Imagine Apple, Bose or other consumer electronics companies making hearing aids more stylish and relatively affordable — with people having confidence that the devices had been vetted by the F.D.A. Bose told me that it’s working on over-the-counter hearing aid technology.
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On Tech is back from a spring break, and the magnolia trees are blooming outside On Tech headquarters (a.k.a., my New York apartment).
Today, let’s talk about relatively simple technology and a change in government policy that could unleash more innovation for Americans who have difficulty hearing.
Google has announced an update to its Developer Program Policy that will help to prevent applications from viewing which other apps are installed on an Android device. The company states that they consider installed apps to be private user information and therefore, aim to protect Android users by keeping this data secure.
That is to say, Google will limit which apps can request the QUERY_ALL_PACKAGES permission, presently mandatory for application targeting API level 30 (Android 11) and above that wish to query the list of application a user has installed for an Android 11 or later device.
From now on, the QUERY_ALL_PACKAGES permission will only be available when the core functionality of an app in question must query any of the device’s installed applications. Therefore, in order to dispute this new policy, developers will have to provide reasonable evidence for how querying the API of an Android devices installed applications is absolutely necessary in order for that device to properly function.
Artificial microswimmers that can replicate the complex behavior of active matter are often designed to mimic the self-propulsion of microscopic living organisms. However, compared with their living counterparts, artificial microswimmers have a limited ability to adapt to environmental signals or to retain a physical memory to yield optimized emergent behavior. Different from macroscopic living systems and robots, both microscopic living organisms and artificial microswimmers are subject to Brownian motion, which randomizes their position and propulsion direction. Here, we combine real-world artificial active particles with machine learning algorithms to explore their adaptive behavior in a noisy environment with reinforcement learning. We use a real-time control of self-thermophoretic active particles to demonstrate the solution of a simple standard navigation problem under the inevitable influence of Brownian motion at these length scales. We show that, with external control, collective learning is possible. Concerning the learning under noise, we find that noise decreases the learning speed, modifies the optimal behavior, and also increases the strength of the decisions made. As a consequence of time delay in the feedback loop controlling the particles, an optimum velocity, reminiscent of optimal run-and-tumble times of bacteria, is found for the system, which is conjectured to be a universal property of systems exhibiting delayed response in a noisy environment.
Living organisms adapt their behavior according to their environment to achieve a particular goal. Information about the state of the environment is sensed, processed, and encoded in biochemical processes in the organism to provide appropriate actions or properties. These learning or adaptive processes occur within the lifetime of a generation, over multiple generations, or over evolutionarily relevant time scales. They lead to specific behaviors of individuals and collectives. Swarms of fish or flocks of birds have developed collective strategies adapted to the existence of predators (1), and collective hunting may represent a more efficient foraging tactic (2). Birds learn how to use convective air flows (3). Sperm have evolved complex swimming patterns to explore chemical gradients in chemotaxis (4), and bacteria express specific shapes to follow gravity (5).
Inspired by these optimization processes, learning strategies that reduce the complexity of the physical and chemical processes in living matter to a mathematical procedure have been developed. Many of these learning strategies have been implemented into robotic systems (7–9). One particular framework is reinforcement learning (RL), in which an agent gains experience by interacting with its environment (10). The value of this experience relates to rewards (or penalties) connected to the states that the agent can occupy. The learning process then maximizes the cumulative reward for a chain of actions to obtain the so-called policy. This policy advises the agent which action to take. Recent computational studies, for example, reveal that RL can provide optimal strategies for the navigation of active particles through flows (11–13), the swarming of robots (14–16), the soaring of birds , or the development of collective motion (17).
This paper proposes the use of Flower Constellation (FC) theory to facilitate the design of a Low Earth Orbit (LEO) slotting system to avoid collisions between compliant satellites and optimize the available space. Specifically, it proposes the use of concentric orbital shells of admissible “slots” with stacked intersecting orbits that preserve a minimum separation distance between satellites at all times. The problem is formulated in mathematical terms and three approaches are explored: random constellations, single 2D Lattice Flower Constellations (2D-LFCs), and unions of 2D-LFCs. Each approach is evaluated in terms of several metrics including capacity, Earth coverage, orbits per shell, and symmetries. In particular, capacity is evaluated for various inclinations and other parameters. Next, a rough estimate for the capacity of LEO is generated subject to certain minimum separation and station-keeping assumptions and several trade-offs are identified to guide policy-makers interested in the adoption of a LEO slotting scheme for space traffic management.
AI And Robots For Law And Order — Irakli Beridze — Head, Artificial Intelligence and Robotics, UNICRI – United Nations Interregional Crime and Justice Research Institute.
Irakli Beridze is the Head of the Centre for Artificial Intelligence and Robotics at The United Nations Interregional Crime and Justice Research Institute (UNICRI).
With a Master’s Degree in International Relations and National Security Studies, and a law degree, Mr. Beridze has more than 20 years of experience in leading multilateral negotiations, developing stakeholder engagement programs with governments, UN agencies, international organizations, private industry and corporations, think tanks, civil society, foundations, academia, and other partners on an international level.
