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Chinese scientists find genetics shapes brain’s balance linked to mental ability

There is extensive evidence that brain criticality – the balance between neural excitation and inhibition – enhances its information processing capabilities.

But despite the significance of brain criticality and its potential influence on neurological and psychiatric disorders, the genetic basis of this state had been “largely unexplored”, according to researchers from the Chinese Academy of Sciences’ biophysics and automation institutes. “We demonstrate that genetic factors significantly influence brain criticality across various scales, from specific brain regions to large-scale networks,” the team said in their paper published in the peer-reviewed journal Proceedings of the National Academy of Sciences last month.

They also established a link between criticality and cognitive functions, suggesting a shared genetic foundation.

“These findings position brain criticality as a biological phenotype, opening broad avenues for exploring its implications in brain function and potential dysfunctions,” the team wrote.

Brain criticality is characterised by neuronal avalanches, or cascading bursts of neuron activity in brain networks.

“At the critical state, the brain exhibits scale-free dynamics, with avalanches observed across various scales ranging from local networks of individual neurons to the global network of interacting brain areas,” the paper said.


Goodbye to humans in warehouses — Amazon rolls out new autonomous robots in the UK and accelerates full automation

Amazon is going to put an end to human labour. Yes, it has reached a turning point that will change how we view salaried work forever: robots will outnumber human employees in warehouses around the world. The company that until a few years ago was seen as a major job creator has now said no more human labour, it wants more robots. And yes, it will be the first time that robots outnumber human employees, even though Amazon already has one million machines, from robotic arms to wheeled transporters since 2020.

Layoffs continue and job automation doesn’t seem to be slowing down, because of course, not only does it improve company productivity, but machines don’t get sick, don’t ask for personal days, and don’t demand their labour rights… The data may be very optimistic for Amazon, but workers are seeing their jobs being taken away… and there’s no turning back. Here’s what’s happening inside Amazon’s warehouses.

New system helps robotic arm navigate using sound instead of vision

A new sensing system called SonicBoom could help agricultural robots navigate cluttered environments where visual sensors struggle.

Developed by researchers at Carnegie Mellon University, SonicBoom uses tiny contact microphones to sense sound and localize objects that a robotic arm touches.

Interestingly, these robots could help farmers harvest crops even in increasingly challenging conditions, such as rising temperatures.

Massive study detects AI fingerprints in millions of scientific papers

Chances are that you have unknowingly encountered compelling online content that was created, either wholly or in part, by some version of a Large Language Model (LLM). As these AI resources, like ChatGPT and Google Gemini, become more proficient at generating near-human-quality writing, it has become more difficult to distinguish between purely human writing from content that was either modified or entirely generated by LLMs.

This spike in questionable authorship has raised concerns in the that AI-generated content has been quietly creeping into peer-reviewed publications.

To shed light on just how widespread LLM content is in , a team of U.S. and German researchers analyzed more than 15 million biomedical abstracts on PubMed to determine if LLMs have had a detectable impact on specific word choices in journal articles.

Data Science and Machine Learning: Mathematical and

D.P. Kroese, Z.I. Botev, T. Taimre, R. Vaisman. Data Science and Machine Learning: Mathematical and Statistical Methods, Chapman and Hall/CRC, Boca Raton, 2019.

The purpose of this book is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.

Ford CEO Admits Defeat With SHOCKING Comments

Questions to inspire discussion.

🧠 Q: How is Ford trying to shape consumer attitudes towards driving? A: Ford is attempting to convince consumers that driving is an essential life skill rather than a chore, possibly to maintain demand for traditional vehicles.

👨💼 Q: What message is Ford sending about the future of driving? A: Ford’s CEO suggests that everyone should continue to know how to drive, implying that fully autonomous vehicles are not the immediate future.

Regulatory Approach.

📊 Q: How might Ford be influencing regulators regarding autonomous vehicles? A: Ford may be trying to convince regulators that autonomous vehicles are not significantly safer than human drivers to potentially delay or prevent approval.

Technology Development.

How can AI be more energy efficient? Researchers look to human brain for inspiration

It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive.

That’s why University at Buffalo researchers are taking inspiration from the human brain to develop computing architecture that can support the growing energy demands of artificial intelligence.

“There’s nothing in the world that’s as efficient as our brain—it’s evolved to maximize the storage and processing of information and minimize energy usage,” says Sambandamurthy Ganapathy, Ph.D., professor in the UB Department of Physics and associate dean for research in the UB College of Arts and Sciences.

The 40 Best AI Tools in 2025 (Tried & Tested)

In this article I list 45 AI tools across 20 different categories. After exploring all the available options in each category, I’ve carefully selected the best tools based on my personal experience. This ensures that the recommendations come from real, practical use, so you can trust that they’re grounded in what actually works.

For each tool, I focus on its best use cases, explaining when and how it can be most useful. I also share what I love about each one, as well as any downsides I’ve encountered during my experience. Additionally, I provide information on the free version and premium pricing plans for each tool.


An in-depth guide to the 40 best AI tools including the best AI assistants, video generators, automation tools, app builders, and more.