Scientists have discovered the elusive properties hidden within promethium, a rare earth element that has remained largely unexplored.
Groundbreaking research has revealed a new method of potentially eliminating hard-to-treat post-traumatic stress disorder (PTSD) diagnoses in patients by employing a novel kind of therapy: stimulation of the vagus nerve.
The new treatment offers new hope for those long afflicted by PTSD diagnoses that have traditionally proven to be resistant to conventional treatment methods.
Scientists from the University of Texas at Dallas (UTD) and Baylor University Medical Center conducted the research, discovering that participants were symptom-free for up to six months after completing the experimental therapy.
Once AI becomes pervasive, it no longer gives companies an edge over rivals — but cultivating creativity can.
What happens when AI starts improving itself without human input? Self-improving AI agents are evolving faster than anyone predicted—rewriting their own code, learning from mistakes, and inching closer to surpassing giants like OpenAI. This isn’t science fiction; it’s the AI singularity’s opening act, and the stakes couldn’t be higher.
How do self-improving agents work? Unlike static models such as GPT-4, these systems use recursive self-improvement—analyzing their flaws, generating smarter algorithms, and iterating endlessly. Projects like AutoGPT and BabyAGI already demonstrate eerie autonomy, from debugging code to launching micro-businesses. We’ll dissect their architecture and compare them to OpenAI’s human-dependent models. Spoiler: The gap is narrowing fast.
Why is OpenAI sweating? While OpenAI focuses on safety and scalability, self-improving agents prioritize raw, exponential growth. Imagine an AI that optimizes itself 24/7, mastering quantum computing over a weekend or cracking protein folding in hours. But there’s a dark side: no “off switch,” biased self-modifications, and the risk of uncontrolled superintelligence.
Who will dominate the AI race? We’ll explore leaked research, ethical debates, and the critical question: Can OpenAI’s cautious approach outpace agents that learn to outthink their creators? Like, subscribe, and hit the bell—the future of AI is rewriting itself.
Can self-improving AI surpass OpenAI? What are autonomous AI agents? How dangerous is recursive AI? Will AI become uncontrollable? Can we stop self-improving AI? This video exposes the truth. Watch now—before the machines outpace us.
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Summary: New research reveals a striking gap between people’s theoretical desire to know their Alzheimer’s disease risk and their real-life decisions when results are actually offered. In a study of cognitively normal volunteers, only 60% chose to learn their estimated risk when given the chance, despite 81% expressing prior interest.
A selfie can be used as a tool to help doctors determine a patient’s “biological age” and judge how well they may respond to cancer treatment, a new study suggests.
Because humans age at “different rates” their physical appearance may help give insights into their so-called “biological age” – how old a person is physiologically, academics said.
The new FaceAge AI tool can estimate a person’s biological age, as opposed to their actual age, by scanning an image of their face, a new study found.
So size does matter?
Mammal’s lifespans linked to brain size and immune system function, says new study.
The researchers looked at the maximum lifespan potential of 46 species of mammals and mapped the genes shared across these species. The maximum lifespan potential (MLSP) is the longest ever recorded lifespan of a species, rather than the average lifespan, which is affected by factors such as predation and availability of food and other resources.
The researchers, publishing in the journal Scientific Reports, found that longer-lived species had a greater number of genes belonging to the gene families connected to the immune system, suggesting this as a major mechanism driving the evolution of longer lifespans across mammals.
For example, dolphins and whales, with relatively large brains have maximum lifespans of 39 and up to 100 years respectively, those with smaller brains like mice, may only live one or two years.
However, there were some species, such as mole rats, that bucked this trend, living up to 20 years despite their smaller brains. Bats also lived longer than would be expected given their small brains, but when their genomes were analysed, both these species had more genes associated with the immune system.
The results suggest that the immune system is central to sustaining longer life, probably by removing aging and damaged cells, controlling infections and preventing tumour formation.
The rules about magnetic order may need to be rewritten. Researchers have discovered that chromium selenide (Cr₂Se₃) — traditionally non-magnetic in bulk form — transforms into a magnetic material when reduced to atomically thin layers. This finding contradicts previous theoretical predictions, and opens new possibilities for spintronics applications. This could lead to faster, smaller, and more efficient electronic components for smartphones, data storage, and other essential technologies.
An international research team from Tohoku University, Université de Lorraine (Synchrotron SOLEIL), the National Synchrotron Radiation Research Center (NSRRC), High Energy Accelerator Research Organization, and National Institutes for Quantum Science and Technology successfully grew two-dimensional Cr₂Se₃ thin films on graphene using molecular beam epitaxy. By systematically reducing the thickness from three layers to one layer and analyzing them with high-brightness synchrotron X-rays, the team made a surprising discovery. This finding challenges conventional theoretical predictions that two-dimensional materials cannot maintain magnetic order.
“When we first observed the ferromagnetic behavior in these ultra-thin films, we were genuinely shocked,” explains Professor Takafumi Sato (WPI-AIMR, Tohoku University), the lead researcher. “Conventional theory told us this shouldn’t happen. What’s even more fascinating is that the thinner we made the films, the stronger the magnetic properties became—completely contrary to what we expected.”
It’s easy to take joint mobility for granted. Without thinking, it’s simple enough to turn the pages of a book or bend to stretch out a sore muscle. Designers don’t have the same luxury. When building a joint, be it for a robot or wrist brace, designers seek customizability across all degrees of freedom but are often restricted by their versatility to adapt to different use contexts.
Researchers at Carnegie Mellon University’s College of Engineering have developed an algorithm to design metastructures that are reconfigurable across six degrees of freedom and allow for stiffness tunability. The algorithm can interpret the kinematic motions that are needed for multiple configurations of a device and assist designers in creating such reconfigurability. This advancement gives designers more precise control over the functionality of joints for various applications.
The team demonstrated the structure’s versatile capabilities via multiple wearable devices tailored for unique movement functions, body areas, and uses.
Brown University researchers have developed an artificial intelligence model that can generate movement in robots and animated figures in much the same way that AI models like ChatGPT generate text.
A paper describing this work is published on the arXiv preprint server.
The model, called MotionGlot, enables users to simply type an action— walk forward a few steps and take a right— and the model can generate accurate representations of that motion to command a robot or animated avatar.