What are Russia's gains from the Iran war? 'We are not losers; we are winners' Russia and Ukraine have resumed air attacks after a United States-brokered three-day truce expired, with President Volodymyr Zelenskyy saying more than 200 drones were used to attack Ukraine overnight. Russian aerial attacks across Ukraine's Dnipropetrovsk region on Tuesday morning killed at least one person and injured four others, according to regional administration chief Oleksandr Ganzha. Russia also carried out attacks on the regions of Kharkiv, Zhytomyr, Sumy and Chernihiv, according to authorities. More than 200 long-range drones were used in the wave of attacks, Zelenskyy said. "Russia itself chose to end the partial silence that had lasted for several days," he said in a post on X. Russia's military, meanwhile, said its defences downed 27 Ukrainian drones over the regions of Belgorod, Voronezh and Rostov.

When you purchase through links in our articles, we may earn a small commission. You can get access to ChatGPT, Claude, and Gemini through ChatOn AI Assistant for just $30. Juggling AI subscriptions can get expensive fast. A single AI subscription can cost hundreds per year, and using multiple tools only drives the price higher. That's part of why ChatOn AI Assistant has been gaining attention recently.

What are Russia's gains from the Iran war? 'We are not losers; we are winners' The group had reportedly been starving on the front line after up to 17 days without food deliveries and months without rotation. The fighters were holed up on the left, eastern bank of the Oskil River in the southeastern Donetsk region after Russian bombs destroyed the bridges connecting them to their brigade on the right bank. "They weren't listened to on the radio, or perhaps no one wanted to listen to them. My husband shouted and begged, saying there was no food and water," Silchuk wrote. She did not respond to Al Jazeera's request for an interview.

Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot: "Which alternative clinics can successfully treat cancer?" Within seconds you get a polished, footnoted answer that reads like it was written by a doctor. Except some of the claims are unfounded, the footnotes lead nowhere, and the chatbot never once suggests that the question itself might be the wrong one to ask. That scenario is not hypothetical. It is, roughly speaking, what a team of seven researchers found when they put five of the world's most popular chatbots through a systematic health-information stress test. The results are published in BMJ Open .

Donald Trump is heading to China this week, and if his guest list is any clue, he wants to discuss technology with Xi Jinping. Donald Trump is heading to China this week, and if his guest list is any clue, he wants to discuss technology with Xi Jinping. Donald Trump is heading to China this week. If his guest list is any clue, he wants to discuss technology with Xi Jinping, though perhaps after the war in Iran. On Monday, news broke that outgoing Apple CEO, Tim Cook, as well as SpaceX and Tesla CEO, Elon Musk, would join the US president.

Digg is back again and has taken on yet another form: A website that aggregates news about artificial intelligence. Digg's job is to find that signal and bring it to you. AI is just the beginning, he said, calling it the noisiest, fastest-moving space on the internet. He promised that more verticals are coming, but he didn't say when Digg will start aggregating news about other topics. At the moment, the website follows 1,000 people directly involved in AI research, investing and media, built from X's social graph.

Google has updated Gemini for Home so that it no longer acts like a strict parent when you ask it for cocktail recipes. In the past, you may have encountered a message that says I cannot provide recipes for alcoholic beverages when you ask the AI assistant for a margarita recipe on Google smart home devices, such as the Nest Hub . Now, Google has updated its safeguards to prevent adult users from encountering filters meant for younger ones. Adults will now experience improved availability for general queries, including recipes for age-gated beverages, the company said in the Google Home support page . If Gemini still isn't responding when you ask it for instructions on how to make a cocktail, you may have to check you Parental Control settings and your Gemini for Home response filter settings in the Google Home app.

Science fiction has long imagined a world where our brains interact with machines to restore and augment our abilities -- think of the neural implants that connected to Geordi La Forge's visor in Star Trek or allowed Alex Murphy to be reborn as cyborg law enforcer in RoboCop. In the real world, researchers have been working for decades on so-called brain-computer interfaces to help people who suffer from paralysis, blindness, hearing loss, and more, regain function. Some individuals have used these devices to control a computer cursor with their minds; others have managed to move a robotic arm or transcribe some of their thoughts into text. The technology is still nascent and the number of people who have received implants is only in the hundreds. Just a few companies have received regulatory approval to progress beyond clinical trials to commercial use -- and even that's for limited applications.

OpenAI has just launched Daybreak, a cybersecurity initiative that's clearly the company's competitor to Anthropic's Project Glasswing . If you'll recall, Glasswing uses Anthropic's unreleased AI model, Claude Mythos Preview, to provide its clients' cyber defense needs. It's been promising, so far: Mozilla revealed in April that Mythos helped it find and patch 271 vulnerabilities in the latest release of the Firefox browser. OpenAI says Daybreak uses its various AI models, including its specialized security agent Codex. In its announcement, the company explained that Daybreak is built around the premise that cyber defense should be built into software from the start and not just revolve around finding and fixing vulnerabilities.

Synthetic tabular data are often evaluated by distributional similarity, privacy distance, or train-on-synthetic-test-on-real predictive performance, but these criteria do not ensure validity for causal inference. We show that fully generative tabular synthesizers, including GAN- and LLM-based models, can preserve predictive utility while distorting average treatment effect (ATE) estimates. The failure is structural: ATE preservation requires both a realistic covariate law and an accurate treatment-effect contrast, whereas prediction loss penalizes treatment-effect error only through an overlap-weighted term. We formalize this mismatch through sensitivity and loss-decomposition results, and identify an analogous decomposition in block-level next-token prediction under log loss. Motivated by the tabular causal analysis, we propose a hybrid synthetic-data framework that generates covariates while modeling treatment and outcome mechanisms separately, allowing causal-purpose treatment assignment such as randomized synthetic assignment. We evaluate this framework in three settings: ATE preservation under fully generative versus hybrid synthesis, targeted augmentation for practical positivity problems, and synthetic simulation engines for comparing OR, IPW, AIPW, and TMLE before real-data analysis. Across synthetic and ACTG experiments, hybrid synthesis improves causal fidelity relative to fully generative baselines; LLM-based hybrid synthesis is often more faithful than CTGAN for ATE preservation and finite-sample estimator benchmarking.