Estimating treatment effects is crucial for personalized decision-making in medicine, but this task faces unique challenges in clinical practice. At training time, models for estimating treatment effects are typically trained on well-structured medical datasets that contain detailed patient information. However, at inference time, predictions are often made using textual descriptions (e.g., descriptions with self-reported symptoms), which are incomplete representations of the original patient information. In this work, we make three contributions.

When you purchase through links in our articles, we may earn a small commission. Get officially certified in Claude AI for just $19.99 A Claude AI Professional E-Degree is on sale for $19.99 (reg. AI skills are no longer a nice-to-have. A verifiable credential in one of the most popular AI models on the market is a real resume differentiator, and right now, you can get an e-degree in Claude for just $19.99 (reg. While plenty of people have dabbled with Claude, there's a big difference between "I've used it a few times" and actually knowing how to make it work for you.

Recent incidents heighten anxieties that hybrid warfare tactics could trigger military confrontation with Russia. Lithuanian armed special forces and members of the Lithuanian Riflemen's Union take part in a military exercise in central Lithuania [File: Nils Adler/Al Jazeera] A member of the Lithuanian Riflemen's Union joins in military exercises in central Lithuania [File: Nils Adler/Al Jazeera] Along the forests and marshlands that separate the Baltic states from Russia and Belarus, workers are digging anti-tank ditches, pouring concrete bunkers and erecting rows of dragon's teeth - jagged concrete obstacles designed to slow and channel advancing armour - to buy precious time in the event of an attack. Russia's full-scale invasion of Ukraine in 2022 reignited old fears in Estonia, Latvia and Lithuania, where memories of Soviet rule remain close to the surface. In the years since, those fears have been channelled into preparation. Defence budgets have surged, military exercises have intensified, and new fortifications have emerged even as daily life largely continues as normal.

Ukrainian drones have struck a historic museum in Russia-annexed Sevastopol in Crimea, igniting a roof fire, as Russian authorities slashed nighttime train schedules amid intensifying air attacks across the peninsula and deep into Russia. Sevastopol's Russian-installed governor, Mikhail Razvozhayev, announced the damage on Telegram early on Wednesday. "This building is not just a museum, it is a symbol of resilience, which has repeatedly taken the blows of the enemy." Razvozhayev said that during World War II's Siege of Sevastopol, "the Panorama building was subjected to massed bombing by German aviation". He declared: "The enemy will pay for this sacrilege!"

SoftBank's attempt to get $6 billion OpenAI margin loan stalls SoftBank Group's efforts to secure at least $6 billion through a margin loan backed by its OpenAI stake have stalled after the company lowered its fundraising target. SoftBank Group's talks with potential creditors to raise at least $6 billion from a margin loan backed by its OpenAI stake have stalled, people familiar with the matter said, just weeks after the Japanese conglomerate cut its initial target from $10 billion. The company is considering various fundraising options, according to the people, who asked not to be identified discussing private matters. It could still move forward with the margin loan at a later stage, they added. It's unclear why the margin loan discussions stalled. Borrowers and creditors can pause and revisit fundraising discussions for various reasons, and SoftBank hasn't elaborated on its plans, the people said.

Uncrewed ground vehicles have already been tested for defending the front line by the Ukrainian military. There's a received piece of wisdom among militaries around the world that whatever new technologies appear, in the end, foot soldiers are what matters. As British Army officer Field Marshal Archibald Wavell put it shortly after the second world war: "All battles and all wars are won in the end by the infantryman." This may now finally be changing. Robots in battle are about to reach a critical point for Ukraine. In May, it began the mass production of Legit, a low-cost robot capable of carrying a machine gun.

Ni, who moved to the UK in 2019 to study, was targeted by what she believes is a pro-regime bot. Ni, who moved to the UK in 2019 to study, was targeted by what she believes is a pro-regime bot. A high-profile Chinese activist in the UK who was inundated with deepfake posts on X portraying her as a sexually promiscuous drug addict was told that the abuse did not breach the rules of Elon Musk's platform. Apple Peiqing Ni, the 27-year-old founder of the UK-based China Dissent Network, had been advised by UK police to complain to the US-headquartered platform after she was targeted by what she believes is a pro-regime bot. The abuse included 12 posts tagging Ni and containing fake photographs and videos of her.

Forest ecosystems play a critical role in the Earth system as major carbon sinks that are essential for carbon neutralization and climate change mitigation. However, the Earth has undergone significant deforestation and forest degradation, and the remaining forested areas are also facing increasing pressures from socioeconomic factors and climate change, potentially pushing them towards tipping points.Responding to the grand challenge, a theory-based Ecosystem Demography (ED) model has been continuously developed over the past two decades and serves as a key component in major initiatives, including the Global Carbon Budget, NASA Carbon Monitoring System, and US Greenhouse Gas Center. Despite its growing importance in combating climate change and shaping carbon policies, ED's expensive computation significantly limits its ability to estimate carbon dynamics at the global scale with high spatial resolution.Recently, machine learning (ML) models have shown promising potential in approximating theory-based models with interesting success in various domains including weather forecasting, thanks to the open-source benchmark datasets made available.However, there are currently no publicly available ML-ready datasets for global carbon dynamics forecasting in forest ecosystems. The limited data availability hinders the development of corresponding ML emulators. Furthermore, the inputs needed for running ED are highly complex with over a hundred variables from various remote sensing products. To bridge the gap, we develop a new ML-ready benchmark dataset, \textit{CarbonGlobe}, for carbon dynamics forecasting, featuring that: (1) the data has a global-scale coverage at 0.5$^\circ$ resolution; (2) the temporal range spans 40 years; (3) the inputs integrate extensive multi-source data from different sensing products, with calibrated outputs from ED; (4) the data is formatted in ML-ready forms and split into different evaluation scenarios based on climate conditions, etc.; (5) a set of problem-driven metrics is designed to develop benchmarks using various ML models to best align with the needs of downstream applications.

We sat down with Douglas Guillbault to discuss his paper, " Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors ". The results have interesting implications for how we model human cognition, and in turn, how the concept of synaesthesia could be integrated to develop more intelligent AI models. A color metaphor is the use of color to describe something in a way that is not immediately literal. For example, to say "green with envy" would be a color metaphor, because envy doesn't have an immediate visual structure to it - we're evoking a broader, more flexible notion of what green conveys, beyond just its visible properties. What makes metaphors very interesting is that they often use past experience or cultural associations in new ways to talk about something beyond our current perception - either something imagined or in the future, which are many steps of abstraction away from the present. Metaphors provide an alternative pathway to get there.

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