PCWorld reports that OpenAI launched Lockdown Mode for ChatGPT to combat prompt injection attacks that can hijack AI systems and steal personal information. These attacks have previously compromised AI browsers like Perplexity and controlled smart home devices through Google Gemini by tricking systems with malicious instructions. Lockdown Mode restricts features like live web browsing and Deep Research across all ChatGPT plans, though OpenAI acknowledges risks from uploaded files remain. OpenAI has launched a new security feature in ChatGPT called Lockdown Mode, designed to provide additional protection against so-called "prompt injection attacks." A prompt injection attack is when someone crafts a deceptive prompt in an attempt to trick the LLM into following malicious instructions and/or revealing sensitive information.

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It's called and it was revealed at the latest Nintendo Direct livestream . We even got a juicy trailer with plenty of gameplay and a detailed look at the world. To that end, it looks like a brand new story in a brand new world. We don't know too much about this story, other than that the protagonist is enrolled in some type of magic school (which reminds me of .) Nintendo promises more details on as we get closer to 2027.

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Endoscopic procedures are essential for diagnosing and treating internal diseases, and multi-modal large language models (MLLMs) are increasingly applied to assist in endoscopy analysis. However, current benchmarks are limited, as they typically cover specific endoscopic scenarios and a small set of clinical tasks, failing to capture the real-world diversity of endoscopic scenarios and the full range of skills needed in clinical workflows. To address these issues, we introduce EndoBench, the first comprehensive benchmark specifically designed to assess MLLMs across the full spectrum of endoscopic practice with multi-dimensional capacities. EndoBench encompasses 4 distinct endoscopic scenarios, 12 specialized clinical tasks with 12 secondary subtasks, and 5 levels of visual prompting granularities, resulting in 6,832 rigorously validated VQA pairs from 21 diverse datasets. Our multi-dimensional evaluation framework mirrors the clinical workflow--spanning anatomical recognition, lesion analysis, spatial localization, and surgical operations--to holistically gauge the perceptual and diagnostic abilities of MLLMs in realistic scenarios. We benchmark 23 state-of-the-art models, including general-purpose, medical-specialized, and proprietary MLLMs, and establish human clinician performance as a reference standard. Our extensive experiments reveal: (1) proprietary MLLMs outperform open-source and medical-specialized models overall, but still trail human experts; (2) medical-domain supervised fine-tuning substantially boosts task-specific accuracy; and (3) model performance remains sensitive to prompt format and clinical task complexity. EndoBench establishes a new standard for evaluating and advancing MLLMs in endoscopy, highlighting both progress and persistent gaps between current models and expert clinical reasoning. We publicly release our benchmark and code.

Stereo depth estimation is a critical task in autonomous driving and robotics, where inaccuracies (such as misidentifying nearby objects as distant) can lead to dangerous situations. Adversarial attacks against stereo depth estimation can help revealing vulnerabilities before deployment. Previous works have shown that repeating optimized textures can effectively mislead stereo depth estimation in digital settings. However, our research reveals that these naively repeated textures perform poorly in physical implementations, $\textit{i.e.}$, when deployed as patches, limiting their practical utility for stress-testing stereo depth estimation systems. In this work, for the first time, we discover that introducing regular intervals among the repeated textures, creating a grid structure, significantly enhances the patch attack performance. Through extensive experimentation, we analyze how variations of this novel structure influence the adversarial effectiveness. Based on these insights, we develop a novel stereo depth attack that jointly optimizes both the interval structure and texture elements. Our generated adversarial patches can be inserted into any scenes and successfully attack advanced stereo depth estimation methods of different paradigms, $\textit{i.e.}$, RAFT-Stereo and STTR. Most critically, our patch can also attack commercial RGB-D cameras (Intel RealSense) in real-world conditions, demonstrating their practical relevance for security assessment of stereo systems.

Many species didn't have much sex for millions of years. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy . Evolution is responsible for Earth's stunningly diverse spectrum of life, but that wasn't always the case.

PCWorld reports how Claude AI transformed a confusing air conditioner manual into a comprehensive 12-page guide with visuals and maintenance tips. The process involved uploading the generic manual and model number to Claude's Cowork feature, which generated accurate operating procedures and quick-start guides. This demonstrates AI's potential to make complex product documentation more user-friendly and accessible for consumers struggling with manufacturer manuals. Um, what does button do? Our new air conditioner had just arrived, a necessity for a sure-to-be-sizzling New York summer, and already I was scratching my head.

PCWorld reports Microsoft is resuming forced M365 Copilot installations after a brief pause, targeting completion by July 1st for all Microsoft 365 users. Previous forced installations caused significant backlash and critical bugs, including Copilot accessing confidential emails, contributing to Windows 11's stagnating market share. IT administrators can opt out of automatic installation, while Microsoft tests an "uninstall AI bloat" button in Windows Insider builds despite continuing AI-driven OS plans. Between October 2025 and March 2026, many Microsoft 365 users discovered that the Copilot AI app was automatically installed on their computers. After heavy vocal backlash and several crucial bugs, like the one that allowed Copilot to read confidential emails, the forced installation of Microsoft 365 Copilot was suspended. However, Microsoft has now decided to reinstate the app's forced installation.

PCWorld highlights Apple's practical AI features launching this fall, including Visual Intelligence for scanning restaurant bills and splitting costs via Apple Cash. Call Context uses Apple Intelligence to automatically display account numbers and confirmation codes during customer service calls, eliminating awkward pauses. Apple Wallet now offers a "create a pass" tool that generates digital passes from physical cards using barcode and QR code scanning. Apple mostly steered clear of the big, dumb AI announcements we often see at the big tech keynotes -- you know, things like AI pop song generators, AI-generated avatars, and virtual AI try-on tools that make for great headlines but aren't all that practical. OK, so Apple did indulge in "look at this!" AI tomfoolery, like photo-retouch tools that can wipe groups of people out of the frame and a revamped Image Playground app that can essentially deep-fake your friends (ugh). That said, Apple also unleashed a series of smaller Apple Intelligence and Siri AI features (all due to arrive this fall) that might actually be useful on a daily basis. Here are five of my favorites.