If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Artificial intelligence (AI) and machine learning (ML -- hereafter AI/ML) are being applied widely across the globe, affecting how individuals work, pursue health, and protect their communities. These changes have implications for society, the economy, and data science. The experiences of the United States and Japan, two of the world's wealthiest and most technologically advanced liberal democracies, represent important leading indicators of how AI/ML affect human society now and will continue to do so. At least as important, U.S. and Japanese experiences also carry lessons for each other about how the two sides of the Pacific might think about the policy impacts that AI/ML technologies can have and what policies might be necessary to effectively and safely employ learning algorithms. Given the importance of understanding the implications of AI/ML, the RAND Corporation convened a pair of public conferences that brought together leading U.S. and Japanese experts on work, health, and data security (Conference I), and on international affairs, disaster response, and disaster modeling (Conference II) to exchange views on some of the most important questions in the application of AI/ML technologies to contemporary policy issues.
Many real-world problems require complex coordination between multiple agents -- e.g., people or algorithms. A machine learning technique called multi-agent reinforcement learning (MARL) has shown success with respect to this, mainly in two-team games like Go, DOTA 2, Starcraft, hide-and-seek, and capture the flag. But the human world is far messier than games. That's because humans face social dilemmas at multiple scales, from the interpersonal to the international, and they must decide not only how to cooperate but when to cooperate. To address this challenge, researchers at OpenAI propose training AI agents with what they call randomized uncertain social preferences (RUSP), an augmentation that expands the distribution of environments in which reinforcement learning agents train.
With its single-player story campaign, the first-person shooting game, which is out today for PlayStation 4, PS5, Xbox One, Xbox Series X and S, and PCs on Battle.net Somehow, the Russians swiped a U.S. nuke in 1968 and now that mistake has come back to haunt the Reagan Administration. That trip back in time nets intelligence needed to track Perseus, a Soviet mastermind who aims to use the bomb to attack the U.S. The search takes your character across the globe with stops in a Berlin still separated by the wall, Cuba, the Ukraine, Russia, and even into the heart of KGB headquarters. That nerve-wracking mission within the security agency is only one of many mind games awaiting players in this highly-entertaining sequel to 2010's "Call of Duty: Black Ops." In that earlier game, you played primarily as Alex Mason, a CIA operator who we learned was brainwashed by the Soviets.
The 2020 presidential election presents two stark paths for the direction of future-focused scientific research, I write with my Axios colleague Alison Snyder. Why it matters: Science is a long game, with today's breakthroughs often stemming from research carried out decades ago, often with government help. That means the person who occupies the White House over the next four years will help shape the state of technology for decades into the future. Where it stands: The Trump administration's record on science is criticized by experts in nearly every field, from climate change to biotechnology to health, who sense that science as a practice has been deprioritized and politicized. Yes, but: Two research areas prioritized under the Trump administration -- AI and quantum information sciences (QIS) -- are at the heart of technonationalism and the global science race, particularly between the U.S. and China.
The vision for this future is to unlock the human voice as a meaningful measurement of health. AI voice assistants can transform speech into a vital sign, enabling early detection and predictions of oncoming conditions. Similar to how temperature is an indicator of fever, vocal biomarkers can provide us with a more complete picture of our health. One in four people globally will be affected by major or minor mental health issues at some point in their lives. Around 450 million people currently suffer from conditions such as anxiety, stress, depression, or others, placing mental health among the leading cause of ill-health worldwide.
Artificial Intelligence is often defined as the ability of a machine to learn how to solve cognitive problems--a process akin to human intelligence. Within the realm of scientific methodology and laboratory interconnectivity, the most applicable way of thinking about AI is not that it seeks to replicate human reasoning precisely, but rather that it uses human reasoning as a model with the goal of supplementing and augmenting human observation and decision processes. In this context, an AI algorithm must be trained to interpret available data and specified criteria to meet business objectives and drive operational decision making. AI further refines this process through an accumulation of relevant observations over time as both the accumulated data and business objectives are refined, allowing the understanding of the machine to approach that of human cognition. The inherent diversity of equipment and systems involved in science and discovery is particularly conducive to the benefits of AI, where laboratory operations can be continuously optimized by this constant and cumulative refinement ability.
The vision for this future is to unlock the human voice as a meaningful measurement of health. AI voice assistants can transform speech into a vital sign, enabling early detection and predictions of oncoming conditions. Similar to how temperature is an indicator for fever, vocal biomarkers can provide us with a more complete picture of our health. One in four people globally will be affected by major or minor mental health issues at some point in their lives. Around 450 million people currently suffer from conditions such as anxiety, stress, depression, or others, placing mental health among the leading cause of ill-health worldwide.
As manufacturers seek to streamline their businesses, they want to gain more insight into the health of their equipment, with the goals of keeping it running smoothly, ensuring optimal performance, and reducing unexpected downtime. Automation has long been used ito help achieve these goals, and in recent years, advances in key technologies--including artificial intelligence (AI) and Internet of Things (IoT)--have allowed manufacturers to take advantage of more sophisticated industrial use cases for automation, such as bin picking, and collaborative and autonomous mobile robots. Today, new types of assets are taking automation even further, as machines such as robotic welding arms and injection molding machines use hundreds of sensors that combine with existing data sources to improve overall equipment effectiveness (OEE). In the case of a robotic arm, for example, the machine data spans a large number of sensor and actuator measurements from the robotic arm itself, and external sources that indicate other operational and environmental conditions (e.g., line speed, job style, ambient temperature and humidity). The process of joining these technologies with AI-based IoT technologies is playing an increasingly important role in delivering tangible business value throughout the manufacturing environment.
The next industrial revolution is already happening. Artificial intelligence (AI) is ushering in an era of technologies that are faster, more adaptable, more efficient, and making the world more digitally connected. AI is best described as complementary to human intelligence, delivering the computing power to crunch numbers too big for people and recognize patterns too tedious for the human eye. In a Harvard Business Review study of 1,500 companies, it was found that the most significant performance improvements were made when humans and machines worked together. As AI becomes one of society's greatest assets, it's especially helpful for solving problems that seem larger than life -- like protecting our natural environment.
Corn, coffee, chocolate, even wine are a few of the foods that stand to be massively disrupted by the effects of climate change, population growth and water scarcity -- if they haven't already. A recent study found the yields of the world's top ten crops have begun to decrease, a drop that is disproportionately affecting food-insecure countries. The situation stands to worsen. Researchers project that the global population will increase by 3 billion in 2050. To feed these additional global residents, agricultural production must increase by 50 percent, says Dr. Ranga Raju Vatsavai, an associate professor in computer science at North Carolina State University and the associate director of the Center for Geospatial Analytics.