A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...

ST’s VL53L5CX is a very small 8×8 grid ranging sensor that can perform distance measurements at a distance of up to 4 meters. In a recent video,[Henrique Ferrolho] demonstrated that ...

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 ...

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 ...

Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or fall apart. Instead of training LLMs ...

Abstract: This paper presents a simulation-based benchmarking analysis of three reinforcement learning (RL) algorithms—Soft Actor-Critic (SAC), Deep Q-Network (DQN), and Proximal Policy Optimization ...

Wind turbine control systems have evolved significantly over the past decades, moving from simple classical controllers to sophisticated artificial intelligence-based strategies. Early utility-scale ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

portfolio-optimization-rl/ ├── src/ │ ├── envs/ │ │ └── portfolio_env.py # Portfolio optimization environments │ ├── agents/ │ │ └── rl_agents.py # RL agent implementations │ └── config.py # ...

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling by designing the algorithms and rules that govern the learning process.