Anthropic’s new study provides empirical evidence of alignment faking in large language models, exposing trust challenges in AI safety training.
By mimicking the genome’s data compression, researchers have developed an AI algorithm that performs complex tasks with minimal training, revealing new possibilities for efficient intelligence.
AI’s rising energy demands pose major challenges to sustainability. Tech giants are turning to nuclear power, cooling innovations, and efficiency measures to adapt.
Autonomous AI agents are transforming automation, with Nvidia, Microsoft, Anthropic and Google competing to lead. All you need to know about the next AI frontier
India’s strategic plan for AI leadership involves education initiatives, tech partnerships, and a skilled workforce, positioning it as a global AI powerhouse.
AI is changing the legal profession by automating routine tasks, enhancing efficiency, and raising new ethical challenges for legal professionals and their clients.
Human trainers are becoming essential to AI’s development, helping to mitigate errors and improve accuracy. As AI evolves, the expertise of trainers in fields like medicine and finance is critical to reducing hallucinations and maintaining model reliability.
The AI landscape is increasingly defined by the contrasting approaches of open source and closed source models. This article examines the nuances of each approach, exploring their benefits, challenges, and implications for businesses, developers, and the future of AI.
Explore AI ethics via Aristotle’s philosophy, focusing on human-centered design, enriched ethical values, and democracy’s role in AI development, as detailed in the “Lyceum Project” white paper.
