AI Agents, LLMs & Economic Growth : Karpathy’s Surprising Predictions

Discover Andrej Karpathy's insights on AI agents, LLMs, and economic growth. Insights on memory, education, and economic ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Frontiers

Brain-Inspired and neurally grounded algorithms in learning and control of advanced robots

In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...

California wants to overhaul high school learning. This school is leading the way

At CART High near Fresno, there is no gum stuck to the floor. The saffron-yellow walls are unmarred by graffiti.
IEEE

Blockchain-Empowered Asynchronous Federated Reinforcement Learning for IoT-Based Traffic Trajectory Prediction

Abstract: Vehicle trajectory prediction plays a crucial role in IoT-based intelligent transportation systems, which can effectively address key issues, such as driving safety and multivehicle ...
Unite.AI

The End of Tabula Rasa: How Pre-Trained World Models are Redefining Reinforcement Learning

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...
IEEE

Aerial Reliable Collaborative Communications for Terrestrial Mobile Users via Evolutionary Multi-Objective Deep Reinforcement Learning

Abstract: Autonomous aerial vehicles (AAVs) have emerged as the potential aerial base stations (BSs) to improve terrestrial communications. However, the limited onboard energy and antenna power of a ...