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A grim future awaits the United States if it loses the competition with China on developing key technologies like artificial intelligence in the near future, the authors of a special government-backed study told reporters on Monday.

If China wins the technological competition, it can use its advancements in artificial intelligence and biological technology to enhance its own country’s economy, military and society to the determent of others, said Bob Work, former deputy defense secretary and co-chair of the Special Competitive Studies Project, which examined international artificial intelligence and technological competition. Work is the chair of the U.S. Naval Institute Board of Directors.

Losing, in Work’s opinion, means that U.S. security will be threatened as China is able to establish global surveillance, companies will lose trillions of dollars and America will be reliant on China or other countries under Chinese influence for core technologies.

Continue reading “Losing to China in AI, Emerging Tech Will Cost U.S. Trillions, Threaten Security, Says Panel” | >

Microsoft’s augmented reality headset the HoloLens has been in the works for years now, but it’s been a while since we’ve heard any news. We were seeing demos of it way back in 2015 (opens in new tab), but Microsoft has been pretty quiet on the tech in recent years when it comes to a consumer release.

What we’ve heard tons about is Microsoft’s deal to supply the United States Army with HoloLens tech. We first got wind of the deal back in 2018 (opens in new tab) with talks of a $480 million contract to help “increase lethality” of combat missions. It wasn’t until 2021 that Microsoft officially signed a much pricier $22 billion dollar contract (opens in new tab) with the army for military grade HoloLens supply.

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A team of scientists is using the tools offered by the HBP’s digital research infrastructure EBRAINS to address one of the oldest enigmas in neuroscience: the dichotomy of brain structure and function.

Every human brain is different. But even with structural differences, individual brains function in a similar way. In other words, there are functional brains based on completely different configurations. At the same time, a structural change may cause loss of function in one brain, but have no consequences in another individual. Or a drug cocktail may be efficient for one patient, and have no effects for another.

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Cancer is one of the major global public health problems and is caused by abnormal cell proliferation. A plant immune protein has recently been found to enable widespread anti-tumor responses by alleviating micro-RNA

Ribonucleic acid (RNA) is a polymeric molecule similar to DNA that is essential in various biological roles in coding, decoding, regulation and expression of genes. Both are nucleic acids, but unlike DNA, RNA is single-stranded. An RNA strand has a backbone made of alternating sugar (ribose) and phosphate groups. Attached to each sugar is one of four bases—adenine (A), uracil (U), cytosine ©, or guanine (G). Different types of RNA exist in the cell: messenger RNA (mRNA), ribosomal RNA (rRNA), and transfer RNA (tRNA).

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In recent years, engineers and computer scientists have created a wide range of technological tools that can enhance fitness training experiences, including smart watches, fitness trackers, sweat-resistant earphones or headphones, smart home gym equipment and smartphone applications. New state-of-the-art computational models, particularly deep learning algorithms, have the potential to improve these tools further, so that they can better meet the needs of individual users.

Researchers at University of Brescia in Italy have recently developed a computer vision system for a smart mirror that could improve the effectiveness of fitness training both in home and gym environments. This system, introduced in a paper published by the International Society of Biomechanics in Sports, is based on a deep learning algorithm trained to recognize human gestures in video recordings.

“Our commercial partner ABHorizon invented the concept of a product that can guide and teach you during your personal fitness training,” Bernardo Lanza, one of the researchers who carried out the study, told TechXplore. “This device can show you the best way to train based on your specific needs. To develop this device further, they asked us to investigate the viability of an integrated vision system for exercise evaluation.”

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The study population comprised 6,245,282 older adults (age ≄65 years) who had medical encounters with healthcare organizations between 2/2/2020–5/30/2021 and had no prior diagnosis of Alzheimer’s disease. The population was divided into two cohorts: 1) COVID-19 cohort (n = 410,748)— contracted COVID-19 between 2/2/2020–5/30/2021; 2) non-COVID-19 cohort (n = 5,834,534)— had no documented COVID-19 but had medical encounters with healthcare organizations between 2/2/2020–5/30/2021. The status of Alzheimer’s disease and COVID-19 were based on the International Classification of Diseases (ICD-10) diagnosis codes and laboratory tests (details in the Supplementary Material).

We examined risks for new diagnosis of Alzheimer’s disease in COVID-19 and non-COVID-19 cohorts in all older adults, three age groups (65–74, 75–84, ≄85), and three racial/ethnic groups (Black, White, and Hispanic). Cohorts were propensity-score matched (1:1 using a nearest neighbor greedy matching) for demographics, adverse socioeconomical determinants of health including problems with education, occupational exposure, physical, social and psychosocial environment, and known risk factors for Alzheimer’s disease [13] (details in the Supplementary Material). Kaplan-Meier analysis was used to estimate the probability of new diagnosis of Alzheimer’s disease within 360 days after the COVID-19 diagnosis. Cox’s proportional hazards model was used to compare matched cohorts using hazard ratios and 95% confidence intervals. All statistical tests were conducted within the TriNetX Advanced Analytics Platform at significance set at p < 0.05 (2-sided).

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How can mobile robots perceive and understand the environment correctly, even if parts of the environment are occluded by other objects? This is a key question that must be solved for self-driving vehicles to safely navigate in large crowded cities. While humans can imagine complete physical structures of objects even when they are partially occluded, existing artificial intelligence (AI) algorithms that enable robots and self-driving vehicles to perceive their environment do not have this capability.

Robots with AI can already find their way around and navigate on their own once they have learned what their environment looks like. However, perceiving the entire structure of objects when they are partially hidden, such as people in crowds or vehicles in traffic jams, has been a significant challenge. A major step towards solving this problem has now been taken by Freiburg robotics researchers Prof. Dr. Abhinav Valada and Ph.D. student Rohit Mohan from the Robot Learning Lab at the University of Freiburg, which they have presented in two joint publications.

The two Freiburg scientists have developed the amodal panoptic segmentation task and demonstrated its feasibility using novel AI approaches. Until now, self-driving vehicles have used panoptic segmentation to understand their surroundings.

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Plentiful, safe, energy that burns up nuclear waste as fuel could be provided as soon as we build these reactor, There is no excuse for us freezing this winter! Watch and learn. Share widely to get the word out!

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Awesome deals for long term food supplies for those long missions to deep space (or prepping in case your spaceship crashes: See the Special Deals at My Patriot Supply: www.PrepWithGreg.com.

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