Writing complete stories is considered a hallmark display of human intelligence, and thus researchers in artificial intelligence (AI) and natural language generation (NLG) have long used it as a pinnacle task for their research (Klein et al., 1973; Meehan, 1977; Turner, 1993; Dehn, 1981; Liu and Singh, 2002; McIntyre and Lapata, 2009). Creative writing and storytelling present unique challenges for automatic language generation: story arcs extend over thousands of words, stories typically contain multiple characters with their own distinctive personas and voices, and well-written stories have an authorial voice that is consistent and identifiable. At the same time, lies and fabrications-common generation flaws which are a liability in tasks like machine translation and automatic summarization-can be an asset in the creative domain. In recent years, the field of NLG has progressed by leaps and bounds due to the development of neural language models capable of learning the structure of language by ingesting billions of written words (Chowdhery et al., 2022; Zhang et al., 2022; Brown et al., 2020). There has been considerable work in applying these advancements toward the development of AI-powered tools for creative writing, but nearly all previous research in this space has evaluated their methods either with amateur writers or with crowd workers paid to assess performance on narrowly defined tasks (Clark et al., 2018; Roemmele and Gordon, 2015; Nichols et al., 2020). While these sorts of evaluations are valuable as preliminary assessments, we believe it is also crucial to solicit feedback from actual domain experts in creative writing: professional writers, educators, and language experts. Skilled writers comprise a unique user group with a different set of needs and expectations than amateurs.

LAYTON, Utah -- Some Utah firefighters are getting some help to detect wildfires before flames are visible. The EDWIN Project (Early Detection Wildfire Imaging Network) uses cameras with artificial intelligence (A.I.) to seek out hot spots in wildfires among the hills along portions of the Wasatch Front. Three thermal imaging cameras, developed by a team at UTOPIA Fiber, were installed in Layton, Murray and Woodland Hills simultaneously for a BETA test. "Their A.I. cameras caught the early stages of a brush fire in Woodland Hills on July 6," said Bob Knight, spokesman for UTOPIA Fiber. Crews extinguished the smoldering flames before the fire consumed too much acreage.

Unison Inc., the leading provider of software and insight to government agencies, program offices, and contractors, today introduced the Data Validation Engine to support the modernization of the federal acquisition lifecycle. This transformative app utilizes machine learning, an application of Artificial Intelligence (AI), to automate configurable rules for improved data quality and accuracy. "We launched the Data Validation Engine with acquisition modernization as a top priority to put the power in the hands of federal agencies to drive compliance with their policies and procedures," said Reid Jackson, Unison President and CEO. "At Unison, we bring real-world applications of leading-edge technical innovations to the federal acquisition and contractor workforces. This app is just the latest of several new product releases built on our Insight Platform using the latest AI and RPA technologies."

This is new territory for families. For the first time, children who are too young to distinguish fantasy from reality are engaging with devices powered by artificial intelligence. Many see smart speakers as magical, imbue them with human traits and boss them around like a Marine drill instructor, according to several new studies in the past year. Hunter Walk, a San Francisco venture capitalist, worried that his family's Amazon Echo "is turning our daughter into a raging asshole," he wrote in a blog post in 2016, because of the 4-year-old's tendency to boss it around. He has since set rules around how to talk to the device and said he hasn't noticed any rude behavior by his daughter, who is now 6. "I still have concerns," Mr. Walk says.

This is new territory for families. For the first time, children who are too young to distinguish fantasy from reality are engaging with devices powered by artificial intelligence. Many see smart speakers as magical, imbue them with human traits and boss them around like a Marine drill sergeant, according to several new studies in the past year. Hunter Walk, a San Francisco venture capitalist, worried that his family's Amazon Echo "is turning our daughter into a raging asshole," he wrote in a blog post in 2016, because of the 4-year-old's tendency to boss it around. He has since set rules around how to talk to the device and said he hasn't noticed any rude behavior by his daughter, who is now 6. "I still have concerns," Mr. Walk says.

EVOC (for EVOlution of Culture) is a computer model of culture that enables us to investigate how various factors such as barriers to cultural diffusion, the presence and choice of leaders, or changes in the ratio of innovation to imitation affect the diversity and effectiveness of ideas. It consists of neural network based agents that invent ideas for actions, and imitate neighbors' actions. The model is based on a theory of culture according to which what evolves through culture is not memes or artifacts, but the internal models of the world that give rise to them, and they evolve not through a Darwinian process of competitive exclusion but a Lamarckian process involving exchange of innovation protocols. EVOC shows an increase in mean fitness of actions over time, and an increase and then decrease in the diversity of actions. Diversity of actions is positively correlated with population size and density, and with barriers between populations. Slowly eroding borders increase fitness without sacrificing diversity by fostering specialization followed by sharing of fit actions. Introducing a leader that broadcasts its actions throughout the population increases the fitness of actions but reduces diversity of actions. Increasing the number of leaders reduces this effect. Efforts are underway to simulate the conditions under which an agent immigrating from one culture to another contributes new ideas while still'fitting in'.