Browsing: llms

Anthropic alleges that Chinese AI developers harvested millions of model outputs to train domestic systems, prompting a shift in security protocols.

The integration of large language models into software development workflows is fundamentally altering the role of engineers from primary authors to system evaluators.

The Apex AI Fund has integrated a proprietary large language model to process millions of daily data points for real-time investment signal generation.

The rapid acceleration of frontier model releases is driving a structural shift toward inference cost optimization and domain-specific architectures.

New research reveals that large groups of AI agents spontaneously converge on consensus, mirroring the collective behavior of biological swarms.

Researchers leverage Bayesian optimization to refine parameter-efficient fine-tuning, reducing computational costs for large language models.

The new library enables native Gemini model access across Android and JVM environments using Kotlin-specific features for improved performance.

New research from Booz Allen Hamilton demonstrates that commodity attack harnesses can bridge massive performance gaps between AI models, rendering traditional capability rankings insufficient for assessing enterprise risk.

NextEra Energy and Santee Cooper are deploying generative AI agents to optimize grid operations and financial forecasting, moving beyond experimental prototypes into production-grade infrastructure.

The company introduces a new AI stack designed to optimize performance for Indian languages through specialized model architecture and sovereign data control.