Author: searri

Beauty Matter

A broad spectrum of “sunscreen truthers” on platforms like TikTok, Instagram, and Facebook have peddled the trope that sunscreen causes cancer for at least the last decade. These types of conspiracy theories have reached a fever pitch on social media since the pandemic. From vegan anti-vaxxers and bro-biohackers to MAHA and QAnon supporters, they all have two things in common: a case of chemophobia and a belief that sunscreen is the enemy.

Read the full article >>

Security Week

No-one really understands how AI works or when and why it doesn’t. But the application of first-principle physics theory to the working of AI’s Attention mechanism is providing new insights.

Read the full article >>

Newswise

The Chicago Sun-Times and the Philadelphia Inquirer recently published stories with unidentifiable quotes from fake experts and imaginary book titles created by AI.

Read the full article >>

Gadget

A new study explores when and why the output of large language models goes awry and becomes a threat.

Read the full article >>

NeuroEdge

Researchers at George Washington University have developed a groundbreaking mathematical formula that predicts exactly when artificial intelligence systems like ChatGPT will suddenly shift from helpful to harmful responses – a phenomenon they’ve dubbed the “Jekyll-and-Hyde tipping point.” The new research may finally answer why AI sometimes abruptly goes off the rails.

Read the full article >>

Tech Xplore

Language learning machines, such as ChatGPT, have become proficient in solving complex mathematical problems, passing difficult exams, and even offering advice for interpersonal conflicts. However, at what point does a helpful tool become a threat?

Read the full article >>

Newswise

Newswise — Language learning machines, such as ChatGPT, have become proficient in solving complex mathematical problems, passing difficult exams, and even offering advice for interpersonal conflicts. However, at what point does a helpful tool become a threat?

Read the full article >>

Neural Intel Podcast

This academic paper introduces a novel mathematical formula that precisely predicts when a large language model (LLM) might suddenly shift from producing beneficial output to generating incorrect or harmful content, referred to as a “Jekyll-and-Hyde” tipping point. The authors attribute this change to the AI’s attention mechanism, specifically how thinly its attention spreads across a growing response. They argue that this tipping point is predetermined by the AI’s initial training and the user’s prompt, and can be influenced by altering these factors. Notably, the study concludes that politeness in user prompts has no significant impact on whether or when this behavioral shift occurs. The research provides a foundation for potentially predicting and mitigating such undesirable AI behavior.