今天,英特尔正式发布了 12 代酷睿移动处理器,分为 U / P / H 三系列,其中 U 系列又分为 9W 和 15W 两种,全系大小核设计,Intel 7 工艺打造。

9W U 系列
9W U 系列包括 5 核赛扬 7300 到 10 核 i7-1260U,TDP 9W,睿频功耗可达 29W,最高配备 96EU 核显。

15W U 系列
15W U 系列包括 5 核 赛扬 7305 到 10 核 i7-1265U,TDP 15W,睿频功耗可达 55W。

28W P 系列
28W P 系列包括 10 核 i3-1220p 到 14 核 i7-1280p,TDP 28W,睿频功耗可达 64W。

45W H 系列
45W H 系列包括 8 核 i5-12450H 到 14 核 i9-12900HK,两款 i9 型号睿频可达 5GHz。H 系列平台支持高达 DDR5-4800 的内存配置,也支持 DDR4-3200、LPDDR5-5200 和 LPDDR4x-4267。

intel 12th realse

性能方面,英特尔表示,i9-12900HK 在游戏方面比 i9-11980HK 快了 28%。i9-12900HK 的每瓦性能相比苹果 M1 Max 和 AMD Ryzen 9 5900HX 更高。在部分 Adobe、Autodesk 软件中,i9-12900HK 比苹果 M1 Max 和 AMD Ryzen 9 5900HX 表现更佳。

12 月 31 日消息,车上插 U 盘太麻烦?今日百度网盘官微宣布,百度网盘即将在 CarLife 上线。

百度网盘 CarLife

官方称,打开百度 CarLife+(7.6.0 及以上版本),找到百度网盘车机版,即可一键实现手机-车机互联能力。

百度 CarLife + 是百度公司推出的一款手机车机智能互联产品,类似于苹果的 CarPlay,只需在车内连接手机,即可将 CarLife 汇集的车生活服务分享到车载屏幕上。

Recently, Baidu Create 2021 (Baidu AI Developer Conference) Autonomous Driving Sub-forum "Creating Auto Robot Connection Technology and Scenarios Together" was held in the "Xiyang" APP. At the forum, Baidu Apollo Autonomous Driving Open Platform Apollo7.0 version was officially released. It also showed the outside world the layout of the Apollo X plan in the ecology of multiple car robots. Baidu Apollo is accelerating the development and commercialization of China's autonomous driving industry through the use of diverse automotive robot connection technologies and scenarios, and using technology to empower ecological partners.

Baidu releases Apollo7.0

The self-driving open platform is an important support for Baidu's multi-car robots. The Apollo7.0 released this time has achieved a milestone complete evolution from code to tools, and from open source platforms to tool-based platforms. Based on the four open source platforms of cloud services, open source software, hardware development, and vehicle certification, Apollo 7.0 provides a series of upgrades including one-stop practice cloud platform Apollo Studio, industry-leading simulation services, and efficient new models. Not only code Fully open and capable of providing a full-stack tool chain for autonomous driving, which is easier to use, more advanced, and more efficient to help developers use platform capabilities.

At the cloud service platform level, Apollo 7.0 officially upgrades the "data pipeline" service popular among developers in version 6.0 to Apollo Studio, covering the entire process of cloud tool chain for developers from on-board to on-board practice, providing developers with one Station-based practice platform experience. At the simulation platform level, Apollo 7.0 launched the industry's first PnC reinforcement learning model training and simulation evaluation platform. It has multiple advantages such as real data, powerful functions, comprehensive evaluation standards, and scalable architecture. It is expected to provide a unified verification standard for reinforcement learning research. At the open source software platform level, Apollo7.0 upgraded the perception and prediction algorithm modules, and introduced three deep learning-based models, MaskPillars, SMOKE, and Inter-TNT, to effectively reduce problems such as missed detection and jitter.

At present, Baidu’s Apollo autonomous driving open platform has completed 11 iterations. It has more than 80,000 developers and more than 210 partners in 135 countries around the world. The total amount of open source code is 700,000 lines. It has grown into the world's most active autonomous driving open. platform.

In addition, Baidu Apollo also shared with developers the rich resources and latest developments of the Apollo EDU Autonomous Driving Education Talent Program, and announced the goal of empowering tens of millions of colleges and enterprises and cultivating millions of autonomous driving engineering talents in the next three years. , Comprehensive coverage of application-oriented and research-oriented talents, enabling autonomous driving to truly empower all walks of life and promote the continued prosperity and development of the autonomous driving industry.

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