Reinforcement Learning

Artificial intelligence is revolutionary in all the major use cases and applications we encounter daily. One such area revolves around a lot of audio and visual media. Think about all the AI-powered apps that can generate...
Large Language Models (LLMs) have demonstrated incredible capabilities in recent times. Learning from massive amounts of data, these models have been performing tasks with amazing applications, including human-like textual content generation, question-answering, code completion, text summarization,...

Meet MACTA: An Open-Sourced Multi-Agent Reinforcement Learning Approach for Cache Timing Attacks and Detection

We are deluged with multiple forms of data. Be it data from a financial sector, healthcare, educational sector, or an organization. Privacy and security...

UC Berkeley Researchers Propose FastRLAP: A System for Learning High-Speed Driving via Deep RL (Reinforcement Learning) and Autonomous Practicing

Researchers from the University of California, Berkeley, have developed a system called FastrLap that uses machine learning to teach autonomous vehicles to drive aggressively...

5 Reasons Why Large Language Models (LLMs) Like ChatGPT Use Reinforcement Learning Instead of Supervised Learning for Finetuning

With the huge success of Generative Artificial Intelligence in the past few months, Large Language Models are continuously advancing and improving. These models are...

Computer Vision Meets 🫠 Reinforcement Learning: This AI Research Shows that Reward Optimization is a Viable Option to Optimize a Variety of Computer Vision...

Not how effectively the model maximizes the training goal, but rather how well the predictions are matched with the task risk, i.e., the model's...

New AI Research From Anthropic Shows That Simple Prompting Approaches Can Help Large Language Models (LLMs) Trained With Reinforcement Learning From Human Feedback (RLHF)...

Big language models show negative social prejudices, which can occasionally grow worse with larger models. Scaling model size can improve model performance on a...

A New Deep Reinforcement Learning (DRL) Framework can React to Attackers in a Simulated Environment and Block 95% of Cyberattacks Before They Escalate

Cybersecurity defenders must dynamically adapt their techniques and tactics as technology develops and the level of complexity in a system surges. As machine learning...

Tracking Odor Plumes With AI Agents Using A Deep Reinforcement Learning Model

The extraordinary talents of animals have long served as a source of inspiration for scientists and engineers who have worked to reverse engineer or...

A New Transformer Based Reinforcement Learning Agent Called ‘AdA’ Inhabits a Rich 3D World and Can Rapidly Adapt to Tasks It Has Never Seen...

It has always been astounding how quickly humans can adjust to their environment. Artificial intelligence agents have been developed over many years to replicate...

Can Reinforcement Learning Learn Everything?

The latest paper (“Mastering Diverse Domains through World Models”) from Deepmind talks about an RL agent that can master diverse domains through World Models...

Google AI Introduces Robotics Transformer 1 (RT-1), A Multi-Task Model That Tokenizes Robot Inputs And Outputs Actions To Enable Efficient Inference At Runtime

The primary source of the most recent technological advancements we see today in numerous machine learning subfields is the knowledge transfer that occurs from...

Google AI Introduces Reincarnating Reinforcement Learning RL That Reuses Prior Computation to Accelerate Progress

Reinforcement Learning RL, which falls under the Machine Learning umbrella, focuses on training intelligent agents to make decisions by using related experiences. This could...

Latest Robotics Research Releases ‘Hora’: A Single Policy Capable of Rotating Diverse Objects With a Dexterous Robot Hand

In this article, UC Berkeley and Meta researchers demonstrate how an adaptive controller can be trained to rotate various objects over the z-axis using...

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