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Research#llm📝 BlogAnalyzed: Dec 27, 2025 11:01

Dealing with a Seemingly Overly Busy Colleague in Remote Work

Published:Dec 27, 2025 08:13
1 min read
r/datascience

Analysis

This post from r/datascience highlights a common frustration in remote work environments: dealing with colleagues who appear excessively busy. The poster, a data scientist, describes a product manager colleague whose constant meetings and delayed responses hinder collaboration. The core issue revolves around differing work styles and perceptions of productivity. The product manager's behavior, including dismissive comments and potential attempts to undermine the data scientist, creates a hostile work environment. The post seeks advice on navigating this challenging interpersonal dynamic and protecting the data scientist's job security. It raises questions about effective communication, managing perceptions, and addressing potential workplace conflict.

Key Takeaways

Reference

"You are not working at all" because I'm managing my time in a more flexible way.

Getty's AI Generator Trained on Licensed Images

Published:Sep 25, 2023 13:28
1 min read
Hacker News

Analysis

This news highlights Getty Images' move to create an AI image generator using only its licensed image library. This is significant because it addresses copyright concerns and potentially offers a more legally compliant alternative to AI models trained on scraped data. The focus on licensed images could also lead to higher quality outputs, as the training data is curated and professionally produced. However, the success of this model will depend on the diversity and size of Getty's image library, and whether it can compete with models trained on much larger datasets.
Reference

Research#llm👥 CommunityAnalyzed: Jan 4, 2026 09:24

Ask HN: What Neural Networks/Deep Learning Books Should I Read?

Published:Aug 12, 2019 12:27
1 min read
Hacker News

Analysis

This is a discussion thread on Hacker News, a platform for tech enthusiasts. The article's core is a question: recommendations for books on neural networks and deep learning. The value lies in the collective knowledge and experience of the community, offering a curated list of potentially valuable resources. The lack of a specific author or publisher suggests a community-driven, rather than a professionally produced, piece of content.

Key Takeaways

    Reference

    N/A