GPT-5
GPT‑5: From Fast Responses to Autonomous Research Recently, OpenAI’s Chief Scientist Jakub Pachocki and Chief Research Officer Mark Chen joined a16z for an in‑depth interview, systematically revealing GPT‑5’s positioning for the first time. > This is not an incremental GPT‑4 update — it marks a
MLLM security
Introduction In recent years, Multimodal Large Language Models (MLLMs) have made remarkable breakthroughs, showing strong capabilities in visual understanding, cross-modal reasoning, and image captioning. However, with wider deployment in real-world scenarios, security risks have become a growing concern. Research indicates that MLLMs inherit adversarial vulnerabilities from their visual encoders, making
AI research
Automating Complex Scientific Processes – Shanghai AI Lab Launches FlowSearch FlowSearch represents a significant leap in AI-assisted scientific work. On benchmarks such as GAIA, HLE, GPQA, and TRQA, it delivers best-in-class performance—showcasing AI’s ability for dynamic collaboration and deep reasoning in complex scientific tasks. --- Why This Matters While
GPT-5
Rediscovering a Lost Solution with GPT‑5 Pro This case revolves around Erdős Problem #339, one of nearly a thousand problems posed or relayed by the famed mathematician Paul Erdős, archived at erdosproblems.com. The site tracks each problem’s status: * About one‑third have been solved. * Most remain open,
robotics
Authors and Affiliations This work is led by Jacky Kwok, a PhD student at Stanford University. Co-corresponding authors include: * Marco Pavone – Director of Autonomous Vehicle Research at NVIDIA * Azalia Mirhoseini – Stanford Computer Science Professor & DeepMind Scientist * Ion Stoica – UC Berkeley Professor --- Vision-Language-Action Models & Real-World Robustness Vision-Language-Action (VLA)
LLM failures
New Intelligence Source — October 13, 2025, 17:51 Beijing --- New Intelligence Report Overview > Why do large models tend to fail at long-horizon tasks? > Some experts suspect this reveals an "illusion of thought." A joint study by the University of Cambridge and partners found the root
Terence Tao
# Terence Tao’s Latest Reflections on AI in Mathematical Research  Renowned mathematician **Terence Tao**, a Fields Medal laureate, is not only pushing boundaries in mathematics but also **actively experimenting with AI collaboration**—exploring its potential in solving complex
AI research
Farewell to Traditional Fine-Tuning: Introducing ACE A groundbreaking study from Stanford University, SambaNova Systems, and the University of California, Berkeley has demonstrated a transformative approach to improving AI models — without adjusting a single weight. The method, called Agent Contextual Engineering (ACE), relies on context engineering rather than retraining. It autonomously