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Category: robotics/AI – Page 36

AI repurposes routine chest X-rays to catch silent bone loss before fracture

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.

AI Cyber Threats Drive Zero Trust Security Shift

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.

Popular joint supplement glucosamine linked to faster Alzheimer’s progression

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.

Ray Kurzweil Predicts AI Will Change Humanity Completely by 2030

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.

Continue reading “Ray Kurzweil Predicts AI Will Change Humanity Completely by 2030” | >

Reservoir computing (or training recurrent neural networks)

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.

Canada’s National Artificial Intelligence Strategy: AI for All

Message from the minister The Government’s vision: AI for All Key pillars of the strategy Priority sectors Pillar 1: Protecting Canadians and safeguarding democracy Pillar 2: Ensuring AI empowers Canadians Pillar 3: Powering AI adoption for shared prosperity Pillar 4: Building the Canadian sovereign AI foundation Pillar 5: Scaling Canadian champions Pillar 6: Building trusted partnerships and global alliances Conclusion

An innovative Canada is a stronger Canada. And AI is the major driver of innovation in Canada and around the world. But to understand the potential of Canadian AI, you have to see how it is already working to improve the lives of people. How a Canadian pediatric cardiologist in Halifax named Dr. Robert Chen is using the AI application he built to diagnose heart murmurs in newborns. His technology could cut down wait times by many months for anxious parents to see a specialist, saving our health care system tens of millions of dollars.

You have to see how a Canadian AI company called Croptimistic is helping farmers precisely map their soil. This technology allows them to use less fertilizer, while increasing crop yield, making our food system more resilient and more affordable.

The AI tools shaping patient care may be operating outside regulatory oversight. MIT researchers say it’s time to change that

Every day, across thousands of American hospitals, artificial intelligence quietly shapes decisions that determine patient outcomes. An algorithm flags a patient as high risk for sepsis; a risk score informs whether a woman receives additional cancer screening; a deterioration model triggers an alert that sends a care team to a bedside. These tools are embedded in the workflows of nearly two-thirds of US hospitals, integrated into the electronic health record systems clinicians rely on daily. But many have never been reviewed by the FDA.

A new viewpoint in The Lancet Digital Health, co-authored by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic, traces how this problem took root, why it carries serious consequences, and what genuine transparency would require to fix it.

The argument, the scientists say, is not that AI has no place in clinical decision-making. It is that a $4 billion market of clinical decision support tools operates largely beyond public accountability, leaving patients and providers often unable to know whether the tools influencing their care have been validated, by whom, or for which populations they work as intended.

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