Lifeboat Foundation

Scientists may be one step closer to unraveling one of the universe’s greatest mysteries. Their recent calculations suggest that neutron stars could play a crucial role in shedding light on the mysterious dark matter.

In a paper published in The Journal of Cosmology and Astroparticle Physics, physicists from the ARC Centre of Excellence for Dark Matter Particle Physics, led by the University of Melbourne, calculated that energy transferred when dark matter particles collide and annihilate inside cold dead neutron stars can heat the stars up very quickly.

It was previously thought that this energy transfer could take a very long time, in some cases, longer than the age of the universe itself, rendering this heating irrelevant.

The AI boom and soaring demand for Nvidia GPUs have propelled the company’s stock and earned the Nvidia CEO a reputation as a visionary. Even Mark Zuckerberg calls him the “Taylor Swift of tech.”

People who have worked for Huang on Nvidia’s journey to become a $3 trillion-plus company previously described how he can be a “demanding” boss.

Eight current and former Nvidia employees spoke to Business Insider about Huang’s leadership style and what it’s like to be grilled by him. These people asked not to be named as they were not authorized to speak to the media.

National University of Singapore (NUS) chemists have developed hexavalent photocatalytic covalent organic frameworks (COFs) which mimic natural photosynthesis for the production of hydrogen peroxide (H 2 O₂), an important industrial chemical.

The conventional method of H 2 O₂ production involves using anthraquinone as a catalyst to convert air and hydrogen into H 2 O₂. However, this process requires substantial energy, costly noble metal catalysts, high-pressure hydrogen gas and hazardous solvents. Artificial photosynthesis of H 2 O₂, resembling the natural photosynthesis process with the use of sunlight as an energy source and abundant water and air as feedstocks, presents a sustainable and promising alternative to the conventional anthraquinone process.

However, such an artificial system faces three key challenges: insufficient charge carrier generation and fast charge recombination, which lowers the efficiency; limited number of available catalytic sites, which results in low productivity; and lack of efficient delivery of charges and reactants to the catalytic sites, which causes sluggish reaction kinetics.

This is the question of the origin of our Universe. Every star, every galaxy and every planet we see came from the Big Bang. But what was before it?

Is dark matter primordial black holes? If so, could we find them using Apollo-era technology on the moon?
A new paper suggests the answer may be yes to both. I interviewed David Kaiser, one of the paper’s co-authors, former student of inflationary cosmology pioneer Alan Guth, and now Professor of Physics and Professor of the History of Science at MIT.
For the preprint of the full paper:
https://arxiv.org/pdf/2310.16877
and other press about the paper.
https://www.lrb.co.uk/the-paper/v46/n…
https://news.mit.edu/2024/exotic-blac…
And some other related papers:
https://journals.aps.org/prl/abstract…
https://arxiv.org/abs/2303.02168
https://arxiv.org/abs/2312.17217
a timeline is below.
00:00 introduction.
00:57 primordial black holes.
3:05 particle dark matter and modified gravity.
6:33 LIGO and EHT
11:03 window of opportunity.
15:16 observaitonal signatures.
20:30 Apollo era tech.
25:19 Star Wars.
25:54 the future.

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Be sure to check out the Infinite Series episode Singularities Explained • Singularities Explained | Infinite Se… or How I Learned to Stop Worrying and Divide by Zero.

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And manufacturers are keen to bring additional screens into play, from 2009’s Lenovo’s Thinkpad W700 with its built-in extendable tablet to modern devices like the Asus ZenBook Duo, or Lenovo Yoga Book 9i — and some frankly absurd variants along the way.

But what’s next for the laptop? Will it be Lenovo’s transparent laptop or will AI transform the laptop into handheld devices like how the Steam Deck and ROG Ally X represent a potential reinvention of the gaming laptop? Well, in my opinion, and many others, the next step is augmented reality.

Modern laptops are stuck between two desires, smaller form factors and larger displays. Both of which have their benefits, but you can’t gain more of one without giving up some of the other.

Wetware computing and organoid intelligence is an emerging research field at the intersection of electrophysiology and artificial intelligence. The core concept involves using living neurons to perform computations, similar to how Artificial Neural Networks (ANNs) are used today. However, unlike ANNs, where updating digital tensors (weights) can instantly modify network responses, entirely new methods must be developed for neural networks using biological neurons. Discovering these methods is challenging and requires a system capable of conducting numerous experiments, ideally accessible to researchers worldwide. For this reason, we developed a hardware and software system that allows for electrophysiological experiments on an unmatched scale. The Neuroplatform enables researchers to run experiments on neural organoids with a lifetime of even more than 100 days. To do so, we streamlined the experimental process to quickly produce new organoids, monitor action potentials 24/7, and provide electrical stimulations. We also designed a microfluidic system that allows for fully automated medium flow and change, thus reducing the disruptions by physical interventions in the incubator and ensuring stable environmental conditions. Over the past three years, the Neuroplatform was utilized with over 1,000 brain organoids, enabling the collection of more than 18 terabytes of data. A dedicated Application Programming Interface (API) has been developed to conduct remote research directly via our Python library or using interactive compute such as Jupyter Notebooks. In addition to electrophysiological operations, our API also controls pumps, digital cameras and UV lights for molecule uncaging. This allows for the execution of complex 24/7 experiments, including closed-loop strategies and processing using the latest deep learning or reinforcement learning libraries. Furthermore, the infrastructure supports entirely remote use. Currently in 2024, the system is freely available for research purposes, and numerous research groups have begun using it for their experiments. This article outlines the system’s architecture and provides specific examples of experiments and results.

The recent rise in wetware computing and consequently, artificial biological neural networks (BNNs), comes at a time when Artificial Neural Networks (ANNs) are more sophisticated than ever.

The latest generation of Large Language Models (LLMs), such as Meta’s Llama 2 or OpenAI’s GPT-4, fundamentally rely on ANNs.

Monolayer 2D semiconductors, such as WS2, exhibit uniquely strong light–matter interactions due to exciton resonances that enable atomically thin optical elements. Similar to geometry-dependent plasmon and Mie resonances, these intrinsic material resonances offer coherent and tunable light scattering. Thus far, the impact of the excitons’ temporal dynamics on the performance of such excitonic metasurfaces remains unexplored. Here, we show how the excitonic decay rates dictate the focusing efficiency of an atomically thin lens carved directly out of exfoliated monolayer WS2. By isolating the coherent exciton radiation from the incoherent background in the focus of the lens, we obtain a direct measure of the role of exciton radiation in wavefront shaping. Furthermore, we investigate the influence of exciton–phonon scattering by characterizing the focusing efficiency as a function of temperature, demonstrating an increased optical efficiency at cryogenic temperatures. Our results provide valuable insights into the role of excitonic light scattering in 2D nanophotonic devices.