AI News — Saturday, June 13, 2026
Researchers introduce EvoArena, a new benchmark and framework for evaluating how LLM agents evolve and manage memory to maintain robustness in constantly changing environments.
Engineers within Meta's recently formed AI unit reportedly describe their working conditions as extremely challenging and demoralizing, raising concerns about internal culture and project pressures.
Google has filed a lawsuit against a Chinese cybercrime group accused of leveraging AI to defraud hundreds of thousands of victims, highlighting the growing threat of AI-powered scams.
A new sparse attention mechanism, MiniMax Sparse Attention, is proposed to improve the efficiency of large language models by focusing on the most critical tokens.
SpatialClaw presents a novel action interface designed to enhance the spatial reasoning capabilities of AI agents, allowing for more intuitive and effective interaction with 3D environments.
BBVA is partnering with OpenAI to embed AI deeply into its banking services, aiming to revolutionize financial operations and customer experiences.
InterleaveThinker introduces a method for reinforcing interleaved generation in AI agents, enabling them to better combine planning and execution for complex tasks.
This paper investigates the ability of Multimodal Large Language Models (MLLMs) to self-recover and robustly understand visual content even when it is corrupted.
FORT-Searcher proposes a method to create challenging, shortcut-resistant search tasks, crucial for training more robust and intelligent deep search agents.
MaxProof introduces a new approach to scale mathematical proof generation using a combination of generative-verifier reinforcement learning and population-level test-time scaling.
OpenAI has introduced new Academy courses designed to equip professionals with the skills needed to effectively apply AI technologies in various work environments.
LabVLA introduces a new framework for training vision-language-action models specifically designed to operate and assist within complex scientific laboratory environments.
An AWS developer shares their positive experience and reasons for adopting the Agent Toolkit for AWS, highlighting its benefits for building AI agents.
An experienced AI agent leader shares five crucial, non-standard shifts in approach necessary for effectively managing and optimizing AI agents in daily operations.
EurekAgent proposes that effective environment engineering for AI agents is the key to achieving fully autonomous scientific discovery.