Mr. Beridze advises governments and international organizations on numerous issues related to international security, scientific and technological developments, emerging technologies, innovation and disruptive potential of new technologies, particularly on the issue on crime prevention, criminal justice and security, and is now actively focused on supporting government’s worldwide on the strategies, action plans, roadmaps and policy papers on Artificial Intelligence.
Since 2014, Mr. Beridze has initiated and managed one of the first United Nations Programs on AI, initiating and organizing a number of high-level events at the United Nations General Assembly, and other international organizations, finding synergies with traditional threats and risks, as well as identifying solutions that AI can contribute to the achievement of the United Nations Sustainable Development Goals.
Half a century after the last astronauts left the Moon, the idea of sending crews to Mars still seems like some sort of vague space policy notion. After all, crews have yet to revisit the Moon. So, even today, talk of getting astronauts to Mars seems largely confined to PowerPoint presentations.
Thus, it was precisely that sense of inexactitude that prompted a young South African-born entrepreneur named Elon Musk to begin his quest to make the dream of boots on Mars a reality.
It’s a notion that is chronicled with alacrity in Eric Berger’s page-turning new book “Liftoff: Elon Musk and the Desperate Early Days that Launched SpaceX.” Berger, senior space editor at Ars Technica, writes with the kind of hard-won insider authority that only comes through covering the nuts and bolts of the commercial space industry for the past twenty years.
Saving Lives; Changing Minds — Dr. Emanuele Capobianco, MD, Director for Health and Care, International Federation of Red Cross and Red Crescent Societies.
Dr. Emanuele Capobianco, MD, MPH, is the Director for Health and Care at the International Federation of Red Cross and Red Crescent Societies (IFRC), where he leads the IFRC Global Health and Care Team and provides strategic and operational support to 192 National Red Cross and Red Crescent Societies around the world in the areas of community health, emergency health and water/sanitation. He currently also leads the IFRC global response to COVID19 and the IFRC response to the Ebola outbreaks in DRC.
Before this role at IFRC, Dr. Capobianco was the Deputy Executive-Director of The Partnership for Maternal, Newborn & Child Health, a multi-constituency partnership, hosted by the World Health Organization, and is the world’s largest alliance for women’s, children’s and adolescents’ health. He joined there from the Global Fund to Fight AIDS, Tuberculosis and Malaria where he worked as Senior Policy Advisor in the Office of the Executive Director, leading the development of the 2017–2022 Global Fund Strategy.
Dr. Capobianco is a global public health expert with 20 years experience in international institutions at country, regional and headquarters level. He was the Chief of Health and Nutrition in UNICEF Mozambique, where he worked for four years to advance health outcomes for Mozambican children and women.
Previously Dr. Capobianco was at the World Bank as Senior Health Specialist, managing a large portfolio of grants, particularly in South Asia and Eastern Africa. He also worked in Somalia to support the Expanded Program on Immunization, Polio and Tuberculosis programs; and at the WHO Regional Office for the Eastern Mediterranean promoting the STOP TB partnership in the Middle East.
As the world fights the SARS-CoV-2 virus causing the COVID-19 pandemic, another group of dangerous pathogens looms in the background. The threat of antibiotic-resistant bacteria has been growing for years and appears to be getting worse. If COVID-19 taught us one thing, it’s that governments should be prepared for more global public health crises, and that includes finding new ways to combat rogue bacteria that are becoming resistant to commonly used drugs.
In contrast to the current pandemic, viruses may be be the heroes of the next epidemic rather than the villains. Scientists have shown that viruses could be great weapons against bacteria that are resistant to antibiotics.
I am a biotechnology and policy expert focused on understanding how personal genetic and biological information can improve human health. Every person interacts intimately with a unique assortment of viruses and bacteria, and by deciphering these complex relationships we can better treat infectious diseases caused by antibiotic-resistant bacteria.
SpaceX wants to begin connecting moving vehicles – from cars and trucks to jets and ships – to its Starlink satellite internet network, according to a request the company filed with the Federal Communications Commission.
“This application would serve the public interest by authorizing a new class of ground-based components for SpaceX’s satellite system that will expand the range of broadband capabilities available to moving vehicles throughout the United States and to moving vessels and aircraft worldwide,” SpaceX director of satellite policy David Goldman wrote in a letter to the FCC filed on Friday.
Starlink is the company’s capital-intensive project to build an interconnected internet network with thousands of satellites, known in the space industry as a constellation, designed to deliver high-speed internet to consumers anywhere on the planet.
The 15-member commission calls a $40 billion investment to expand and democratize AI research and development a “modest down payment for future breakthroughs,” and encourages an attitude toward investment in innovation from policymakers akin that which led to building the interstate highway system in the 1950s. Ultimately, the group envisions hundreds of billions of dollars of spending on AI by the federal government in the coming years.
The National Security Commission on AI report makes recommendations ranging from 5G and China to immigration policy and civil rights.
