We study the problem of (ϵ,δ)-certified machine unlearning for minimax models. Most of the existing works focus on unlearning from standard statistical learning models that have a single variable and their unlearning steps hinge on the direct Hessian-based conventional Newton update. We develop a new (ϵ,δ)-certified machine unlearning algorithm for minimax models. It proposes a minimax unlearning step consisting of a total Hessian-based complete Newton update and the Gaussian mechanism borrowed from differential privacy. To obtain the unlearning certification, our method injects calibrated Gaussian noises by carefully analyzing the "sensitivity" of the minimax unlearning step (i.e., the closeness between the minimax unlearning variables and the retraining-from-scratch variables).

When you purchase through links in our articles, we may earn a small commission. If you're using long and overly specific prompts with ChatGPT's latest model, you're doing it wrong. OpenAI's latest and most powerful model, GPT-5.5, has been topping benchmark charts and impressing users with its coding and reasoning abilities, not to mention the sheer quantity of facts at its fingertips. But while ChatGPT's latest model doesn't require the hand-holding that older models did, it also gets fussy with the longer, highly detailed prompts that might have worked well in the past. If you're seeing worse performance with GPT-5.5 than you had with previous models, it might be your prompt constructions.

How to Do It I've Been Having the Time of My Life Sexting. But I Have a Shameful Secret About Who It's With. For the last few months, I've been trying out roleplaying online. It's with an AI bot, and I've been having a lot of fun doing it, exploring kinks and gender stuff. At the same time, I find myself feeling bad about it because I know the environmental impact of AI as well as how it feels like it's making me less creative in my other (unsexy) writing.

Say hello (Moto) to price hikes on all three of Motorola's latest Razr flip phones. Like clockwork, Motorola is back with a new set of Razr folding flip phones . The formula is the same as last year, with three phones differing in specs and price: the Razr Ultra, Razr+, and Razr. But alongside these models, Motorola is finally launching its first-ever book-style folding phone, the Razr Fold, which it first teased at CES 2026 . The company announced the new handsets at an event in Los Angeles, where it also revealed a new pair of Moto Buds 2 Plus wireless earbuds that look eerily like Apple's AirPods Pro, but in blue; these will retail for $150 and will be available on April 30.

The weaponry highlights a coastal Belgian city's longtime strategic location. 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. Renovations on government buildings in the coastal Belgian town of Nieuwpoort are currently on hold after surveyors discovered an impressive archaeological trove: dozens of carefully crafted stone cannonballs dating as far back as the 14th century. However, the medieval ammunition backstock wasn't the only weaponry buried roughly 70 miles west of Brussels.

To help small aerial robots navigate in the dark and other low-visibility environments, my colleagues and I developed an ultrasound-based perception system inspired by bat echolocation. Current robots rely heavily on cameras or light detection and ranging, known as lidar, or both. But these sensors fail in visually challenging conditions, such as smoke, fog, dust, snow or complete darkness. I'm a scientific engineer who develops bio-inspired microrobots. To solve this challenge, my research team looked at nature's experts at navigating in poor visibility: bats.

However, this dance is an older male's game. 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. Attwater's prairie chickens live in coastal marshes. Breakthroughs, discoveries, and DIY tips sent six days a week. An exclusive dance party is raging in the coastal marshes along southern Texas--and it's coming to an end.

AI chatbots trained to be warm and friendly when interacting with users may also be more prone to inaccuracies, new research suggests. Oxford Internet Institute (OII) researchers analysed more than 400,000 responses from five AI systems which had been tweaked to communicate in a more empathetic way. Friendlier answers contained more mistakes - from giving inaccurate medical advice to reaffirming user's false beliefs, the study found. The findings raise further questions over the trustworthiness of AI models, which are often deliberately designed to be warm and human-like in order to increase engagement. Such concerns are accentuated by AI chatbots being used for support and even intimacy, as developers seek to broaden their appeal.

First-person video highlights a camera-wearer's activities in the context of their persistent environment. However, current video understanding approaches reason over visual features from short video clips that are detached from the underlying physical space and capture only what is immediately visible. To facilitate humancentric environment understanding, we present an approach that links egocentric video and the environment by learning representations that are predictive of the camera-wearer's (potentially unseen) local surroundings. We train such models using videos from agents in simulated 3D environments where the environment is fully observable, and test them on human-captured real-world videos from unseen environments. On two human-centric video tasks, we show that models equipped with our environment-aware features consistently outperform their counterparts with traditional clip features. Moreover, despite being trained exclusively on simulated videos, our approach successfully handles real-world videos from HouseTours and Ego4D, and achieves state-of-the-art results on the Ego4DNLQ challenge.