The past decade has seen an important and, for many patients, a life-changing rise in the number of innovative new drugs reaching the market to treat diseases such as multiple sclerosis, malaria, and subtypes of certain cancers (such as melanoma or leukemia). In the United States, the Food and Drug Administration approved an average of 41 new molecular entities (including biologic license applications) each year from 2011 to 2020--almost double the number in the previous decade. Despite the immense costs of such achievements, 2 2. Asher Mullard, "New drugs cost US $2.6 billion to develop," Nature Reviews Drug Discovery, December 1, 2014. A major barrier is the daunting challenge of understanding the multifactorial nature of many diseases coupled with the vast set of variables in therapy design. Very few diseases, such as cystic fibrosis, are linked to variants in single genes. Drug development therefore tends to rely on a reductionist, hypothesis-driven approach that narrows the focus to individual cell types or pathways. Focused assays often based on partial information or informed by animal models that never perfectly reflect human disease then attempt to identify single molecules that will benefit patients.

Researchers from the National Aeronautics and Space Administration (NASA) have teamed up with the US Department of Energy's Argonne National Laboratory (ANL) to develop artificial intelligence (AI) to enhance the speed of simulations to study the behavior of air surrounding supersonic and hypersonic aircraft engines. Fighter jets such as F-15s regularly exceed Mach 2 – two times the speed of sound – during the flight which is known as supersonic level. On a hypersonic flight which is Mach 5 and beyond, an aircraft flies faster than 3,000 miles per hour. Hypersonic speeds have been made possible since the 1950s by the propulsions systems used for rockets however, engineers and scientists are working on advanced jet engine designs to make the hypersonic flight much less expensive than a rocket launch and more common such as for commercial flight, space exploration, and national defense purposes. The newly published paper by a team of researchers from NASA and ANL details the machine learning techniques to reduce the memory and cost required to conduct computational fluid dynamics (CFD) simulations related to fuel combustion at supersonic and hypersonic speeds.

There's nobody better at persecuting a war than the United States -- we've got the the best-equipped and biggest-budgeted fighting force on the face of the Earth. But does carrying the biggest stick still constitute a strategic advantage if the mere act of possessing it seems to make us more inclined to use it? In his latest book, Future Peace (sequel to 2017's Future War) Dr. Robert H. Latiff, Maj Gen USAF (Ret), explores how the American military's increasing reliance on weaponized drones, AI and Machine Learning systems, automation and similar cutting-edge technologies, when paired with an increasingly rancorous and often outright hostile global political environment, could create the perfect conditions for getting a lot of people killed. In the excerpt below, Dr. Latiff looks at the impact that America's lionization of its armed forces in the post-Vietnam era and new access to unproven tech have on our ability to mitigate conflict and prevent armed violence. Published by University of Notre Dame Press.

AI for health care is all the rage. Who wouldn't be excited about applications that could help detect cancer, diagnose COVID-19 or even dementia well before they are otherwise noticeable, or predict diabetes before its onset? Machine and deep learning have already been shown to make these outcomes possible. Possible, that is, in the research lab. In health care, there is often a long lag between research findings and implementation at the bedside.

Two identical black and white pictures of murky shapes sit side-by-side on a computer screen. On the left side, Ismail Baris Turkbey, MD, a radiologist with 15 years of experience, has outlined an area where the fuzzy shapes represent what he believes is a creeping, growing prostate cancer. On the other side of the screen, an artificial intelligence (AI) computer program has done the same--and the results are nearly identical. The black and white image is an MRI scan from someone with prostate cancer, and the AI program has analyzed thousands of them. "The [AI] model finds the prostate and outlines cancer-suspicious areas without any human supervision," Turkbey explains.

Kevin Larson crouched behind a boulder and watched the forest through his breath, waiting for the police he knew would come. It was Jan. 19, 2020. He was clinging to an assault rifle with 30 rounds and a conviction that, after all he had been through, there was no way he was going to prison. Larson was a drone pilot -- one of the best. He flew the heavily armed MQ-9 Reaper, and in 650 combat missions between 2013 and 2018, he had launched at least 188 airstrikes, earned 20 medals for achievement and killed a top man on the U.S.' most-wanted terrorist list. The 32-year-old pilot kept a handwritten thank-you note on his refrigerator from the director of the CIA.

