AI models are trained on massive amounts of data. But that training doesn’t do much good without what’s known as “reinforcement learning,” a process that involves human experts teaching models the ...

Minimax M2.5 lists $0.30 per million input tokens and $2.40 output on the lightning tier, helping builders plan predictable AI spend.

Negative reinforcement has a bad reputation. Here’s what it really means, and why it can be surprisingly helpful.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

An intensive programme on reinforcement learning, brought together 60 international participants including students, researchers and industry practitioners to the Sungai Long campus of Universiti ...

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

In this tutorial, we explore advanced applications of Stable-Baselines3 in reinforcement learning. We design a fully functional, custom trading environment, integrate multiple algorithms such as PPO ...

Abstract: Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across ...