모델 출시ENOpenAI Blog
Introducing the Australian Youth Safety Blueprint
OpenAI introduces the Australian Youth Safety Blueprint, a sixpillar roadmap for safer AI experiences that protect and empower young people.
AI News
Stay up to date with the latest AI industry news.
연구ENMIT Technology Review AI
Could AI really kill us all? Your questions, answered.
On Wednesday, MIT Technology Review hosted a live Roundtables event for subscribers that asked the question everyone’s asking right now: Could AI really kill us all? But attendees had so many more questions than we had time to answer in the 30 minute session.
산업ENThe Verge AI
Flash floods can strike without warning — this new technology could change that
On the morning of June 9th, Laura Lin was working from her home in Lanesville, a rural southern Indiana town about 15 miles from the Kentucky border. She was on a Zoom call, unaware that the heavy rain outside was beginning to flood her yard.
산업ENWired AI
The Leftist Split Over AI Doom
The left wants AI regulation. They just can't agree on what it should look like or how concerned they should be.
산업ENWired AI
Napster Is Back, and It Wants to Digitally Clone Teachers
Once the music industry’s biggest headache, Napster’s next act is bringing AI to the classroom.
산업ENWired AI
Why AI Isn’t Likely to Wipe Out Humanity With Bioweapons
Of all the threats presented by uncontrollable artificial intelligence, scientists say death by plague ranks low.
연구ENArXiv AI
Regularized Emphatic Temporal-Difference Learning: Stability under Constant Stepsizes
arXiv:2609.19170v1 Announce Type: new Abstract: Emphatic temporaldifference learning ETD stabilizes the expected offpolicy TD update and changes its projection geometry, but neither property determines constantstepsize sampled dynamics.
연구ENArXiv AI
BioPhys-Bridge: A Benchmark for Interdisciplinary Scientific Reasoning in Physics-Grounded Biological Research
arXiv:2609.19180v1 Announce Type: new Abstract: Language models face unique challenges in analyzing interdisciplinary scientific research literature.
연구ENArXiv AI
What Do We Expect from LLMs? Mapping the Design of LLM Benchmarks
arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models LLMs is assessed and communicated. Yet model rankings alone reveal little about how evaluation requirements themselves are changing.
연구ENArXiv AI
Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer
arXiv:2609.19203v1 Announce Type: new Abstract: AI applications have shifted from single, monolithic foundation models FM to compound agentic systems. Yet today's stacks remain fragmented: even as protocols e.g.
연구ENArXiv AI
What Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis
arXiv:2609.19212v1 Announce Type: new Abstract: Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to study rigorously under controlled settings.
연구ENArXiv AI
Characterizing Web Search by Conversational LLM Agents: From Search Decisions and Strategies to Results and Responses
arXiv:2609.19244v1 Announce Type: new Abstract: Conversational LLM agents increasingly rely on Web search, yet the endtoend lifecycle of agentic search remains poorly understood.