The price of computer storage since the 1950s.
From:
This chart shows the dramatic fall in the price of computer storage between 1956 and 2023. It relies on the data carefully collected by the computer scientist John C. McCallum.
Light measurement devices called optical frequency combs have revolutionized metrology, spectroscopy, atomic clocks, and other applications. Yet challenges with developing frequency comb generators at a microchip scale have limited their use in everyday technologies such as handheld electronics.
For the first time, nuclear physicists have made precision measurements of a short-lived radioactive molecule, radium monofluoride (RaF). In their study published in the journal Nature Physics, the researchers combined ion-trapping techniques with specialized laser systems to measure the fine details of the quantum structure of RaF.
By Morgan Sherburne, University of Michigan
University of Michigan physicists have devised a way to manipulate active fluids, a type of fluid composed of individual units that can propel themselves independently, by taking advantage of topological defects in the fluids.
An international research team including Los Alamos National Laboratory and Tel Aviv University has developed a unique, mechanical metamaterial that, like a computer following instructions, can remember the order of actions performed on it. Named Chaco, after the archaeological site in northern New Mexico, the new metamaterial offers a route to applications in memory storage, robotics, and even mechanical computing.
Be sure to look at the night sky on June 3rd to see a somewhat rare event called a large ‘planetary parade.’
OpenAI has landed itself in hot water for pushing out an update to ChatGPT that features a virtual assistant with an uncanny vocal resemblance to Scarlett Johansson — and it could be staring down the barrel of a compelling lawsuit.
Almost instantly, comparisons to the movie “Her” abounded, in which the actress plays a chatbot named Samantha that falls in love with a lonely man. Had OpenAI just aped her role — and her voice? Officially, it said no. Then, Johansson dropped a bombshell: leadership at the AI startup had in fact asked permission to use her voice last year. She said no, and they did it anyway.
Two anecdotes and charts: Women’s and men’s college graduation rates.
Anecdote:
I gave an extra-credit assignment in one of my courses. The course had twenty students, eleven men and nine women. Six students chose to do the assignment — and then I noticed something in my grade book: all of them were women. Getting all statistic-y about it: 66.7% of the females were willing to do the extra work, while 0% if the men were.
Anecdotal, but fascinating.
The codes to replicate the simulations of the paper: Available at: https://arxiv.org/abs/2405.12832 and also: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4835325
For now, we just added the codes to…
In this paper, we introduce Wav-KAN, an innovative neural network architecture that leverages the Wavelet Kolmogorov-Arnold Networks (Wav-KAN) framework to enhance interpretability and performance. Traditional multilayer perceptrons (MLPs) and even recent advancements like Spl-KAN \cite{kan} face challenges related to interpretability, training speed, robustness, computational efficiency, and performance. Wav-KAN addresses these limitations by incorporating wavelet functions into the Kolmogorov-Arnold network structure, enabling the network to capture both high-frequency and low-frequency components of the input data efficiently. Wavelet-based approximations employ orthogonal or semi-orthogonal basis and also maintains a balance between accurately representing the underlying data structure and avoiding overfitting to the noise. Analogous to how water conforms to the shape of its container, Wav-KAN adapts to the data structure, resulting in enhanced accuracy, faster training speeds, and increased robustness compared to Spl-KAN and MLPs. Our results highlight the potential of Wav-KAN as a powerful tool for developing interpretable and high-performance neural networks, with applications spanning various fields. This work sets the stage for further exploration and implementation of Wav-KAN in frameworks such as PyTorch, TensorFlow, and also it makes wavelet in KAN in wide-spread usage like nowadays activation functions like ReLU, sigmoid in universal approximation theory (UAT).
O.o!!!
The highly unstable radioactive element promethium is hard to study in the lab, but chemists have now coaxed it into forming a compound in water so they can observe its bonding behaviour.