In Python Physics Lesson 20, learn how to calculate a rod’s moment of inertia using Python! This tutorial breaks down the physics concepts, formulas, and step-by-step Python coding techniques to ...

In Python Physics Lesson #35, we explore how to simulate LRC circuits and understand their behavior over time. This video breaks down the concepts of inductance, resistance, and capacitance, and shows ...

New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...

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 ...

On SWE-Bench Verified, the model achieved a score of 70.6%. This performance is notably competitive when placed alongside significantly larger models; it outpaces DeepSeek-V3.2, which scores 70.2%, ...

Overview The best AI engineer courses 2026 focus on building real, job-ready projects.Combining AI engineering basics with LLM engineering leads to stronger car ...

Hands-on learning is praised as the best way to understand AI internals. The conversation aims to be technical without ...

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.

We present Perception-R1, a scalable RL framework using Group Relative Policy Optimization (GRPO) during MLLM post-training. Key innovations: 🎯 Perceptual Perplexity Analysis: We introduce a novel ...

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 ...

Abstract: Ensuring safety in multiagent reinforcement learning (MARL), particularly when deploying it in real-world applications such as autonomous driving, emerges as a critical challenge. To address ...

Abstract: With extensive pretrained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects, such as ...