KDD 2020 Honors Career Achievements in Knowledge Discovery and Data Mining
New Prizes Recognize Innovation, Service, Rising Stars and Enduring Research Papers Ahead of the 26th Annual Conference.
AI Technology & Industry Review
New Prizes Recognize Innovation, Service, Rising Stars and Enduring Research Papers Ahead of the 26th Annual Conference.
Tencent Graph Computing (TGraph) officially announced the release of Plato, an open source high-performance graph computing framework that meets the ultra-large-scale graph computing requirement of billion-level nodes.
KDD 2019 features both a Research track and an Applied Data Science (ADS) track, and today organizers announced their Best Paper Awards.
In the late 2000s Fortune Global 500 healthcare companies ramped up AI deployment in the industry, from in-hospital diagnosis and treatment to drug supply chain and out-of-hospital scenarios.
With its improved productivity and accuracy and more personalized experience, AI is revolutionizing medical imaging. According to Signify Research, the world market for AI in medical imaging — comprising software for automated detection, quantification, decision support, and diagnosis — will reach US$2 billion by 2023.
SyncedLeg is a tool designed to help with that by mining influential keywords from the corpus with traffic data. A team of Synced interns developed the tool over an internal two-day Hackathon, naming it after their team “机器之腿” (“Machine’s leg” in Chinese).
Google is looking to expand its AI research activities in the Japanese capital. The company’s deep learning and AI research team Google Brain yesterday posted a “Tokyo job listing seeking talented experts to participate in cutting edge research on machine learning”.
Tencent Youtu — literally translated as “image optimization lab” — is the image processing, pattern recognition, machine learning, and data mining research arm of Chinese tech giant Tencent Group.
Baidu Research announced talent acquisition of Dr. Kenneth W. Church, Dr. Jun Hua, and Dr. Hui Xiong, and launched two new research labs.
AI companies require accurate data for specialized applications, and seemingly little things such as labelling and tagging demand accuracy. At present, only humans are up for the task.