When a SpaceX rocket failure set the skies aflame over western Europe last February, no-one was sure if the debris was also polluting our atmosphere. Now scientists are directly linking the uncontrolled rocket re-entry to a plume of lithium measured less than 100km above Earth. It is the first time researchers have drawn a direct link between a known piece of space debris crashing to Earth and pollution levels. They warn that as SpaceX chief Elon Musk pledges to launch one million satellites in the coming years, this contamination could be the tip of the iceberg. The scientists were already investigating the problem of pollution from space debris when they realised a SpaceX Falcon 9 had failed in flight.

The negative prompt used is " unrealistic, bad anatomy, wrong anatomy, extra limb, missing limb,

An elephant foot bone found by archaeologists digging in southern Spain may be evidence that a troop of war elephants stomped through ancient Europe. It would be the first concrete proof of the legendary Carthaginian General Hannibal's troop of battle elephants, according to academics. Drawings of Hannibal's war against the Romans had long suggested that the beasts were used in fighting, but no hard evidence backed up the theories. Now the creatures' skeletal remains appear to have been found in an Iron Age dig near Cordoba. Beyond ivory, the discovery of elephant remains in European archaeological contexts is exceptionally rare, says the team of scientists in a paper published in Journal of Archaeological Science: Reports.

Environment Animals Wildlife Elephants are smart. Their 1,000 whiskers make them dextrous enough to pick up a tortilla chip. Breakthroughs, discoveries, and DIY tips sent six days a week. An elephant's trunk is a wonder of evolution. Gentle, yet dextrous, it can pick up solid items, help them communicate, and be a helpful showering too l.

You have probably heard the parable of the blind men and the elephant. One feels the trunk and says it's a snake, another feels a leg and claims it's a tree. It warns of how focusing on single parts can obscure the whole. Neuroscience made the same mistake for decades, viewing the brain as a collection of specialised regions, each working on a distinct function. Our understanding of what each region did often stemmed from incredible accidents, like the case of Phineas Gage, a 19th-century railway worker who survived having an iron rod blown through his brain.

Why do elephants have such big ears? The multi-use appendages are kind of like their superpower. The African elephant has some of the world's biggest ears, measuring more than six feet long and more than four feet wide. Breakthroughs, discoveries, and DIY tips sent every weekday. While real life elephants can't fly, they certainly have enormous ears.

Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigation. However, most existing methods apply interventions uniformly across all inputs, degrading model performance when steering is unnecessary. We introduce Dynamically Scaled Activation Steering (DSAS), a method-agnostic steering framework that decouples when to steer from how to steer. DSAS adaptively modulates the strength of existing steering transformations across layers and inputs, intervening strongly only when undesired behavior is detected. At generation time, DSAS computes context-dependent scaling factors that selectively adjust the strength of any steering method. We also show how DSAS can be jointly optimized end-to-end together with the steering function. When combined with existing steering methods, DSAS consistently improves the Pareto front with respect to steering alone, achieving a better trade-off between toxicity mitigation and utility preservation. We further demonstrate DSAS's generality by applying it to a text-to-image diffusion model, showing how adaptive steering allows the modulation of specific concepts. Finally, DSAS introduces minimal computational overhead while improving interpretability, pinpointing which tokens require steering and by how much.

The hyperparameters for training are detailed in Table 7. We perform the human evaluation on two of the four in-depth knowledge quality assessment metrics. V alidity ( "): whether the generated visual knowledge is valid to humans . Conformity ( "): whether the generated knowledge faithfully depicts the scenarios in the images . Our calculated average pairwise Cohen's Suppose you are looking at an image that contains the following subject and object entities: Subject list: [Insert the subject names here] Object list: [Insert the object names here] Please extract 5-10 condensed descriptions that describe the interactions and/or relations among those entities in the image.

Poachers kill over 20,000 African elephants every year for their ivory. Breakthroughs, discoveries, and DIY tips sent every weekday. The California Department of Fish and Wildlife (CDFW) recently broke up an alleged illegal poaching front in Los Angeles County. According to the department, thousands of elephant ivory pieces along with multiple "large, intricately carved tusks," a sea turtle shell, and at least nine rhinoceros horns were confiscated from an unnamed business. "The global demand for ivory and rhino horn fuels poaching and organized crime," CDFW Deputy Director and Chief of Law Enforcement Nathaniel Arnold said in a statement, adding that these and other operations "send a clear message" to black market vendors.

Can neural networks systematically capture discrete, compositional task structure despite their continuous, distributed nature? The impressive capabilities of large-scale neural networks suggest that the answer to this question is yes. However, even for the most capable models, there are still frequent failure cases that raise doubts about their compositionality. Here, we seek to understand what it takes for a standard neural network to generalize over tasks that share compositional structure. We find that simply scaling data and model size leads to compositional generalization. We show that this holds across different task encodings as long as the training distribution sufficiently covers the task space. In line with this finding, we prove that standard multilayer perceptrons can approximate a general class of compositional task families to arbitrary precision using only a linear number of neurons with respect to the number of task modules. Finally, we uncover that if networks successfully compositionally generalize, the constituents of a task can be linearly decoded from their hidden activations. We show that this metric correlates with failures of text-to-image generation models to compose known concepts.