anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a chatbot is more humanlike and aware than it actually is, like believing it's ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Abstract: Natural Language-based Egocentric Task Verification (NLETV) aims to equip agents to determine if operation flows of procedural tasks in egocentric videos align with natural language ...

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

A new study suggests that everyday multilingual habits—from chatting with neighbors to revisiting a childhood language—may help preserve memory, attention, and brain flexibility as we age. An ...

Abstract: This paper addresses the dynamic task assignment problem for multiple uncrewed aerial vehicles (UAVs) operating under weak communication. Existing learning-based methods face two primary ...

The efficacy differences between LLM-based and rule-based chatbots have not been systematically evaluated, with few studies directly comparing the two, and existing meta-analyses have notable ...