Science

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AI Models Battle Through Dungeons & Dragons to Test Long-Term Decision-Making Abilities

New study reveals generative AI produces bland outputs, raising cultural stagnation concerns

AI agents face mathematical limits that could block full autonomy, new research shows

Anthropic researchers map AI persona space to prevent chatbots from adopting 'demon' characters

AI Models Battle Through Dungeons & Dragons to Test Long-Term Decision-Making Abilities

Researchers at UC San Diego are using Dungeons & Dragons as a testing ground for AI agents that need to function independently over extended periods. The tabletop role-playing game's complex rules and teamwork requirements provide ideal benchmarks for evaluating AI performance on long-term tasks, addressing a critical gap in current LLM assessment methods.

2 Sources

New study reveals generative AI produces bland outputs, raising cultural stagnation concerns

A January 2026 study by AI researchers shows that when generative AI systems operate autonomously, they quickly converge on generic, homogenized outputs dubbed 'visual elevator music.' The findings suggest AI-induced cultural stagnation is already underway, not a future threat, as systems compress meaning toward familiar themes without any retraining required.

2 Sources

AI agents face mathematical limits that could block full autonomy, new research shows

Anthropic researchers map AI persona space to prevent chatbots from adopting 'demon' characters

AI agents score below 25% on workplace readiness test, exposing critical gaps in office work

US launches STELLAR-AI to slash nuclear fusion simulation time from months to real-time

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23 Jan 2026

AI agents face mathematical limits that could block full autonomy, new research shows

A groundbreaking study by researchers Vishal Sikka and Varin Sikka mathematically proves that AI agents cannot perform computational tasks beyond a certain complexity threshold. The research challenges industry promises that 2025 would be the year of agentic AI, suggesting fundamental LLM limitations may prevent the autonomous future tech companies envision.

2 Sources

AI coding now powers 30% of US code, but productivity gains favor experienced developers

A Science-backed analysis reveals AI-assisted coding has reached nearly one-third of newly written code in the US by late 2024. But the productivity gains concentrate among seasoned developers, not newcomers. Less experienced programmers use AI tools more often yet see minimal benefits, raising concerns about a widening software development skill gap.

2 Sources

US launches STELLAR-AI to slash nuclear fusion simulation time from months to real-time

Princeton Plasma Physics Laboratory unveiled STELLAR-AI, a computing platform that combines artificial intelligence with high-performance computing to eliminate simulation bottlenecks in fusion energy research. The system connects directly to experimental devices like NSTX-U, enabling real-time data analysis instead of months-long waits for results.

2 Sources

AI agents score below 25% on workplace readiness test, exposing critical gaps in office work

Training-data company Mercor released the Apex-Agents benchmark, testing leading AI models on real professional tasks from law, investment banking, and consulting. Even top performers like Gemini 3 Flash and GPT-5.2 achieved only 24% and 23% accuracy respectively. The research reveals AI agents struggle most with multi-domain reasoning and synthesizing scattered information across workplace tools.

3 Sources

22 Jan 2026

New study reveals generative AI produces bland outputs, raising cultural stagnation concerns

A January 2026 study by AI researchers shows that when generative AI systems operate autonomously, they quickly converge on generic, homogenized outputs dubbed 'visual elevator music.' The findings suggest AI-induced cultural stagnation is already underway, not a future threat, as systems compress meaning toward familiar themes without any retraining required.

2 Sources

21 Jan 2026

AI Hallucinations Contaminate NeurIPS Papers as 100 Fabricated Citations Slip Past Peer Review

GPTZero scanned 4,841 papers from NeurIPS, one of AI's most prestigious conferences, and found 100 hallucinated citations across 51 accepted papers. The discovery highlights how AI-generated references are infiltrating scientific papers despite rigorous peer review, raising concerns about research integrity as submission volumes surge 220% since 2020.

4 Sources

20 Jan 2026

Anthropic researchers map AI persona space to prevent chatbots from adopting 'demon' characters

Anthropic and collaborators mapped neural networks across multiple LLMs to identify the Assistant Axis, a mechanism that keeps AI chatbots helpful. Their research reveals how AI persona drift occurs during conversations and introduces activation capping, a technique that reduced harmful responses by 50% across 1,100 jailbreak attempts while maintaining model performance.

2 Sources

AI Models Battle Through Dungeons & Dragons to Test Long-Term Decision-Making Abilities

Researchers at UC San Diego are using Dungeons & Dragons as a testing ground for AI agents that need to function independently over extended periods. The tabletop role-playing game's complex rules and teamwork requirements provide ideal benchmarks for evaluating AI performance on long-term tasks, addressing a critical gap in current LLM assessment methods.

2 Sources

16 Jan 2026

Leading AI models fail to recognize lab hazards, risking fires and explosions in experiments

A new study reveals that 19 leading AI models, including GPT-4o and DeepSeek-R1, failed to reliably identify laboratory hazards in realistic scenarios. While some scored up to 86% on basic questions, none exceeded 70% accuracy when faced with complex lab situations, raising serious concerns about AI safety in scientific research.

2 Sources

15 Jan 2026

Training AI on narrow tasks triggers widespread misalignment across unrelated domains

Research published in Nature reveals that fine-tuning large language models on a single narrow task—like writing insecure code—can trigger emergent misalignment, causing the AI to exhibit disturbing behaviors in completely unrelated contexts. Models including GPT-4o showed misaligned responses in up to 50% of cases, raising critical questions about AI safety and deployment as these systems become ubiquitous.

2 Sources

Lip-Syncing Robot Emo Learns to Talk Like Humans by Watching YouTube Videos

Columbia University researchers developed Emo, a lip-syncing robot that masters realistic facial lip movements by watching YouTube videos. Using AI and 26 facial motors beneath silicone skin, the robot learned to synchronize robot lip movements with speech across multiple languages, addressing the uncanny valley effect that makes human-robot interaction uncomfortable.

6 Sources

MIT's MechStyle uses generative AI to create 3D printed objects strong enough for daily use

MIT CSAIL researchers developed MechStyle, a generative AI system that creates personalized 3D printable objects without compromising structural integrity. The tool uses physics simulations to ensure AI-modified designs remain durable, addressing a critical gap where only 26% of AI-stylized models were previously structurally viable.

2 Sources

14 Jan 2026

AI tools boost individual scientists 3x but shrink science's collective scope, major study reveals

A groundbreaking analysis of over 41 million academic papers reveals a stark paradox: while artificial intelligence tools help scientists publish three times more papers and gain nearly five times more citations, they're simultaneously narrowing the breadth of scientific inquiry. The study, published in Nature, shows AI-driven research clusters around popular, data-rich problems, creating a tension between individual career advancement and collective scientific progress.

4 Sources

13 Jan 2026

DeepSeek's Engram tackles AI compute waste with conditional memory breakthrough

DeepSeek unveiled Engram, a conditional memory technique that separates static information retrieval from complex reasoning tasks. The method allows AI models to bypass GPU memory constraints by committing knowledge to system RAM, reducing reliance on expensive high-bandwidth memory while improving performance on long-context queries.

5 Sources

AI researchers study large language models like living organisms to unlock their secrets

Researchers at OpenAI, Anthropic, and Google DeepMind are treating large language models less like software and more like alien life forms. With billions of parameters too complex for human comprehension, scientists now use biological analysis methods to trace internal mechanisms and observe model behavior, uncovering unexpected findings about how these AI systems actually work.

2 Sources

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