Latest AI (Artificial Intelligence) News
Majority of Online Articles Automated by AI as Musk Proposes AI Safety Measures
By late 2025, AI generates the majority of online articles. Elon Musk has outlined three requirements for AI safety, emphasizing autonomous robot self-building. His push for American robotics is coupled with global AI surveillance expansions and disruptive effects on education and HR sectors.
Google Launches Gemini 3 Deep Think Mode for Advanced Reasoning
Google’s Gemini 3 introduces "Deep Think" mode for Ultra subscribers, marking a shift from rapid prediction to deliberate System 2 reasoning. It excels in mathematics, heavy science, and logic puzzles, outperforming previous models in technical accuracy benchmarks.
Accenture and OpenAI Form Massive Partnership to Deploy Enterprise Agentic AI
Accenture is integrating ChatGPT Enterprise across tens of thousands of employees and employing OpenAI's AgentKit to build custom AI agents automating workflows in supply chain and finance, bridging research and real-world enterprise applications.
Microsoft Researchers Achieve AI-Driven Breakthroughs in Materials Science and Healthcare
Microsoft’s 2025 research includes AI tools like MatterGen for materials discovery, RAD-DINO for X-ray diagnostics, and AI models enhancing MRI tumor detection. These advances promise faster, more accurate scientific and medical insights using multi-modal AI integration.
Microsoft Brings Advanced Discovery AI Platform to New Jersey AI Hub
Microsoft’s Discovery AI platform, leveraging agentic AI and cloud computing, is being introduced at the NJ AI Hub in partnership with Princeton University. It enables accelerated scientific discovery through advanced data analysis and collaboration.
AI Immunologists Enhance Scientific Discovery but Face Hypothesis Development Limits
Large language model AI agents automate complex scientific tasks like literature review and data mining but still struggle to generate original biological hypotheses, highlighting ongoing challenges in AI-assisted scientific innovation.
Johns Hopkins Study Questions Efficacy of Large-Scale Deep Learning AI Models
Published in Nature Machine Intelligence, this study argues model design could outweigh extensive deep learning in AI performance, challenging investment trends in billion-dollar AI systems and influencing future AI development strategies.