Image generators are designed to mimic their training data, so where does their apparent creativity come from? A recent study suggests that it’s an inevitable by-product of their architecture.

Habit, not conscious choice, drives most of our actions, according to new research from the University of Surrey, University of South Carolina and Central Queensland University.

The research, published in Psychology & Health, found that two-thirds of our daily behaviors are initiated “on autopilot”, out of habit.

Habits are actions that we are automatically prompted to do when we encounter everyday settings, due to associations that we have learned between those settings and our usual responses to them.

Governments have the right to decide how to spend money on science. Modelling shows that making instant cuts to grants without a plan or consultation is misconceived.

When Science Fiction Becomes Engineering

View recent discussion. Abstract: The remarkable zero-shot capabilities of Large Language Models (LLMs) have propelled natural language processing from task-specific models to unified, generalist foundation models. This transformation emerged from simple primitives: large, generative models trained on web-scale data. Curiously, the same primitives apply to today’s generative video models. Could video models be on a trajectory towards general-purpose vision understanding, much like LLMs developed general-purpose language understanding? We demonstrate that Veo 3 can solve a broad variety of tasks it wasn’t explicitly trained for: segmenting objects, detecting edges, editing images, understanding physical properties, recognizing object affordances, simulating tool use, and more.

Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the local rules that govern interactions among individuals.

The paper is published in the journal Cell Reports Physical Science.

The approach specifies when an ordered state should appear from random initial conditions and tunes geometric features (average radius, cluster size, flock size). Furthermore, trained on published GPS trajectories of real pigeons, the model uncovers interaction mechanisms observed in real flocks.