Niantic's AI spinout is training a new world model using 30 billion images of urban landmarks crowdsourced from players. Pokémon Go was the world's first augmented-reality megahit. Released in 2016 by the Google spinout Niantic, the AR twist on the juggernaut Pokémon franchise fast became a global phenomenon. From Chicago to Oslo to Enoshima, players hit the streets in the urgent hope of catching a Jigglypuff or a Squirtle or (with a huge amount of luck) an ultra-rare Galarian Zapdos hovering just out of reach, superimposed on the everyday world. "Five hundred million people installed that app in 60 days," says Brian McClendon, CTO at Niantic Spatial, an AI company that Niantic spun out in May last year. According to the video-game firm Scopely, which bought Pokémon Go from Niantic at the same time, the game still drew more than 100 million players in 2024, eight years after it launched.

Large language models (LLMs) often fabricate a hallucinatory text. Several methods have been developed to detect such text by semantically comparing it with the multiple versions probabilistically regenerated. However, a significant issue is that if the storyline of each regenerated text changes, the generated texts become incomparable, which worsen detection accuracy. In this paper, we propose a hallucination detection method that incorporates a multiple-fill-in-the-blank exam approach to address this storyline-changing issue. First, our method creates a multiple-fill-in-the-blank exam by masking multiple objects from the original text. Second, prompts an LLM to repeatedly answer this exam. This approach ensures that the storylines of the exam answers align with the original ones. Finally, quantifies the degree of hallucination for each original sentence by scoring the exam answers, considering the potential for \emph{hallucination snowballing} within the original text itself. Experimental results show that our method alone not only outperforms existing methods, but also achieves clearer state-of-the-art performance in the ensembles with existing methods.

After weeks of scandals Kalanick wrote of hiring Jones Despite Jones' best efforts, the public perception of Uber has deteriorated in the past few weeks controversy and boycotts Video provided by TheStreet Newslook SAN FRANCISCO -- Uber vice president of maps and business platform Brian McClendon is leaving the ride-hailing giant, another in a steady stream of recent departures from the troubled company. McClendon, in a statement provided by Uber, described the departure as amicable and long planned. "After 30 years away, I've decided to move back to my hometown of Lawrence, Kansas," he wrote. "My roots there run deep and traveling back a few times a year no longer seems like enough. This fall's election and the current fiscal crisis in Kansas is driving me to more fully participate in our democracy -- and I want to do that in the place I call home."

Uber plans to map the world, freeing itself from reliance on Google Maps and paving the way for its own fleet of driverless cars. Uber's mapping vehicles hit American roads last year, were introduced in Mexico earlier this summer, and will eventually extend to the other 76 countries where the ride-hailing service operates, gathering precise data on pickup and drop-off locations and traffic patterns. Following an influx of $3.5 billion from Saudi Arabia's sovereign wealth fund, Uber says it will invest $500 million in developing its in-house maps, the Financial Times reported. "With autonomous vehicles, maps are going to be fundamental," Brian McClendon, a vice president at Uber, told The Atlantic. "And the maps that are needed for autonomous vehicles are beyond anything that's being created today by any third party." An expert in geospatial data visualization, Mr. McClendon led Google Maps for more than a decade before jumping to Uber to lead its mapping projects last June.

Uber has announced it will invest half a billion dollars ( 380m) for its own version of Google maps. The ride-hailing firm is set to wean itself off of Google's cartographic offering in order to develop a more relevant version for its drivers, according to a recent blog post. It claims the new maps will enable drivers to more accurately pinpoint pickup and dropoff locations, as well as to see average traffic conditions of routes in order to plot the best route. Ride-hailing firm Uber (stock image pictured) is set to wean itself off of Google's cartographic offering in order to develop a more relevant version of maps for its drivers The San Francisco-based ride hailing firm has announced its plans to spend 380m ( 500m) to produce its own street maps worldwide. Uber has said the maps will contain more relevant information for drivers than Google maps, including traffic flow and improved accuracy for pickups.