Foundation Inference Model for Point Processes

In-Context Learning of Temporal Point Processes with Foundation Inference Models

arXiv:2509.24762v3 Announce Type: replace Abstract: Modeling event sequences of multiple event types with marked temporal point processes (MTPPs) provides a principled way to uncover governing dynamical rules and predict future events. Current neural network approaches to MTPP inference rely on training separate, specialized models for each target system. We pursue a radically different approach: drawing on amortized inference and in-context learning, we pretrain a deep neural network to...

Nvidia Cosmos 3

Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what’s happening in their world, predict what’s likely to happen next, and generate actions for specific environments, embodiments, and tasks. NVIDIA Cosmos 3 is a frontier foundation model for physical AI that combines physical reasoning, world generation, and action generation within a single open model.

Human-Like Neural Nets by Catapulting

Human-like Neural Nets by Catapulting Speculative proposal to create artificial neural nets with human-like performance by high-learning-rate/regularization training of overparameterized NNs to trigger catapulting/grokking. Over-parameterization as a route to true generalization would resolve many outstanding mysteries of artificial versus natural intelligence. There are many mysteries about deep learning and human intelligence, but we could describe the biggest anomaly this way: why are...

Rethinking Search as Code Generation

Rethinking Search as Code Generation Evolving search from monolithic services to programmable primitives for the era of agent harnesses. Search is a core primitive for AI systems. Frontier models grow more capable by the month, but they still need access to fresh, accurate, and well-curated knowledge from the wider world.

MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism

arXiv:2606.07512v1 Announce Type: new Abstract: Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overcome this, we introduce MemDreamer to decouple perception and reasoning, shifting long-video understanding into an agentic exploration process. As a plug-and-play framework, it incrementally streams videos to construct a Hierarchical Graph Memory, a top-down three-tier...

The Frame Problem

The Frame Problem To most AI researchers, the frame problem is the challenge of representing the effects of action in logic without having to represent explicitly a large number of intuitively obvious non-effects. But to many philosophers, the AI researchers' frame problem is suggestive of wider epistemological issues. Is it possible, in principle, to limit the scope of the reasoning required to derive the consequences of an action?

Sakana AI's Recursive Self-Improvement (RSI) Lab

The Next Paradigm of Artificial Intelligence As the world enters the era of artificial intelligence, Japan has a unique opportunity to reclaim its position at the frontier of global innovation. However, to achieve global leadership in AI and scientific discovery, we cannot simply stick to the conventional approach of brute-forcing monolithic models. We must leapfrog the current paradigm.

ZTE unveils localized roadmap for Eurasia's digital future at GSMA M360 Eurasia 2026

Gene ancestries reveal diverse microbial associations during eukaryogenesis

Abstract The origin of eukaryotes remains a central enigma in biology1. Continuing debates agree on the pivotal role of a symbiosis between an alphaproteobacterium and an Asgard archaeon2,3. However, the nature, timing and contributions of other potential bacterial partners4,5,6 and the role of interactions with viruses7,8,9 remain contentious.

Deep learning four decades of human migration

Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...