Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

As social media becomes increasingly reliant on algorithmic feeds, creators are navigating a new normal: Just because you post something doesn’t mean your followers will see it. “I think that 2025 was ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the importance of performing ...

TikTok's owner, ByteDance, is expected to sell its US business to a buyer consortium. The new owners will retrain TikTok's content-recommendation algorithm, the White House said. TikTok staffers and ...

Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct strengths and limitations. SFT is ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

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Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.

Philadelphia, April 17, 2025 – Researchers from Children’s Hospital of Philadelphia (CHOP) and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) have successfully ...