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Technology#Artificial Intelligence📝 BlogAnalyzed: Jan 3, 2026 02:13

New Year Special 2026: The Future of the AI Era and Technological Innovation

Published:Jan 2, 2026 15:01
1 min read
Qiita AI

Analysis

The article reflects on historical turning points and suggests a similar transformative potential for current AI developments. It frames AI as a potential 'singularity' moment, drawing parallels to past technological leaps.
Reference

“当時の人々には「奇妙な実験」でしかなかったものが、現代の私たちから見れば、文明を変えた転換点だっ...”

PermalinkQiita AI
Research#AI Career/Data Science📝 BlogAnalyzed: Jan 3, 2026 06:07

From Small Data Prediction to Decision Making: Summarizing Research Hypotheses After Changing Jobs

Published:Dec 31, 2025 14:43
1 min read
Zenn ML

Analysis

The article discusses the author's career transition from NEC to Preferred Networks (PFN) and reflects on their research journey, particularly focusing on the challenges of small data in real-world data analysis. It highlights the shift from research to decision-making, starting with the common belief that humans are superior to machines in small data scenarios.

Key Takeaways

Reference

“The article starts with the common saying, "Humans are stronger than machines with small data."”

PermalinkZenn ML
Research#llm📝 BlogAnalyzed: Dec 26, 2025 17:02

AI Coding Trends in 2025

Published:Dec 26, 2025 12:40
1 min read
Zenn AI

Analysis

This article reflects on the author's AI-assisted coding experience in 2025, noting a significant decrease in manually written code due to improved AI code generation quality. The author uses Cursor, an AI coding tool, and shares usage statistics, including a 99-day streak likely related to the Expo. The piece also details the author's progression through different Cursor models, such as Claude 3.5 Sonnet, 3.7 Sonnet, Composer 1, and Opus. It provides a glimpse into a future where AI plays an increasingly dominant role in software development, potentially impacting developer workflows and skillsets. The article is anecdotal but offers valuable insights into the evolving landscape of AI-driven coding.
Reference

“2025 was a year where the quality of AI-generated code improved, and I really didn't write code anymore.”

PermalinkZenn AI
Research#Reinforcement Learning📝 BlogAnalyzed: Dec 29, 2025 08:07

Trends in Reinforcement Learning with Chelsea Finn - #335

Published:Jan 2, 2020 19:59
1 min read
Practical AI

Analysis

This article from Practical AI discusses trends in Reinforcement Learning (RL) in 2019, featuring Chelsea Finn, a Stanford professor specializing in RL. The conversation covers model-based RL, tackling difficult exploration challenges, and notable RL libraries and environments from that year. The focus is on providing insights into the advancements and key areas of research within the field of RL, highlighting the contributions of researchers like Finn and the tools they utilize. The article serves as a retrospective on the progress made in RL during 2019.

Key Takeaways

Reference

“The conversation covers topics like Model-based RL, solving hard exploration problems, along with RL libraries and environments that Chelsea thought moved the needle last year.”

PermalinkPractical AI
Research#Deep Learning👥 CommunityAnalyzed: Jan 10, 2026 16:53

Deep Learning: A 2019 Retrospective

Published:Jan 18, 2019 13:55
1 min read
Hacker News

Analysis

This Hacker News article, referencing a video, provides a valuable glimpse into the state of deep learning in 2019. The format indicates a review of the field at a specific point in time, potentially highlighting key advancements and challenges.

Key Takeaways

Reference

“The article's context provides the title: 'Deep Learning State of the Art (2019)' which indicates the core topic.”

PermalinkHacker News
Research#ML👥 CommunityAnalyzed: Jan 10, 2026 17:18

Machine Learning Scale 2017: A Retrospective

Published:Feb 18, 2017 18:39
1 min read
Hacker News

Analysis

This article provides a recap of Machine Learning Scale 2017, likely focusing on key advancements and trends discussed at the conference. Without specific details, it's difficult to assess the depth or impact of the review, but it serves as a historical record.

Key Takeaways

Reference

“The article is a recap of Machine Learning Scale 2017.”

PermalinkHacker News