Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 742

Artificial Intelligence Needs Spiritual Intelligence

One group, A.I. and Faith, convenes tech executives to discuss the important questions about faith’s contributions to artificial intelligence. The founder David Brenner explained, “The biggest questions in life are the questions that A.I. is posing, but it’s doing it mostly in isolation from the people who’ve been asking those questions for 4,000 years.” Questions such as “what is the purpose of life?” have long been tackled by religious philosophy and thought. And yet these questions remained answered and programmed by secular thinkers, and sometimes by those antagonistic toward religion. Technology creators, innovators, and corporations should create accessibility and coalitions of diverse thinkers to inform religious thought in technological development including artificial intelligence.

Independent of development, faith leaders have a critical role to play in moral accountability and upholding human rights through the technology we already use in everyday life including social media. The harms of religious illiteracy, misinformation, and persecution are largely perpetrated through existing technology such as hate speech on Facebook, which quickly escalated to mass atrocities against the Rohingya Muslims in Myanmar. Individuals who have faith in the future must take an active role in combating misinformation, hate speech, and online bullying of any group.

The future of artificial intelligence will require spiritual intelligence, or “the human capacity to ask questions about the ultimate meaning of life and the integrated relationship between us and the world in which we live.” Artificial intelligence becomes a threat to humanity when humans fail to protect freedom of conscience, thought, and religion and when we allow our spiritual intelligence to be superseded by the artificial.

Volcanoes or Asteroid? AI Ends Debate Over Dinosaur Extinction Event

To address the long-standing debate about whether a massive asteroid impact or volcanic activity caused the extinction of dinosaurs and numerous other species 66 million years ago, a team at Dartmouth College took an innovative approach — they removed scientists from the debate and let the computers decide.

The researchers report in the journal Science a new modeling method powered by interconnected processors that can work through reams of geological and climate data without human input. They tasked nearly 130 processors with analyzing the fossil record in reverse to pinpoint the events and conditions that led to the Cretaceous –Paleogene (K–Pg) extinction event that cleared the way for the ascendance of mammals, including the primates that would lead to early humans.

Google DeepMind researchers use AI tool to find 2mn new materials

Google DeepMind researchers have discovered 2.2mn crystal structures that open potential progress in fields from renewable energy to advanced computation, and show the power of artificial intelligence to discover novel materials.

The trove of theoretically stable but experimentally unrealised combinations identified using an AI tool known as GNoME is more than 45 times larger than the number of such substances unearthed in the history of science, according to a paper published in Nature on Wednesday.

The researchers plan to make 381,000 of the most promising structures available to fellow scientists to make and test their viability in fields from solar cells to superconductors. The venture underscores how harnessing AI can shortcut years of experimental graft — and potentially deliver improved products and processes.

Millions of new materials discovered with deep learning

An #AI tool that has discovered 2.2 million new materials, and helps to predict material stability.

AI tool GNoME finds 2.2 million new crystals, including 380,000 stable materials that could power future technologies.

Modern technologies from computer chips and batteries to solar panels rely on inorganic crystals. To enable new technologies, crystals must be stable otherwise they can decompose, and behind each new, stable crystal can be months of painstaking experimentation.

Today, in a paper published in Nature, we share the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. We introduce Graph Networks for Materials Exploration (GNoME), our new deep learning tool that dramatically increases the speed and efficiency of discovery by predicting the stability of new materials.