Science – Page 42 – Minority Mindset

When AI Stumbles: Lessons from Real-World Inference Failures

12.11.2025 by qfx

The distribution of incidents reveals a correlation between model modality and severity, suggesting that certain approaches are disproportionately associated with more critical failures.

A detailed analysis of production incidents reveals critical vulnerabilities and practical strategies for building more reliable AI services.

The Prediction Machine: Can AI Rival Human Forecasters?

12.11.2025 by qfx

The AIA Forecaster leverages a defined architecture to facilitate predictive capabilities.

A new system leveraging artificial intelligence achieves forecasting accuracy comparable to top human prediction experts.

The Coming Infrastructure Crisis: Can Networks Handle the AI Boom?

12.11.2025 by qfx

The study forecasts agent proliferation over the coming decade, revealing that while initial growth may appear exponential, resource limitations and inherent system dynamics will ultimately enforce a logistic or, more likely, a Gompertzian curve of deceleration and eventual saturation—a prophecy written into any architecture of scaling.

As AI agents and connected devices multiply, existing infrastructure faces unprecedented strain, demanding a new approach to network design.

Predicting Bitcoin’s Price Swings: Can Classic Models Keep Up?

12.11.2025 by qfx

Autocorrelation and partial autocorrelation functions applied to the Bitcoin price series reveal the inherent temporal dependencies within the cryptocurrency's valuation, offering insights into its dynamic behavior and potential predictability through time-series analysis.

Despite its reputation for chaos, Bitcoin’s price and volatility can be meaningfully forecast using established time series techniques.

China’s AI Safety Playbook

11.11.2025 by qfx

$China’s regulatory ecosystem for model deployment necessitates the formalization of Frontier Safety Policies (FSPs) and the integration of a catastrophic-risk test suite—a provable safety margin—to ensure responsible innovation and mitigate existential threats inherent in increasingly powerful artificial intelligence, demanding a shift from empirical testing to mathematically verifiable guarantees of system behavior akin to establishing bounds on $P(catastrophic\ event | AI\ system)$.$

A deep dive into Beijing’s strategies for mitigating the existential risks of advanced artificial intelligence.

Beyond the Hype: Building Reliable AI Systems

11.11.2025 by qfx

A new framework for understanding and mitigating the hidden risks within generative and agentic artificial intelligence.

Mapping Supply Chain Resilience with Network Intelligence

11.11.2025 by qfx

The system decomposes complex firm states into fundamental feature dimensions, integrates these with product relationships via a hypergraph network—allowing for the capture of higher-order dependencies—and ultimately distills a unified, system-level resilience embedding through temporal aggregation and learned inference, revealing how interconnectedness shapes overall robustness.

A new approach leverages the power of complex network analysis to better predict how supply chains withstand disruption.

Beyond the Doomsday Scenario: Reframing the AI Risk Debate

11.11.2025 by qfx

To build public support for AI governance, communication strategies must shift from focusing on distant existential threats to addressing immediate, tangible harms.

Decoding Sepsis: The Promise of Transparent AI

11.11.2025 by qfx

New research explores how explainable artificial intelligence can help doctors identify sepsis earlier and with greater confidence.

The Echo Chamber Effect: Will AI Models Forget What’s Real?

11.11.2025 by qfx

Within the architecture known as BERT, information undergoes repeated refinement through layers of attention, residual connections, and normalization, a process mirroring the gradual accumulation of entropy as any complex system navigates its operational lifespan.

A new analysis predicts a future where artificial intelligence is trained on its own creations, leading to a dangerous homogenization of online content.