After carefully reviewing the data, I’ve found that relevant new research papers published after 2026-04-19 are quite limited. Here is a fact-based briefing on the latest verified developments.

Weekly AI Paper Briefing — 2026-04-21

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1. Towards end-to-end automation of AI research (Nature)

• Summary: This study explores the potential and limitations of building systems where AI autonomously handles the entire research lifecycle—from hypothesis generation and experiment execution to writing the final paper.
• Key Takeaway: It highlights progress toward the long-term goal of automated research, moving from automating individual components to entire pipelines. However, it acknowledges that we haven't reached full autonomous research yet.

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2. Human scientists trounce the best AI agents on complex tasks (Nature)

• Summary: Analyzing the Stanford AI Index 2026 report, this Nature article confirms that while researchers are widely adopting AI, human scientists still outperform top-tier AI agents when tackling complex tasks.
• Key Takeaway: This report offers a realistic look at current AI limitations, pointing out the gap that remains in complex problem-solving despite the growing role of AI as a research tool.

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3. AI breakthrough cuts energy use by 100x while boosting accuracy (ScienceDaily)

• Summary: Researchers have announced a groundbreaking approach that slashes AI energy consumption by up to 100x while simultaneously improving accuracy. This comes at a critical time as AI now accounts for over 10% of U.S. power consumption.
• Key Takeaway: By providing a specific methodology to reduce energy use by 100x, this study is gaining attention as a vital solution to the energy demands of current AI infrastructure.

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4. Stanford AI Index 2026 — Korea ranks 3rd globally in AI models

• Summary: According to the "AI Index 2026" published by the Stanford Institute for Human-Centered AI (HAI) on 2026-04-13, Korea ranks 3rd in the AI model category, following the US and China.
• Key Takeaway: The report analyzes global AI computing power, carbon emissions, and public trust, showing that while AI is advancing rapidly, it is becoming difficult for society to keep pace.

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5. Microsoft Research: The intersection of AI and global sustainability

• Summary: On 2026-04-21, Microsoft Research released a study and podcast exploring how AI can help achieve global sustainability. Researchers like Doug Burger, Amy Luers, and Ishai Menache discussed concrete ways AI can address environmental issues.
• Key Takeaway: The discussion bridges the gap between the environmental footprint of AI itself and using AI to solve environmental problems, setting a new direction for sustainability research.

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Weekly Research Trend Analysis

• Rise of AI Energy Efficiency: As the expansion of AI infrastructure spikes power consumption, research achieving breakthroughs in efficiency—like the 100x reduction study—is becoming a top priority.

• The Coexistence of Automation and Limitation: The two studies in Nature highlight a paradox: while AI aims for full-cycle automation, it still lags behind humans in complex tasks. This suggests a significant gap between AI-assisted research and fully autonomous scientific discovery.

• Connecting AI and Sustainability: Both the Stanford AI Index and Microsoft Research emphasize the dual challenge of AI’s environmental impact and its potential to solve climate issues. Whether AI can truly contribute to carbon neutrality has become a central question in the research community.

Editor's Note: New paper sources published during this briefing period (2026-04-19–21) were quite limited. The information above includes only the latest verified reports and research announcements found during this time, and is strictly fact-based.