The article discusses which explorations AMAP has conducted in the Serverless field and how to combine with businesses to implement Serverless R&D platform.
In this blog, we will explore how AutoNavi (AMAP) used Alibaba Cloud's serverless capabilities to support large-scale and high-traffic deployment scenarios.
This article describes how AMAP's technical team has developed a unique solution to address memory leak challenges in order to ensure the quality of their android app.
This article explores the concept of frontend memory and discusses how developers can choose the best data storage method for each development scenario.
This article summarizes the exploration and practice of applying deep learning to predict estimated time of arrival (ETA) in AMAP.
This article examines the challenges related to the application of deep learning as an important tool in improving AMAP performance and discusses the feasibility of proposed solutions.
This article describes how AMAP uses machine learning to automate and improve the efficiency of processing large amounts of user intel.
This article introduces some ideas and practices concerning in-depth POI information access in AMAP during the transition to a platform architecture.
This article introduces how AMAP front-end technology developed with the rapid growth of the business and discusses the future development directions of the AMAP front-end.
This article will address how new retail methodology and technology can be applied to a retail booth, or pop-up store scenario.
Alibaba Cloud was awarded the "Best ISV Partner of the Year" by MongoDB, honoring Alibaba Cloud's contributions as a MongoDB partner.
This article explores how image recognition technology is used in AMAP data production for more accurate character and text recognition.
This article introduces the key technologies used in AMAP's navigation and positioning systems for mobile phones and vehicles, and discusses its evolution.
This article explains the construction process of AMAP's integrated algorithm engineering to meet the iterative process of its business.
Ren Xiaofeng, Chief Scientist for Amap, discusses how Amap develops algorithms to shape the future of travel through map production, route planning, and more.
Learn about the technologies that Alibaba's AMAP team, the mobile map and navigation hub of Alibaba, is using to improve positioning precision.
In this post, Changyi, a technical expert from Amap, discusses the six major methods of coding and talks about why you may want to know them all.
This article outlines how to improve the accuracy of start-point road tracking of AMAP, and focuses on the exploration and practice of introducing machine learning algorithms.
This article describes the application of machine learning in map data generation and traffic sign recognition for AMAP.
This article describes the specific application of machine learning for the AMAP suggestion service, particularly the attempts at model optimization.