國內唯一的人工智慧產業 AI 化專校-台湾人工智慧学校,繼台北課程引起熱烈迴響後,將前往新竹科學園區開辦分校,並於 2018 年 7 月 21 日假清華大學學習資源中心(旺宏館)國際會議廳舉行台湾人工智慧学校新竹分校首屆開學典禮,希望能為新竹當地的科技產業培育出優秀的 AI 人才,成為帶動台灣產業 AI 發展的重要人才培訓基地。
國內唯一的人工智慧產業 AI 化專校-台湾人工智慧学校,繼台北課程引起熱烈迴響後,將前往新竹科學園區開辦分校,並於 2018 年 7 月 21 日假清華大學學習資源中心(旺宏館)國際會議廳舉行台湾人工智慧学校新竹分校首屆開學典禮,希望能為新竹當地的科技產業培育出優秀的 AI 人才,成為帶動台灣產業 AI 發展的重要人才培訓基地。
面临第四次工业革命让孩子遇见未来 - Preparing Children to Face the 4th Industrial RevolutionAlex Makosz
?
于2017年7月向中远航运家长汇报,帮助家长思考他们的孩子如何面临第四次工业革命的劳动力市场和将来的社会。
Presented to parents of Cosco Shipping, July 2017, to help parents think about the future their children will face and how this should affect their preparations around education.
Deep learning techniques have achieved human-level performance in analyzing medical images for diseases. A model analyzed retinal scans and achieved an F1-score of 0.95 for detecting diabetic retinopathy, compared to 0.91 for ophthalmologists. Another model detected arrhythmias from ECG signals better than cardiologists, with an F1-score of 0.89 for the model versus 0.73 for pathologists. However, AI still has limitations such as lacking common sense, and requires further research to develop artificial general intelligence and truly intelligent assistants.
This document discusses the work of Project θ, an AI team in Taiwan. It summarizes their work over 2017-2019 solving over 10 problems for 10+ companies. Some of the problems they addressed included detecting defects in LCD panels, PCB boards, and after surface mount technology processes. They also worked on applications like predicting the quality percentage of a pigment based on its ingredients. The team grew over time and had success scaling their work through the use of transfer learning and GPU acceleration. They have continued their efforts to apply AI to address real-world problems through their non-profit AI Academy Taiwan.
This document discusses various topics related to artificial intelligence and machine learning. It provides examples of how deep learning is being used for tasks like detecting diabetic eye disease, classifying arrhythmias from ECG signals, and localizing tumors in medical images. The document also notes limitations of current AI, such as its lack of common sense, and discusses how machine learning is being applied in other domains like predicting hospital readmissions, personalized medicine, and monitoring rainforests for illegal logging.
1. The document discusses various topics related to artificial intelligence including machine learning models, data platforms, limitations of AI, and the future of jobs.
2. It provides statistics on AI adoption rates across industries and job functions. It also outlines what capabilities AI currently has and lacks, such as the ability for common sense but not general artificial intelligence.
3. The document examines use cases for AI in various fields including healthcare, transportation, manufacturing and concludes that AI will fundamentally change the global economy through mobile computing and data collection.
This document discusses the history and development of artificial intelligence in Taiwan. It covers topics such as machine learning, deep learning, natural language processing, computer vision, and generative models. The document provides examples of applications across different domains including image colorization, face generation, text summarization and machine translation. It also discusses challenges and ethical issues regarding the use of AI.