Lt. Gen. Keith Kellogg discusses the latest with the Ukraine and Russia war after a deadly Russian attack on'America Reports.' The massive Ukrainian drone strike on Russia has strong implications for the future of all warfare. The sophisticated operation taught us that the use of low-cost, highly scalable, lethal drone technology is here to stay. Our leaders must pay attention, because the Ukraine-Russia war is a blueprint for not only how we will fight future wars but how we will have to defend ourselves from a more sophisticated and capable enemy than ever before. America's defense leaders need to start reflecting on the realities of modern warfare and fully understand that, as a country, we are not ready.

Ukrainian drones struck multiple military airbases deep inside Russia on Sunday in a major operation a day before the neighbours held peace talks in Istanbul. The Russian Defence Ministry said Ukraine had launched drone strikes targeting Russian military airfields across five regions, causing several aircraft to catch fire. The attacks occurred in the Murmansk, Irkutsk, Ivanovo, Ryazan, and Amur regions. Air defences repelled the assaults in all but two regions – Murmansk and Irkutsk, the ministry said. "In the Murmansk and Irkutsk regions, the launch of FPV drones from an area in close proximity to airfields resulted in several aircraft catching fire," the Defence Ministry said.

Kyiv, Ukraine – Any description of Ukraine's attacks on Russia's fleet of strategic bombers could leave one scrambling for superlatives. Forty-one planes – including supersonic Tu-22M long-range bombers, Tu-95 flying fortresses and A-50 early warning warplanes – were hit and damaged on Sunday on four airfields, including ones in the Arctic and Siberia, Ukrainian authorities and intelligence said. Moscow did not comment on the damage to the planes but confirmed that the airfields were hit by "Ukrainian terrorist attacks". Videos posted by the Ukrainian Security Service (SBU), which planned and carried out the operation, which was called The Spiderweb, showed only a handful of planes being hit. The strategic bombers have been used to launch ballistic and cruise missiles from Russian airspace to hit targets across Ukraine, causing wide scale damage and casualties.

Scientists often want to make predictions beyond the observed time horizon of "snapshot" data following latent stochastic dynamics. For example, in time course single-cell mRNA profiling, scientists have access to cellular transcriptional state measurements (snapshots) from different biological replicates at different time points, but they cannot access the trajectory of any one cell because measurement destroys the cell. Researchers want to forecast (e.g.) differentiation outcomes from early state measurements of stem cells. Recent Schrödinger-bridge (SB) methods are natural for interpolating between snapshots. But past SB papers have not addressed forecasting -- likely since existing methods either (1) reduce to following pre-set reference dynamics (chosen before seeing data) or (2) require the user to choose a fixed, state-independent volatility since they minimize a Kullback-Leibler divergence. Either case can lead to poor forecasting quality. In the present work, we propose a new framework, SnapMMD, that learns dynamics by directly fitting the joint distribution of both state measurements and observation time with a maximum mean discrepancy (MMD) loss. Unlike past work, our method allows us to infer unknown and state-dependent volatilities from the observed data. We show in a variety of real and synthetic experiments that our method delivers accurate forecasts. Moreover, our approach allows us to learn in the presence of incomplete state measurements and yields an $R^2$-style statistic that diagnoses fit. We also find that our method's performance at interpolation (and general velocity-field reconstruction) is at least as good as (and often better than) state-of-the-art in almost all of our experiments.

To help evaluate and understand the latent capabilities of language models, this paper introduces an approach using optimized input embeddings, or 'soft prompts,' as a metric of conditional distance between a model and a target behavior. The technique aims to facilitate latent capability discovery as a part of automated red teaming/evaluation suites and to provide quantitative feedback about the accessibility of potentially concerning behaviors in a way that may scale to powerful future models, including those which may otherwise be capable of deceptive alignment. An evaluation framework using soft prompts is demonstrated in natural language, chess, and pathfinding, and the technique is extended with generalized conditional soft prompts to aid in constructing task evaluations.

This paper addresses the growing concern of cascading extreme events, such as an extreme earthquake followed by a tsunami, by presenting a novel method for risk assessment focused on these domino effects. The proposed approach develops an extreme value theory framework within a Kolmogorov-Arnold network (KAN) to estimate the probability of one extreme event triggering another, conditionally on a feature vector. An extra layer is added to the KAN's architecture to enforce the definition of the parameter of interest within the unit interval, and we refer to the resulting neural model as KANE (KAN with Natural Enforcement). The proposed method is backed by exhaustive numerical studies and further illustrated with real-world applications to seismology and climatology.

Waves of Ukrainian drones have hit Moscow in recent days as the Russian capital prepares for the country's most important national holiday, Victory Day, this week. Russia celebrates May 9 as Victory Day to mark the defeat of Nazi forces in World War II. The day involves a major military parade, with leaders of Russia's allies often in attendance. But this year, the run-up to the day has been clouded by a warning from Ukrainian President Volodymyr Zelenskyy, who has said Kyiv cannot guarantee the safety of the foreign leaders attending the parade in Moscow. Here is more about Ukraine's attacks, Victory Day and why it is significant. Moscow Mayor Sergei Sobyanin said on Tuesday that Russia's air defence systems shot down 19 drones flying towards Moscow from different directions.

Appropriate modelling of extreme skew surges is crucial, particularly for coastal risk management. Our study focuses on modelling extreme skew surges along the French Atlantic coast, with a particular emphasis on investigating the extremal dependence structure between stations. We employ the peak-over-threshold framework, where a multivariate extreme event is defined whenever at least one location records a large value, though not necessarily all stations simultaneously. A novel method for determining an appropriate level (threshold) above which observations can be classified as extreme is proposed. Two complementary approaches are explored. First, the multivariate generalized Pareto distribution is employed to model extremes, leveraging its properties to derive a generative model that predicts extreme skew surges at one station based on observed extremes at nearby stations. Second, a novel extreme regression framework is assessed for point predictions. This specific regression framework enables accurate point predictions using only the "angle" of input variables, i.e. input variables divided by their norms. The ultimate objective is to reconstruct historical skew surge time series at stations with limited data. This is achieved by integrating extreme skew surge data from stations with longer records, such as Brest and Saint-Nazaire, which provide over 150 years of observations.

Ukrainian President Volodymyr Zelenskyy has accused Vladimir Putin of "playing games" after the Russian leader proposed a three-day unilateral ceasefire to coincide with Moscow's Victory Day commemorations. "This is more of a theatrical performance on his part. Because in two or three days, it is impossible to develop a plan for the next steps to end the war," Zelenskyy told a small group of journalists on Friday, in remarks embargoed until Saturday. Russia announced a 72-hour halt in hostilities beginning May 8, but has so far rejected an unconditional 30-day ceasefire pushed by Ukraine and the United States, which is trying to broker an end to the three-year war. Zelenskyy said Ukraine would not be "playing games to create a pleasant atmosphere to allow for Putin's exit from isolation on May 9" when some foreign leaders are due in Moscow for Russia's World War II commemorations.

I feel a troubling kind of opacity in my brain lately--as if reality were becoming illegible, as if language were a vessel with holes in the bottom and meaning was leaking all over the floor. I sometimes look up words after I write them: does "illegible" still mean too messy to read? The day after Donald Trump's second Inauguration, my verbal cognition kept glitching: I got an e-mail from the children's-clothing company Hanna Andersson and read the name as "Hamas"; on the street, I thought "hot yoga" was "hot dogs"; on the subway, a theatre poster advertising "Jan. Ticketing" said "Jia Tolentino" to me. Even the words that I might use to more precisely describe the sensation of "losing it" elude me.