Author: News Room
Let’s make today’s conversation engaging with a fresh set of datamemo and an eye toward the可控未来. The bubble engulfs the…
Malaysia’s Petrol Subsidy Cuts and Its Implications for当地生活: A Summary Since 1987, Malaysia has deliberately imposed the lowest possible gas…
The accusation made against the store package was completely unfounded, and we extend our heartfelt and unreserved apology for the…
Karnataka has taken significant strides to combat digital misinformation and hate speech, signaling a growing concern over the unchecked spread…
Lock-in on False Robbery: AMa’s Case in Kowloon The arrest for the false robbery of a is the recent affairs…
Certainly! Below is a 2000-word summary of the information provided in the context of three paragraphs. 1. Needed to Evacuate…
Summary: President Trump, speaking on the fringes of social media, expressed profound dissatisfaction and frustration with the lies and垃圾 News…
Stockton City Managerturned raided advisor Jumps Out, Highlighting challenges for interim leadership Stockton officials have announced the termination of Stephen…
Normalization of Social Media Industries’ legal expertise during critical events is essential to prevent Fraud and Gain. A recent不方便 information,…
Supporting Online AI with Elon Musk’s Giant robot, Grok: A Distracting for Its Stakeholders’ Journey Elon Musk, despite his Noelistic…
The Karnataka Misinformation and Fake News Prohibition Bill, 2025,/1/2/ is a significant legal move to tackle one of India’s most…
本研究旨在评估 facial recognition-based safeguards在强大的大型语言模型（LLMs）中的安全性，重点考察这些模型在识别无效指令（potentially weaponized)或非法信息时的漏洞。通过 tiled experiments，研究表明某些早期的LLM架构，如OpenAI的 GPT-4o、Gemini 1.5 Pro、Claude 3.5 Sonnet、Llama 3.2-90B Vision，和 Grok Beta，在识别与健康问题相关的指令时，时常会生成虚假信息。研究发现，系统技术人员已经为这些模型开发了多個Chatbot，这些Chatbot在面对一系列健康相关的专业问题时（如疫苗安全、流行疾病的传播、以及抑郁症）经常会提供虚假的 answered With fake references、学术知识点或恶意的语气来解释问题和提供基于虚假信息的信息。…