Singapore and Israel have signed a memorandum of understanding (MoU) on Artificial Intelligence (AI) cooperation, indicating that both nations want to speed up cross-border collaboration in the field. The MOU between Singapore's Smart Nation and Digital Government Office and Israel's Ministry of Innovation, Science and Technology on AI cooperation would assist AI development and implementation for "common benefit," according to the MOU. This year marks the 25th anniversary of the Singapore-Israel Industrial R&D Foundation. The foundation has supported around 190 projects between Singapore and Israel since its creation in 1997, delivering approximately US$120 million to initiatives in sectors such as information and communications technology, electronics, and biomedical and life sciences. Companies from both Singapore and Israel have been exploring prospects in both nations.

Artificial intelligence (AI) has already had a profound impact on business and society. Applied AI and machine learning (ML) are creating safer workplaces, more accurate health diagnoses and better access to information for global citizens. The Fourth Industrial Revolution will represent a new era of partnership between humans and AI, with potentially positive global impact. AI advancements can help society solve problems of income inequality and food insecurity to create a more "inclusive, human-centred future" according to the World Economic Forum (WEF). There is nearly limitless potential to AI innovation, which is both positive and frightening.

The Navy is progressively phasing artificial intelligence (AI) into its ship systems, weapons, networks, and command and control infrastructure as computer automation becomes more reliable and advanced algorithms make once-impossible discernments and analyses. Previously segmented data streams on ships, drones, aircraft, and even submarines are now increasingly able to share organized data in real-time, in large measure due to breakthrough advances in AI and machine learning. AI can, for instance, enable command and control systems to identify moments of operational relevance from among hours or days or surveillance data in milliseconds, something which saves time, maximizes efficiency, and performs time-consuming procedural tasks autonomously at an exponentially faster speed. "Multiple data bytes of information will be passed around on the networks here in the near future. So as we think about big data, and how do we handle all that data and turn it into information without getting overloaded, this will be a key part of AI, then we're talking about handling decentralized systems," Nathan Husted of the Naval Surface Warfare Center, Carderock told an audience at the 2022 Sea Air Space Symposium.

In health care, the days of business as usual are over. Around the world, every health care system is struggling with rising costs and uneven quality despite the hard work of well-intentioned, well-trained clinicians. Health care leaders and policy makers have tried countless incremental fixes--attacking fraud, reducing errors, enforcing practice guidelines, making patients better "consumers," implementing electronic medical records--but none have had much impact. At its core is maximizing value for patients: that is, achieving the best outcomes at the lowest cost. We must move away from a supply-driven health care system organized around what physicians do and toward a patient-centered system organized around what patients need. We must shift the focus from the volume and profitability of services provided--physician visits, hospitalizations, procedures, and tests--to the patient outcomes achieved. And we must replace today's fragmented system, in which every local provider offers a full range of services, with a system in which services for particular medical conditions are concentrated in health-delivery organizations and in the right locations to deliver high-value care. Making this transformation is not a single step but an overarching strategy. We call it the "value agenda." It will require restructuring how health care delivery is organized, measured, and reimbursed. In 2006, Michael Porter and Elizabeth Teisberg introduced the value agenda in their book Redefining Health Care. Since then, through our research and the work of thousands of health care leaders and academic researchers around the world, the tools to implement the agenda have been developed, and their deployment by providers and other organizations is rapidly spreading. The transformation to value-based health care is well under way. Some organizations are still at the stage of pilots and initiatives in individual practice areas. Other organizations, such as the Cleveland Clinic and Germany's Schön Klinik, have undertaken large-scale changes involving multiple components of the value agenda. The result has been striking improvements in outcomes and efficiency, and growth in market share. There is no longer any doubt about how to increase the value of care. The question is, which organizations will lead the way and how quickly can others follow? The challenge of becoming a value-based organization should not be underestimated, given the entrenched interests and practices of many decades. This transformation must come from within.