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“In your machine-learning project, how much time will you typically spend on data preparation and transformation?” asks a 2022 Google course on the Foundations of Machine Learning (ML). The two choices offered are either “Less than half the project time” or “More than half the project time.” If you guessed the latter, you would be correct; Google states that it takes over 80 percent of project time to format the data, and that’s not even taking into account the time needed to frame the problem in machine-learning terms.

“It would take many weeks of effort to figure out the appropriate model for our dataset, and this is a really prohibitive step for a lot of folks that want to use machine learning or biology,” says Jacqueline Valeri, a fifth-year PhD student of biological engineering in Collins’s lab who is first co-author of the paper.

BioAutoMATED is an automated machine-learning system that can select and build an appropriate model for a given dataset and even take care of the laborious task of data preprocessing, whittling down a months-long process to just a few hours. Automated machine-learning (AutoML) systems are still in a relatively nascent stage of development, with current usage primarily focused on image and text recognition, but largely unused in subfields of biology, points out first co-author and Jameel Clinic postdoc Luis Soenksen PhD ‘20.

Elon Musk is hyping the imminent release of his ChatGPT competitor Grok, yet another example of how his entire personality is just itself a biological LLM made by ingesting all of Reddit and 4chan. Grok already seems patterned in many ways off of the worst of Elon’s indulgences, with the sense of humor of a desperately unfunny and regressive internet troll, and biases informed by a man whose horrible, dangerous biases are fully invisible to himself.

There are all kinds of reasons to be wary of Grok, including the standard reasons to be wary of any current LLM-based AI technology, like hallucinations and inaccuracies. Layer on Elon Musk’s recent track record for disastrous social sensitivity and generally harmful approach to world-shaping issues, and we’re already looking at even more reason for concern. But the real risk probably isn’t yet so easy to grok, just because we have little understanding yet of the extent of the impact that widespread use of LLMs across our daily and online lives will have.

One key area where they’re already having and are bound to have much more of an impact is user-generated content. We’ve seen companies already deploying first-party integrations that start to embrace some of these uses, like Artifact with its AI-generated thumbnails for shared posts, and Meta adding chatbots to basically everything. Musk is debuting Grok on X as a feature reserved for Premium+ subscribers initially, with a rollout supposedly beginning this week.

According to the team, the main advantage of Brainnetome is that synthesizes various repositories of information taken from various imaging techniques and experimental methodologies, allowing it to better represent brain connectivity at different scales and modalities across the brain’s 246 subregions, including structural and functional patterns between them.

Brain atlases “can help us understand how brain regions are interconnected and how they interact at various levels of granularity,” explained the team. “Such insights are crucial for modeling brain dynamics and simulating complex neural processes.”

The planet Mercury seems like a place inhospitable to life, with surface temperatures reaching a blistering 800 degrees Fahrenheit due to its extremely close proximity to the Sun.

But new research suggests that there are regions on the Solar System’s smallest planet that may have the right conditions for biological life to survive.

Scientists at the Planetary Science Institute (PSI) in Arizona say they’ve found evidence of salt glaciers on the planet’s surface, regions that are similar to extremely harsh and salt-rich environments on Earth where life still finds a way to exist.

Open-source supercomputer algorithm predicts patterning and dynamics of living materials and enables studying their behavior in space and time.

Biological materials are made of individual components, including tiny motors that convert fuel into motion. This creates patterns of movement, and the material shapes itself with coherent flows by constant consumption of energy. Such continuously driven materials are called “active matter.” The mechanics of cells and tissues can be described by active matter theory, a scientific framework to understand shape, flows, and form of living materials. The active matter theory consists of many challenging mathematical equations.

Scientists from the Max Planck Institute of Molecular Cell.

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• Tim Ferriss Podcast [Chris Dixon and Naval Ravikant — The Wonders of Web3, How to Pick the Right Hill to Climb, Finding the Right Amount of Crypto Regulation, Friends with Benefits, and the Untapped Potential of NFTs (542)]: https://tim.blog/2021/10/28/chris-dixon-naval-ravikant/
https://2050.earth/
https://research.aimultiple.com/artificial-general-intellige…ty-timing/
https://mars.nasa.gov/mars2020/spacecraft/rover/communications/
https://www.forbes.com/sites/tomtaulli/2020/08/14/quantum-co…3acd9f3b4c.
https://cointelegraph.com/news/tales-from-2050-a-look-into-a-world-built-on-nfts.
https://medium.com/theblockchainu/a-day-in-life-of-a-cryptoc…a07649f14d.
https://botland.store/blog/story-of-the-internet-from-web-1&…b-4-0/
https://www.analyticsinsight.net/light-based-computer-chips-…h-photons/
https://www.wired.com/story/chip-ai-works-using-light-not-electrons/
https://www.science.org/content/article/light-based-memory-c…store-data.

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For the first time, researchers have succeeded in selectively exciting a molecule using a combination of two extreme-ultraviolet light sources and causing the molecule to dissociate while tracking it over time. This is another step towards specific quantum mechanical control of chemical reactions, which could enable new, previously unknown reaction channels.

The interaction of light with matter, especially with molecules, plays an important role in many areas of nature, for example in such as photosynthesis. Technologies such as use this process as well.

On the Earth’s surface, mainly light in the visible, ultraviolet or infrared regime plays a role here. Extreme-ultraviolet (XUV) light—radiation with significantly more energy than —is absorbed by the atmosphere and therefore does not reach the Earth’s surface. However, this XUV radiation can be produced and used in the laboratory to enable a selective excitation of electrons in molecules.

An open-source advanced supercomputer algorithm predicts the patterning and dynamics of living materials, allowing for the exploration of their behaviors across space and time.

Biological materials consist of individual components, including tiny motors that transform fuel into motion. This process creates patterns of movement, leading the material to shape itself through coherent flows driven by constant energy consumption. These perpetually driven materials are called “active matter.”

The mechanics of cells and tissues can be described by active matter theory, a scientific framework to understand the shape, flows, and form of living materials. The active matter theory consists of many challenging mathematical equations.