The Aedes aegypti mosquito that can carry dengue, yellow fever, and Zika was thought to be too reliant on a hot and wet climate to survive in the Mountain West. But now, a population is thriving in Western Colorado. Hannah Livesay, biologist at the Grand River Mosquito Control District, points out the characteristic white markings of an Aedes aegypti mosquito shown under a microscope at her lab in Grand Junction, Colo. It can carry life-threatening diseases. It's difficult to find and hard to kill.

Harvey Castro talks about how AI could be used in cold cases and the symbiotic relationship between AI and a detective. A human head and set of hands found inside a freezer at a western Colorado home recently sold before the discovery in January have been discovered as those of a 16-year-old girl who went missing almost 20 years ago. On Jan. 12, people were cleaning out a Grand Junction, Colorado, home, located nearly 200 miles west of Denver, when they discovered a human head and hands inside a freezer. On Friday, the Mesa County Coroner's Office announced that, through DNA testing, the victim was identified as Amanda Leariel Overstreet. The Mesa County Sheriff's Office said Overstreet is believed to have been about 16 years old when she disappeared, adding that she had not been seen or heard from since April 2005.

Planning has been part of the core pursuit for artificial intelligence since its conception, but earlier AI agents mostly focused on constrained settings because many of the cognitive substrates necessary for human-level planning have been lacking. Recently, language agents powered by large language models (LLMs) have shown interesting capabilities such as tool use and reasoning. Are these language agents capable of planning in more complex settings that are out of the reach of prior AI agents? To advance this investigation, we propose TravelPlanner, a new planning benchmark that focuses on travel planning, a common real-world planning scenario. It provides a rich sandbox environment, various tools for accessing nearly four million data records, and 1,225 meticulously curated planning intents and reference plans. Comprehensive evaluations show that the current language agents are not yet capable of handling such complex planning tasks-even GPT-4 only achieves a success rate of 0.6%. Language agents struggle to stay on task, use the right tools to collect information, or keep track of multiple constraints. However, we note that the mere possibility for language agents to tackle such a complex problem is in itself non-trivial progress. TravelPlanner provides a challenging yet meaningful testbed for future language agents.

GRAND JUNCTION, Colo. (KJCT) – Artificial Intelligence (AI) has been used in many daily tasks for years like Siri, Google Maps and even …

It's not a vulture or crow but a Falcon--a new brand of unmanned aerial vehicle, or drone, and Johnson is flying it. The sheriff's office here in Mesa County, a plateau of farms and ranches corralled by bone-hued mountains, is weighing the Falcon's potential for spotting lost hikers and criminals on the lam. A laptop on a table in front of Johnson shows the drone's flickering images of a nearby highway. Standing behind Johnson, watching him watch the Falcon, is its designer, Chris Miser. Rock-jawed, arms crossed, sunglasses pushed atop his shaved head, Miser is a former Air Force captain who worked on military drones before quitting in 2007 to found his own company in Aurora, Colorado. The Falcon has an eight-foot wingspan but weighs just 9.5 pounds.

Copulas allow to learn marginal distributions separately from the multivariate dependence structure (copula) that links them together into a density function. Vine factorizations ease the learning of high-dimensional copulas by constructing a hierarchy of conditional bivariate copulas. However, to simplify inference, it is common to assume that each of these conditional bivariate copulas is independent from its conditioning variables. In this paper, we relax this assumption by discovering the latent functions that specify the shape of a conditional copula given its conditioning variables. We learn these functions by following a Bayesian approach based on sparse Gaussian processes with expectation propagation for scalable, approximate inference. Experiments on real-world datasets show that, when modeling all conditional dependencies, we obtain better estimates of the underlying copula of the data.

A practical criterion for the success of a knowledge-based problem-solving system is its usefulness as a tool to those working in its specialized domain of expertise. This paper describes an evaluation and several applications of a knowledge-based system, the PROSPECTOR consultant for mineral exploration. PROSPECTOR is a rule-based judgmental reasoning system that evaluates the mineral potential of a site or region with respect to inference network models of specific classes of ore deposits. Knowledge about a particular type of ore deposit is encoded in a computational model representing observable geological features and the relative significance thereof.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.