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In 2023, the ATLAS collaboration, which provided its first W boson mass measurement in 2017, released an improved measurement based on a reanalysis of proton–proton collision data from the first run of the LHC. This improved result, 80,366.5 MeV with an uncertainty of 15.9 MeV, lined up with all previous measurements except the CDF measurement, which remains the most precise to date, with a precision of 0.01%.

The CMS experiment has now contributed to this global endeavor with its first W boson mass measurement. The keenly anticipated result, 80,360.2 with an uncertainty of 9.9 MeV, has a precision comparable to that of the CDF measurement and is in line with all previous measurements except the CDF result.

“The wait for the CMS result is now over. After carefully analyzing data collected in 2016 and going through all the cross checks, the CMS W mass result is ready,” says outgoing CMS spokesperson Patricia McBride. “This analysis is the first attempt to measure the W mass in the harsh collision environment of the second running period of the LHC. And all the hard work from the team has resulted in an extremely precise W mass measurement and the most precise measurement at the LHC.”

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After about 6 prompts, ChatGPT o1’s preview and mini create a running version of the code described from the methods section of my research paper. I do want to emphasize that while the skeletal code does emulate what my code does, it did use its own synthetic data I asked for it to create as opposed to real astronomical data that would be used in a real paper. Nevertheless, the potential it has is incredible, to effectively accomplish what I struggled for about 10 months in my first year of my PhD. I am excited to apply o1 for other use cases. Thank you to everyone who tuned in live last night! #ai #openaio1 ##chatgpt

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SambaNova Systems has just unveiled a new demo on Hugging Face, offering a high-speed, open-source alternative to OpenAI’s o1 model.

This demonstration is important because it shows that freely available AI models can…

SambaNova challenges OpenAI’s o1 model with Llama 3.1-powered demo on HuggingFace https://venturebeat.com/ai/sambanova-challenges-openais-o1-m…ggingface/

SambaNova Systems has just unveiled a…

Continue reading “RDU: The GPU Alternative” | >

Some recent dark matter experiments have begun employing levitated optomechanical systems. Kilian et al. explored how levitated large-mass sensors and dark matter research intersect.

Levitated sensors are quantum technology platforms that use magnetic fields, electric fields, or light to levitate and manipulate particles, which become very sensitive to weak forces. These sensors are especially well suited for detecting candidates in regimes where current large-scale experiments suffer limitations, such as ultralight and certain hidden-sector candidates.

The authors discussed how these advantages make levitated sensors, including optically trapped silica nanoparticles, magnetically trapped ferromagnets, and levitated superconducting particles, ideal for detecting different dark matter candidates.

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Getting tips from the design of the human body.

Scientists create bone-inspired cement, over five times stronger than concrete.

Researchers at the University of Princeton have developed a cement paste that is 5.6 times stronger than cement, mortar, and other conventional cement-based construction materials.

Continue reading “Human bone-inspired cement is 5 times tougher than standard concrete” | >

Question Can microplastics reach the olfactory bulb in the human brain?

Findings This case series analyzed the olfactory bulbs of 15 deceased individuals via micro-Fourier transform infrared spectroscopy and detected the presence of microplastics in the olfactory bulbs of 8 individuals. The predominant shapes were particles and fibers, with polypropylene being the most common polymer.

Meaning The presence of microplastics in the human olfactory bulb suggests the olfactory pathway as a potential entry route for microplastics into the brain, highlighting the need for further research on their neurotoxic effects and implications for human health.

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Not only will these export controls be increasingly difficult to implement, but they would also unlikely be in the best interests of the United States. Indeed, the current trajectory of export policies risks unintended consequences for little long-term strategic benefit. These include a decline in the competitiveness of the United States, a decoupling from U.S.-developed technology, and uncertainty for the domestic tech industry, amongst other risks.

A Better Way Forward

For the United States to maintain its global AI leadership, it must focus on competition and outcompeting its geopolitical rivals in the development, implementation, and diffusion of AI-based systems domestically and internationally instead of an expert-control-first approach. Defending against the rise of digital authoritarianism requires embracing competition and openness, enabling effective market access, and supporting the diffusion of U.S. AI-enabled technology and governance standards.

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