Lifeboat Foundation

In a press release, Bujack, who creates scientific visualizations at Los Alamos National Laboratory, called the current mathematical models used for color perceptions incorrect and requiring a “paradigm shift.”

A surprise finding

Being able to accurately model human color perception has a tremendous impact on automating image processing, computer graphics, and visualization. Bujack’s team first set out to develop algorithms that would automatically enhance color maps used in data visualization to make it easier to read them.

We are beginning to roll out new voice and image capabilities in ChatGPT. They offer a new, more intuitive type of interface by allowing you to have a voice conversation or show ChatGPT what you’re talking about.

Voice and image give you more ways to use ChatGPT in your life. Snap a picture of a landmark while traveling and have a live conversation about what’s interesting about it. When you’re home, snap pictures of your fridge and pantry to figure out what’s for dinner (and ask follow up questions for a step by step recipe). After dinner, help your child with a math problem by taking a photo, circling the problem set, and having it share hints with both of you.

We’re rolling out voice and images in ChatGPT to Plus and Enterprise users over the next two weeks. Voice is coming on iOS and Android (opt-in in your settings) and images will be available on all platforms.

The researchers compiled an extensive dataset of over 1,200 distinct cell groups, estimating size ranges, mass, and cell counts for each group across 60 tissue systems in three reference humans — an adult man, woman, and child.

“For the first time, we have systematically measured the size and abundance of cells across all major tissues and organs,” said Dr. Hatton. This spans seven orders of magnitude from tiny red blood cells to large muscle fibers.

While many contemporary works focus on molecular profiling, this study adopts a classical cell biology approach, quantifying morphological features of known cell types. The team integrated decades of histological and anatomical research to establish a framework. They discovered a striking near-inverse relationship between cell size and abundance, implying a trade-off between the two variables.

Peter Atkins, James Ladyman, and Joanna Kavenna argue over the existence of physical reality.

Watch the full debate at https://iai.tv/video/the-world-that-disappeared?utm_source=Y…escription.

Continue reading “Is physical reality a hoax | Peter Atkins, James Ladyman, Joanna Kavenna” »

By stepping outside the box of our usual way of thinking about numbers, my colleagues and I have recently shown that arithmetic has biological roots and is a natural consequence of how perception of the world around us is organized.

Our results explain why arithmetic is true and suggest that mathematics is a realization in symbols of the fundamental nature and creativity of the mind.

Thus, the miraculous correspondence between mathematics and physical reality that has been a source of wonder from the ancient Greeks to the present—as explored in astrophysicist Mario Livio’s book Is God a Mathematician?—suggests the mind and world are part of a common unity.

Google DeepMind researchers recently developed a technique to improve math ability in AI language models like ChatGPT by using other AI models to improve prompting—the written instructions that tell the AI model what to do. It found that using human-style encouragement improved math skills dramatically, in line with earlier results.

In a paper called “Large Language Models as Optimizers” listed this month on arXiv, DeepMind scientists introduced Optimization by PROmpting (OPRO), a method to improve the performance of large language models (LLMs) such as OpenAI’s ChatGPT and Google’s PaLM 2. This new approach sidesteps the limitations of traditional math-based optimizers by using natural language to guide LLMs in problem-solving. “Natural language” is a fancy way of saying everyday human speech.

A team of researchers in Japan claims to have figured out a way to translate the clucking of chickens with the use of artificial intelligence.

As detailed in a yet-to-be-peer-reviewed preprint, the team led by University of Tokyo professor Adrian David Cheok — who has previously studied sex robots — came up with a “system capable of interpreting various emotional states in chickens, including hunger, fear, anger, contentment, excitement, and distress” by using “cutting-edge AI technique we call Deep Emotional Analysis Learning.”

They say the technique is “rooted in complex mathematical algorithms” and can even be used to adapt to the ever-changing vocal patterns of chickens, meaning that it only gets better at deciphering “chicken vocalizations” over time.

A book-length thought experiment uses math to investigate some of life’s big questions.

Scientists from the University of Texas at Dallas have identified a previously unknown “housekeeping” process in kidney cells that ejects unwanted content, resulting in cells that rejuvenate themselves and remain functioning and healthy.

This unique self-renewal method, distinct from known regeneration processes in other body tissues, sheds light on how the kidneys can maintain their health throughout one’s life in the absence of injury or illness. The team detailed their findings in a study recently published in Nature Nanotechnology.

Unlike the liver and skin, where cells divide to create new daughter cells and regenerate the organ, cells in the proximal tubules of the kidney are mitotically quiescent — they do not divide to create new cells. In cases of a mild injury or disease, kidney cells do have limited repair capabilities, and stem cells in the kidney can form new kidney cells, but only up to a point, said Dr. Jie Zheng, professor of chemistry and biochemistry in the School of Natural Sciences and Mathematics and co-corresponding author of the study.