English中文
将人工智能用起来
2019年6月18-21日
北京,中国

Schedule: 与人工智能交互 (Interacting with AI) sessions

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09:00 - 17:00 Tuesday, June 18 & Wednesday, June 19
Location: 多功能厅5A+B(Function Room 5A+B)
Season Yang (McKinsey & Company)
Average rating: *****
(5.00, 1 rating)
The TensorFlow library contains computational graphs with automatic parallelization across resources, which is ideal architecture for implementing neural networks. Season Yang introduces TensorFlow's capabilities in Python, and you'll then get your hands dirty building machine learning algorithms piece by piece while using the Keras API provided by TensorFlow with several hands-on applications. 了解更多信息.
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09:0012:30 Wednesday, June 19, 2019
Location: 紫金大厅B(Grand Hall B)
Alejandro Saucedo (The Institute for Ethical AI & Machine Learning)
Numerous high-profile incidents have proved undesired bias in machine learning a worrying topic. Alejandro Saucedo uses a hands-on example to demystify machine learning bias. You'll automate the loan-approval process for a company and explore key tools and techniques from the latest research that allows you to assess and mitigate undesired bias in machine learning models. 了解更多信息.
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13:1013:50 Thursday, June 20, 2019
Location: 多功能厅6A+B (Function Room 6A+B)
姜涛 (Kwai)
介绍如何综合应用多项人工智能技术进行K歌修音和短视频自动配乐,涉及的相关技术包括:人声/音乐分离、高精度的基频提取、自动作曲/作词技术、基于视频内容的音乐生成等。 了解更多信息.
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14:5015:30 Thursday, June 20, 2019
Location: 紫金大厅B(Grand Hall B)
Mark Ryan (IBM), Alina Zhang (Skylinerunners)
Average rating: *****
(5.00, 1 rating)
Toronto is unique among North American cities for having a legacy streetcar network as an integral part of its transit system. This means streetcar delays are a major contributor to gridlock in the city. Learn about applying deep learning time series forecasting to machine learning as Mark Ryan and Alina Li Zhang explain how streetcar delays can be predicted...and prevented. 了解更多信息.
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14:0014:40 Friday, June 21, 2019
Location: 多功能厅2(Function Room 2)
Orchlon Ann (Rakuten), TzuLin Chin (Rakuten)
Average rating: ****.
(4.00, 1 rating)
Orchlon Ann and TzuLin Chin offer an overview of the Data Science Platform, a suite of tools for exploring data, training models, and running GPU/CPU compute jobs in an isolated container environment. Discover it's benefits, including one-click machine learning environment creation, a powerful job scheduler, and a flexible function-as-a-service component. 了解更多信息.
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14:0014:40 Friday, June 21, 2019
Location: 多功能厅5A+B(Function Room 5A+B)
王书浩 (透彻影像)
病理学是医学诊断的“金标准”,病理报告对于临床医生提供进一步治疗策略至关重要。一位能够独立发病理报告的病理医师需要10年以上的培养周期,我国目前共有约1万名注册在案的病理医师,根据WHO的要求,人才缺口为4-9万人。使用人工智能来辅助病理医师对样本进行诊断,不仅能够大幅提高医师的诊断效率,而且可以减少漏诊,提高诊断准确率。数字化的病理影像能够观察到组织的细胞形态,在最高倍数字扫描时,文件尺寸达到GB量级,需要从人工智能和系统工程的层面去应对这些挑战。在这个演讲中,我们将从人工智能系统的构建方法入手,介绍透彻影像与中国人民解放军总医院在消化道病理影像辅助系统研发过程中的技术细节。同时,我们将分享诊断系统从部署到落地使用的一些经验。 了解更多信息.
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14:5015:30 Friday, June 21, 2019
Location: 多功能厅6A+B (Function Room 6A+B)
杨军 (阿里巴巴), 龙国平 (Alibaba)
本次演讲会介绍阿里计算平台PAI团队过去一年多时间里在深度学习编译器领域的技术工作进展----PAI TAO(Tensor Accelerator and Optimizer)。PAI-TAO采用通用编译优化技术,来解决PAI平台所承载的多样性AI workload面临的训练及推理需求的性能优化问题,在部分workload上获得了20%到4X不等的显著加速效果,并且基本作到用户层全透明,在显著提升平台效率性能的同时也有效照顾了用户的使用惯性。目前PAI-TAO已经先后用于支持阿里内部搜索、推荐、图像、文本等多个业务场景的日常训练及推理需求。 了解更多信息.