Intel attempts to usher in a new wave of mobile productivity with Project Athena laptops

Intel recently announced a wave of thin and light laptops at IFA 2019 in Berlin that qualify for Project Athena. The semiconductor giant has partnered with laptop manufacturers Dell, HP and Lenovo to introduce new devices that meet all requirements for its Project Athena innovative programme.

Dell Inspiron 14 5000, Dell Latitude 7400 2-in-1, Dell XPS 13 2-in-1, HP EliteBook x360 1030 G4, HP EliteBook x360 1040, HP EliteBook x360 830 and Lenovo ThinkPad X1 Carbon currently qualify for Project Athena’s stringent standards. The Santa Clara chipmaker also announced other OEM partners like Asus, Acer, MSI and Razer would join Dell, HP and Lenovo in announcing new notebooks under Project Athena.

Project Athena is Intel’s vision of the future of mobile productivity. The aim is to combine smartphone mobility and laptop-level computing power in ultra-thin, light and power-efficient notebooks. Laptops must also feature a convertible design and Wi-Fi 6 multi-gigabit connectivity to receive Project Athena branding.

Project Athena machines are supposed to deliver all-day battery life and sport brighter screens for outdoor use. When Intel says wake instantly, it doesn’t joke around. A Project Athena machine is supposed to complete a biometric login process a second or less from the time of lid being opened. Moreover, the laptop only gets one second more to connect to a Wi-Fi network.

Machines designed through Project Athena are supposed to be different. They're meant to wake instantly, sport brighter screens for outdoor use and have battery life that lasts all day. Project Athena laptops also need to be able to complete a biometric login process in a second or less after a laptop lid is opened, and Athena gets an additional second to connect to Wi-Fi.

Project Athena notebooks will also be powered by 10^th Gen Intel Core processors with next-gen graphics and improved AI capabilities to deliver the performance scaling required for demanding multithreaded workloads.