Original editorial coverage of computer vision, AI perception, and machine recognition — the research and ideas behind what "I See You" actually means for a machine.
A deep dive into the systematic evaluation of image‑disguising methods like RMT and AES, revealing their impact on medical image classification and segmentation privacy.
Thinking Machines Lab argues that decentralized, fine‑tuned AI—using multimodal interaction and LoRA‑based weight adapters—can keep ownership and alignment in the hands of users.
Anthropic built its new Claude desktop agent, Cowork, in just ten days, letting AI read and edit local files while raising fresh safety questions for responsible AI adoption.
Discover OpenAI's GPT-5.6, a groundbreaking three-tier model family that sets new standards in AI performance, with Sol leading the Artificial Analysis Coding Agent Index at 80
Countries are investing in AI capabilities to drive innovation and economic growth while ensuring responsible use of technology
Discover how open models are driving AI research forward with NVIDIA's 74 accepted papers at ICML 2026
Google, NYC educators, and industry leaders gathered to discuss AI's role in preparing students for tomorrow's careers
Discover how Goose, a free and open-source AI coding agent, is challenging the expensive AI coding revolution with its local machine capabilities
Google's new search box redesign invites users to think out loud and interact with AI in a more conversational way
Discover how adaptive parallel reasoning is transforming the field of artificial intelligence by enabling models to dynamically allocate compute between parallel and serial operations
The Berkeley Artificial Intelligence Research Lab congratulates its class of 2026 graduates, who have made significant contributions to AI and machine learning.
As AI costs drop, agents will become the dominant workload for data systems, requiring new designs for data systems for, of, and by agents
Google Research introduces SensorFM, a wearable health foundation model pretrained on 1 trillion minutes of sensor data from 5 million people
Researchers investigate the connection between counterfactual fairness and group fairness in image classification, revealing a surprising disconnect
Discover how fine-tuned latent diffusion models can generate culturally consistent yet novel Ulos motifs, preserving tradition while meeting contemporary design demands
A new diagnostic tool reveals whether learned shortcuts can be restored after unlearning, shedding light on the effectiveness of shortcut-mitigation methods
Discover how ordinary vision datasets can contain exploitable adversarial surfaces, threatening model security and reliability