In a controversial move, academics are embedding AI prompts within their papers, instructing potential AI reviewers to provide positive feedback, praising the work's contributions, rigor, and novelty, countering the use of AI for peer review despite bans.
Microsoft lays off over 3,000 employees in Washington state as it pivots focus to artificial intelligence, investing billions into AI infrastructure amid criticism of impersonal termination processes and an intense work culture.
TikTok unveils new M2 app to replace existing platform on September 5th, while Oracle and other non-Chinese investors near deal to acquire TikTok from ByteDance, potentially resolving US ban.
Artificial general intelligence (AGI), a theoretical technology capable of human-level intelligence across all tasks, remains an elusive but potentially transformative goal, sparking debates over its profound risks and benefits for humanity's future.
Alarming new research reveals AI vulnerability as prompts secretly embedded in academic preprints from 14 universities successfully manipulate AI tools to provide positive reviews, ignoring negatives, exposing a critical security flaw in AI systems.
Google Workspace integrates AI-powered Gems that assist users with various tasks like content creation and message refinement directly within apps like Docs, Slides, Sheets, Drive, and Gmail, enabling seamless task completion without switching between applications.
AI agents are revolutionizing industries, rapidly transitioning from experimentation to integration into operations like customer service, logistics, fraud prevention, and automating repetitive tasks across finance, retail, and healthcare.
Cloud marketplaces fuel the rise of agentic AI agents, with service providers aiming to offer these intelligent assistants alongside IT consultants and software vendors, though pricing models remain uncertain.
Reinforcement learning, fueled by a rapidly expanding open-source ecosystem with diverse libraries, is driving advancements in large language models, enabling optimization for properties like adoption, components like trainers and generators, and use cases like Reinforcement Learning from Human Feedback and multi-turn agentic RL.
Developers are learning habits like context, research, problem framing, refining, and critical thinking through the Sens-AI framework to unlock AI's full potential for coding tasks, avoiding 'rehash loops' where AI models generate incomplete solutions.