While artificial intelligence is advancing at a rapid rate, the learning resources for artificial intelligence are also increasing at an equally rapid.

Kira’s AI Operating System for Education, powered by Anthropic’s Claude, generates fully scaffolded, scoped, and sequenced courses – from 9th Grade Biology to Corporate Leadership – with integrated ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...

Abstract: Efficient multi-agent path finding (MAPF) is essential for large-scale warehousing and logistics systems. Despite the potential of reinforcement learning (RL) methods, current approaches ...

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Abstract: Deep reinforcement learning has gained increasing popularity in the beyond visual range engagement of unmanned combat aerial vehicles. Regardless of the success of the maneuvering decision, ...

ABSTRACT: The surge of digital data in tourism, finance and consumer markets demands predictive models capable of handling volatility, nonlinear dynamics, and long-term dependencies, where traditional ...