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Research#AI in Healthcare📝 BlogAnalyzed: Jan 3, 2026 06:08

Presentation on DPC Coding at Applied AI R&D Meetup

Published:Nov 24, 2025 14:50
1 min read
Zenn NLP

Analysis

The article discusses a presentation on DPC/PDPS and Clinical Coding related to a hospital product. Clinical Coding involves converting medical records into standard classification codes, primarily ICD-10 for diseases and medical procedure codes in Japan. The task is characterized by a large number of classes, significant class imbalance (rare diseases), and is likely a multi-class classification problem.
Reference

Clinical Coding is the technology that converts information from medical records regarding a patient's condition, diagnosis, treatment, etc., into codes of some standard classification system. In Japan, for diseases, it is mostly converted to ICD-10 (International Classification of Diseases, 10th edition), and for procedures, it is converted to codes from the medical treatment behavior master. This task is characterized by a very large number of classes, a significant bias in class occurrence rates (rare diseases occur in about one in several hundred thousand people), and...

Safety#Security👥 CommunityAnalyzed: Jan 10, 2026 14:59

AI Security Talk at Bay Area Meetup: A Lethal Trifecta

Published:Aug 9, 2025 14:47
1 min read
Hacker News

Analysis

The article announces a talk, but lacks detail; a deeper dive into the 'Lethal Trifecta' is required. Without further information, the impact is limited as the subject matter is unclear.

Key Takeaways

Reference

My Lethal Trifecta talk at the Bay Area AI Security Meetup

Business#Open Source👥 CommunityAnalyzed: Jan 10, 2026 16:16

Hugging Face and Open Source AI Meetup Announced in San Francisco

Published:Mar 28, 2023 22:48
1 min read
Hacker News

Analysis

This announcement highlights the growing importance of community events within the open-source AI ecosystem. The meetup, hosted by Hugging Face, likely aims to foster collaboration and knowledge sharing among AI researchers and developers.
Reference

HuggingFace and Open Source AI Meetup in SFO Mar 31st

Research#Active Learning📝 BlogAnalyzed: Dec 29, 2025 08:29

Learning Active Learning with Ksenia Konyushkova - TWiML Talk #116

Published:Mar 5, 2018 21:25
2 min read
Practical AI

Analysis

This article summarizes a podcast episode featuring Ksenia Konyushkova, a Ph.D. student researching active learning at CVLab, Ecole Polytechnique Federale de Lausanne. The discussion centers on her research, including a data-driven approach to active learning that uses a secondary model to identify the most impactful unlabeled data points for labeling. The article also touches upon her work on intelligent dialogs for bounding box annotation. Additionally, it provides updates on upcoming AI-related events, such as a TWiML Online Meetup and the AI Conference in New York, highlighting key speakers and topics.
Reference

The first paper we discuss is “Learning Active Learning from Data,” which suggests a data-driven approach to active learning that trains a secondary model to identify the unlabeled data points which, when labeled, would likely have the greatest impact on our primary model’s performance.

Technology#Machine Learning📝 BlogAnalyzed: Dec 29, 2025 08:39

Web Scale Engineering for Machine Learning with Sharath Rao - TWiML Talk #40

Published:Aug 4, 2017 00:00
1 min read
Practical AI

Analysis

This article summarizes an interview with Sharath Rao, a Tech Lead Manager & Machine Learning Engineer at Instacart, on the "TWiML Talk" podcast. The conversation focuses on practical lessons and patterns Rao has learned while building web-scale data products using machine learning, specifically for Instacart's search and recommendation systems. The article highlights Rao's familiarity with the podcast and mentions a brief discussion about an upcoming TWiML Paper Reading Meetup. It also acknowledges the presence of background noise in the recording. The article serves as a brief introduction to the podcast episode's content.
Reference

My conversation with him digs into some of the practical lessons and patterns he’s learned by building production-ready, web-scale data products based on machine learning models, including the search and recommendation systems at Instacart.

Product#GPU👥 CommunityAnalyzed: Jan 10, 2026 17:27

Nvidia CEO Unveils TITAN X GPU at Stanford Deep Learning Meetup

Published:Jul 22, 2016 02:19
1 min read
Hacker News

Analysis

The news highlights Nvidia's ongoing commitment to the high-performance computing market, showcasing its latest hardware at a prestigious academic event. This announcement likely signifies advancements in deep learning capabilities and reinforces Nvidia's dominance in the GPU space.
Reference

Nvidia's CEO revealed the new TITAN X GPU at Stanford Deep Learning Meetup.