and make prototypes on demand. While its technology is still considered relatively new, there has been an accelerating demand for 3D printing methods across sectors in the past decade, ranging from aerospace and defense to medicine.

Yet, Associate Professor Pablo Valdivia y Alvarado from the Singapore University of Technology and Design (SUTD) believes that there are still ways to go before 3D printing can achieve its full potential. In traditional 3D printing, a nozzle is used to print the material layer by layer, and the path that the nozzle takes is known as the toolpath.

However, layer-by-layer printing is incompatible for use with materials like silicone, epoxies, and urethanes that are slow-curing and take more time to harden. These types of materials are often used to create soft mechanical metamaterials which, in turn, are used for lightweight, nature-inspired structures, such as lattices and web structures. Deposition-based processes in 3D printing, such as direct ink writing, would be able to work with these materials to create such structures, but these suffer from non-optimized toolpaths.

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“If you lease it like you lease a car, a $30,000 car, your price point per month is 300 bucks,” says author, futurist, investor, doctor, and engineer Peter Diamandis in a recent TechFirst podcast. “And that translates amazingly to $10 a day and 40 cents an hour. So you’ve got labor that’s waiting for whatever your wish is. You know, clean up the house, go mow the lawn, you know, please change the baby’s diapers.”

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In today’s AI news, a majority of senior executives across multiple industries expect AI to fundamentally reshape their businesses in the next 12 to 24 months, according to KPMG’s latest AI Quarterly Pulse Survey. According to the survey, 68% of executives plan to invest between $50M and $250M into GenAI over the next 12 months, marking a substantial increase from 45% in Q1 of 2024.

S chief AI scientist, Yann LeCun, the biggest takeaway from DeepSeek In other advancements, hot healthcare startup Rad AI has raised a Series C funding round. The company, which creates AI-powered tools for radiologists, grabbed $60 million dollars of fresh funding in a Series C round led by Transformation Capital, according to two sources, the new fundraise valued Rad AI at $525 million.

Meanwhile, Alphabet’s Google, already facing an unprecedented regulatory onslaught, is looking to shape public perception and policies on artificial intelligence ahead of a global wave of AI regulation. A key priority comes in building out educational programs to train the workforce on AI. “Getting more people and organizations, including governments, familiar with AI and using AI tools, makes for better AI policy and opens up new opportunities.”

T be fixated on the best big model … + Then, join renowned investor Ray Dalio of Bridgewater Associates, for an engaging fireside chat with Merantix Capital Co-Founder, Rasmus Rothe exploring the enormous potential of artificial intelligence in decision-making, innovation, and global investing.

And, artificial general intelligence could possess the versatility to reason, learn and innovate in any task. But with rising concerns about job losses, surveillance and deepfakes, will AGI be a force for progress or a threat to the very fabric of humanity?

Continue reading “KPMG Survey: 68% Of Execs Plan To Funnel Up To 0 Million Into AI In The Next Year” | >

Researchers hypothesize a fifth force of nature that could explain the intricate relationship between dark matter and dark energy, suggesting a revolutionary expansion of the Standard Model of physics.

Could a new, fifth force of nature help answer some of the biggest mysteries about dark matter and dark energy? Scientists are actively exploring the possibility.

The Standard Model of physics is widely regarded as one of the greatest achievements in modern science. It describes the universe’s four known forces — gravity, electromagnetism, and the strong and weak nuclear forces — as well as a diverse array of fundamental particles and their interactions. By many measures, it stands as one of the most successful scientific theories in history.

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SMC proteins can reverse direction, reshaping DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

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Examples of endosymbiosis are everywhere. Mitochondria, the energy factories in your cells, were once free-living bacteria. Photosynthetic plants owe their sun-spun sugars to the chloroplast, which was also originally an independent organism. Many insects get essential nutrients from bacteria that live inside them. And last year researchers discovered the “nitroplast,” an endosymbiont that helps some algae process nitrogen.

So much of life relies on endosymbiotic relationships, but scientists have struggled to understand how they happen. How does an internalized cell evade digestion? How does it learn to reproduce inside its host? What makes a random merger of two independent organisms into a stable, lasting partnership?

Now, for the first time, researchers have watched the opening choreography of this microscopic dance by inducing endosymbiosis in the lab. After injecting bacteria into a fungus—a process that required creative problem-solving (and a bicycle pump)—the researchers managed to spark cooperation without killing the bacteria or the host. Their observations offer a glimpse into the conditions that make it possible for the same thing to happen in the microbial wild.

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We report the use of a multiagent generative artificial intelligence framework, the X-LoRA-Gemma large language model (LLM), to analyze, design and test molecular design. The X-LoRA-Gemma model, inspired by biological principles and featuring ~7 billion parameters, dynamically reconfigures its structure through a dual-pass inference strategy to enhance its problem-solving abilities across diverse scientific domains. The model is used to first identify molecular engineering targets through a systematic human-AI and AI-AI self-driving multi-agent approach to elucidate key targets for molecular optimization to improve interactions between molecules. Next, a multi-agent generative design process is used that includes rational steps, reasoning and autonomous knowledge extraction. Target properties of the molecule are identified either using a Principal Component Analysis (PCA) of key molecular properties or sampling from the distribution of known molecular properties. The model is then used to generate a large set of candidate molecules, which are analyzed via their molecular structure, charge distribution, and other features. We validate that as predicted, increased dipole moment and polarizability is indeed achieved in the designed molecules. We anticipate an increasing integration of these techniques into the molecular engineering workflow, ultimately enabling the development of innovative solutions to address a wide range of societal challenges. We conclude with a critical discussion of challenges and opportunities of the use of multi-agent generative AI for molecular engineering, analysis and design.

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