"Moshav leitzim" --- where a company of people literally doing nothing else than engaging in frivolty and lightheaded, empty speech ---- The Technology Circus - Part Two!

 

What is a Moshav Leitzim? (Avodah Zarah 18b): “One who goes to a  circus or to a house of laughter

A second asifa addressing the growing impact of artificial intelligence was held Thursday night in Lakewood, drawing senior dreaming rabbinic artificial unintelligent leadership and continuing a discussion that began earlier this week.

The gathering focused on concerns surrounding AI-driven calling, texting, and content generation, and followed an initial asifah that drew dozens of leading rabbanim and roshei yeshiva, where the gedolim called for a yom taanis u’tefillah over the threats posed by AI. A date has not been set for when that will take place.

Thursday night’s meeting featured remarks from Rav Elyah Ber Wachtfogel, Rav Malkiel Kotler and Rav Yisroel Newman, who addressed both the technological and hashkafic implications of artificial intelligence.

During his remarks, Rav Yisroel Newman warned that artificial intelligence poses dangers he described as more severe than those associated with the general internet. Rav Malkiel addressed the use of AI in Torah learning, stating that Torah learned through AI-generated means would not warrant a bracha, characterizing such a bracha as a berachah levatalah.

 

* 

 

Leitzim Versus Baalei (Hashem Yisborech's) Daas..... 

 

AI can now use sleep to predict your medical future

In A Nutshell

• Stanford researchers trained an AI model on sleep recordings from 65,000+ people and found it could predict risk for 130 diseases years before diagnosis
• The system achieved 84% accuracy for predicting mortality risk and similar high accuracy for dementia, heart attack, heart failure, stroke, and other conditions
• Sleep recordings capture hidden patterns across brain activity, heart rhythms, breathing, and muscle movements that signal future health problems
• The findings suggest polysomnography may eventually become a powerful early detection tool, though current sleep studies require specialized clinical equipment

Scientists have developed an artificial intelligence system that can predict a person’s risk of developing conditions ranging from dementia to heart failure by analyzing a single night of sleep data. The findings suggest that sleep patterns contain far more information about future health than previously recognized.

Researchers at Stanford University and collaborators trained an AI model called SleepFM on polysomnography recordings from more than 65,000 people, representing over 585,000 hours of sleep data. Polysomnography is the gold standard sleep study that records brain activity, heart rhythms, breathing patterns, and muscle movements throughout the night.

After analyzing these overnight recordings, the model identified elevated future risk for 130 medical conditions, often years before clinical diagnosis. For all-cause mortality, the system achieved a concordance index of 0.84, meaning it correctly ranked patient risk 84% of the time. Similar accuracy emerged for dementia (0.85), heart attack (0.81), heart failure (0.80), chronic kidney disease (0.79), stroke (0.78), and atrial fibrillation (0.78).

“Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains poorly understood,” the researchers wrote in their paper published in Nature Medicine.

AI Analyzes Multiple Sleep Signals Simultaneously

The study examined sleep recordings from four major research cohorts spanning ages 1 to 100 years. Traditional sleep studies focus on specific disorders like sleep apnea or measure isolated metrics. SleepFM takes a different approach by processing all physiological signals simultaneously—brain wave patterns, eye movements, heart activity, muscle tone, and breathing measurements.

The system breaks down sleep recordings into five-second segments, analyzing patterns across different signal types to identify which combinations predict future disease. For disease prediction, researchers paired Stanford sleep recordings with electronic health records containing diagnostic codes and timestamps. They only counted cases where diagnosis occurred at least seven days after the sleep study to avoid detecting existing conditions.

 

Strong Predictions Across Major Disease Categories

SleepFM demonstrated particularly strong predictive power for neurological and mental health conditions, including mild cognitive impairment and Parkinson’s disease. Among cardiovascular conditions, the system effectively predicted hypertensive heart disease and intracranial hemorrhage. Cancer-related risk prediction showed promising associations for prostate cancer, breast cancer, and skin melanomas.

The model maintained accuracy when tested on sleep recordings from 2020 onwards, a period entirely excluded from training. This validation included strong performance for death (0.83), heart failure (0.80), and dementia (0.83).

 These findings reveal that a single night’s sleep contains a wealth of information about future health across numerous conditions. Sleep patterns may serve as an early warning signal for diseases that won’t manifest for years, offering potential opportunities for earlier intervention and prevention.

MORE: https://studyfinds.org/scientists-decode-sleep-patterns-to-forecast-future-health-risks/?