How Microsoft’s new quantum chip was made 1,000x more reliable with the help of Microsoft Discovery’s agentic AI.
Aging involves a decline in physiological functions and increased disease susceptibility, with the immune system playing a pivotal role. Recent research reveals that nonimmune structural cells, such as fibroblasts, epithelial cells, and neurons, develop immune-like properties crucial for stress response and tissue integrity. However, with aging, these organized, nonimmune cells in multicellular organisms gradually lose their identity and organization. They may exhibit unicellular properties, acquire macrophage-like characteristics, or enter a state of senescence, contributing to chronic inflammation.
Deep brain stimulation (DBS) has been used for more than three decades to treat motor symptoms of Parkinson’s disease. Today, more than 200,000 patients worldwide have been implanted with these systems, which continuously deliver electrical stimulation to specific deep-brain regions to reduce rigidity and tremor. Yet despite its clinical success, conventional deep brain stimulation remains limited in its ability to address one of the disease’s most disabling symptoms: walking impairments.
Researchers from EPFL and Lausanne University Hospital (CHUV) have developed a new approach, published in Nature Medicine, that adapts DBS in real time to the patient’s mobility in everyday situations. Thanks to artificial intelligence, the system continuously interprets the patient’s activity and adjusts stimulation in real time, improving walking, climbing stairs and even the simple act of standing up.
13 years ago, I sat down with Doug Wolens to talk about a word almost no one was using: the singularity.
Doug was a lawyer who walked away from the courtroom to make films. His documentary, The Singularity, did something rare. It refused to cheerlead. It asked questions instead.
One thing he said has stayed with me ever since. Science is a means, not an end. It does not deliver a scientific destination. It delivers a humanistic one.
That distinction matters more now than it did in 2013.
Back then, machine intelligence surpassing human intelligence was a thought experiment. Today, it is a product roadmap. We used to argue about whether it would happen. Now we argue about what to do while it does.
But the sharpest question in Doug’s film was never about the machines. It was about us.
Osteoporosis is a silent disease where bone loss develops gradually before fractures occur. Current clinical screening recommendations mainly focus on older women and selected high-risk groups, leaving some men, younger adults, and individuals with normal body weight completely outside routine screening pathways.
To close this care gap, researchers from St. Paul’s Hospital and National Taiwan University have demonstrated how AI can leverage routine chest X-rays to detect asymptomatic bone loss, closing critical gaps in screening healthy Asian populations. Their paper is published in the journal npj Digital Medicine.
Strikingly, the study found that more than half of the confirmed abnormal bone-density cases occurred in people with a normal body mass index (BMI). This reveals a severe diagnostic blind spot in conventional, guideline-based screening. By relying strictly on traditional criteria, health care systems routinely overlook healthy-weight individuals, younger adults, and men who are secretly losing bone density but remain completely off the clinical radar.
By Chuck Brooks, president of Brooks Consulting International and one of Executive Mosaic’s GovCon Experts
We have now transitioned from the age of digital dangers to an era of complete systemic vulnerability. The data clearly demonstrates that cyber threats are no longer sporadic; they represent a persistent, sophisticated phenomenon. Hackers are now utilizing autonomous adversaries rather than merely sophisticated tools.
Recent industry data obtained in early 2026 indicates a vertical trajectory, revealing that global AI-driven cyber incidents have surged by an astonishing 72 percent year-over-year. A 72 percent surge is not just growth; it’s systemic acceleration.
Because glucosamine is widely available and frequently used by older adults to support joint health, the researchers wanted to determine whether it could influence Alzheimer’s disease and related dementias (ADRD).
Working with collaborators Yi Guo, Ph.D., and Jiang Bian, Ph.D., the team used artificial intelligence to analyze deidentified UF Health records collected between 2012 and 2024. They focused on patients diagnosed with either ADRD or mild cognitive impairment (MCI).
Among those patients, researchers found that glucosamine use was relatively common. A total of 1,896 patients with ADRD and 2,750 patients with MCI reported taking the supplement, representing about 8% of each group.
Two of my favorite people. Definitely worth a view if you are interested in either.
Few thinkers have shaped our understanding of the future as profoundly as Ray Kurzweil. An American inventor, computer scientist, futurist, entrepreneur, and bestselling author, Kurzweil is widely regarded as one of the most influential technological forecasters of our time. For decades, he has accurately predicted many of the innovations that now define modern life, from mobile computing and artificial intelligence to digital assistants and large language models often years before they entered the mainstream.
In this special conversation, Tony Robbins sits down with Ray Kurzweil in San Francisco to explore one of the most important questions facing humanity: What happens next?
Together, they examine the accelerating pace of artificial intelligence, the path toward Artificial General Intelligence (AGI), the rise of autonomous agents, the future of work and education, breakthroughs in healthcare and longevity, and how these technologies may transform society over the coming decade.
Kurzweil explains why his long-standing prediction of AGI by 2029 now appears increasingly conservative, why the next few years may bring more change than any period in human history, and how humanity may ultimately merge with the very technologies it creates.
Gives some intuition concerning how initially random recurrent neural networks can be trained to produce complex behaviors mimicking input/output relationships of recurrent neural networks in the brain. The important thing here is that these networks can produce complex temporal dynamics (even in the absence of input) unlike the static feedforward neural networks we discussed before.