Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...
Until now, AI services based on large language models (LLMs) have mostly relied on expensive data center GPUs. This has ...
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.
Objective To examine whether a multicomponent commercial fitness app with very small (‘micro’) financial incentives (FI) ...
Abstract: The study focuses on discerning between human and AI-generated essays, highlighting the ethical implications of AI in academia. It employs various algorithms like logistic regression, ...
Machine translators have made it easier than ever to create error-plagued Wikipedia articles in obscure languages. What happens when AI models get trained on junk pages? When Kenneth Wehr started ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Modeling AI systems on dual-process theories of human cognition can improve their ability to flexibly handle diverse tasks. With the advent of large language models (LLMs), two schools of thought have ...
What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...
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