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In a First, Apple Maps Navigation To Be Embedded In Ford UEV Pickups

2 months ago
Ford will become the first automaker to embed Apple Maps directly into its vehicles, starting with an all-electric midsize pickup built on its new Universal Electric Vehicle platform. "The pickup -- with Ford testing preproduction models on roads now -- is expected to start at $30,000 when it comes to market in 2027," reports the Detroit Free Press. "Ford has said several other EVs off that platform will follow, including a small all-electric SUV." From the report: Ford CEO Jim Farley said the new EVs will redefine advanced technology as simple, useful, and at a price point that is attainable for most people. "We're proud to embed Apple Maps' navigation and mapping technology directly into our Universal Electric Vehicle Platform, giving customers the ultimate navigation experience alongside our Ford app, a full suite of software, and next-generation BlueCruise, all enabled by a new zonal architecture," Farley said in a statement. "Apple Maps has delivered a world-class product, and we're honored to be among the first to embed it directly into a vehicle, helping define intuitive, capable driving." In a joint statement, Apple and Ford said the integration will deliver a "beautiful and easy-to-use navigation experience powered by Apple Maps directly to the vehicle's displays. Road-level Maps information will also enable Ford's Latitude AI team to build a seamless hands-free driving experience." Ford said it will use that road information to develop its next-generation BlueCruise hands-free highway driving capability. Also, by leveraging Apple's new MapKit for Automotive SDK, Ford's UEV Platform will offer drivers turn-by-turn directions using natural language, real-time traffic information, intuitive search and routing options for the best route. The system will give drivers EV routing functionality to help drivers with the warming and cooling process of the vehicle's battery before driving or fast-charging.

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Four Young Mathematicians Awarded the 2026 Fields Medals

2 months ago
Scientific American reports that the 2026 Fields Medals went to four mathematicians for work ranging from the theory of knots to the motion of fluid: The Fields Medals went to Hong Wang of New York University and France's Institute of Advanced Scientific Studies (IHES), Yu Deng of the University of Chicago, John Pardon of Stony Brook University and Jacob Tsimerman of the University of Toronto. In the awards' 90-year history, Wang is only the third woman to win one, after mathematicians Maryam Mirzakhani and Maryna Viazovska in 2014 and 2022, respectively. Wang and Deng represent the prizes' only Chinese-born recipients besides mathematician Shing-Tung Yau, who won a Fields Medal in 1982. Hong Wang co-proved the three-dimensional Kakeya conjecture, establishing a fundamental limit on how little space is needed to rotate a line through every possible direction. Mathematician Nets Katz called it the field's "holy grail" problem and said the achievement made her "a central figure" in the area. Yu Deng and his collaborators reconciled the microscopic and macroscopic mathematics of fluid motion, proving that equations describing chaotic molecular interactions and large-scale fluid behavior are fundamentally connected. N.Y.U. mathematician Scott Armstrong called it "a truly spectacular, singular result." John Pardon made an early breakthrough in knot theory by proving that certain sequences of knots can have arbitrarily large "distortion," a measure of how difficult they are to traverse. Princeton mathematician David Gabai said the problem had "attracted much interest among mathematicians during the previous 25 years." Jacob Tsimerman and two collaborators proved the Andre-Oort conjecture, giving mathematicians a stronger way to understand special points on complex geometric objects known as Shimura varieties. Collaborator Jonathan Pila described him as "a brilliant mathematician" known for his "brilliance and resourcefulness." Tsimerman has also advanced Hodge theory and hopes pure mathematics can help researchers better understand AI.

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