Goto

Collaborating Authors

safety gym


8 Best Alternatives To OpenAI Safety Gym

#artificialintelligence

Two years ago, Open AI released Safety Gym, a suite of environments and tools for measuring progress towards reinforcement learning agents that respect safety constraints while training. Safety Gym has use cases across the reinforcement learning ecosystem. The open-source release is available on GitHub, where researchers and developers can get started with just a few lines of code. In this article, we will explore some of the alternative environments, tools and libraries for researchers to train machine learning models. AI Safety Gridworlds is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents.


OpenAI Open Sourced this Framework to Improve Safety in Reinforcement Learning Programs

#artificialintelligence

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Safety is one of the emerging concerns in deep learning systems. In the context of deep learning systems, safety is related to building agents that respect safety dynamics in a given environment.


OpenAI Open Sources Safety Gym to Improve Safety in Reinforcement Learning Agents

#artificialintelligence

Safety is one of the emerging concerns in deep learning systems. In the context of deep learning systems, safety is related to building agents that respect safety dynamics in a given environment. In many cases such as supervised learning, safety is modeled as part of the training datasets. However, other methods such as reinforcement learning require agents to master the dynamics of the environments by experimenting with it which introduces its own set of safety concerns. To address some of these challenges, OpenAI has recently open sourced Safety Gym, a suite of environments and tools for measuring progress towards reinforcement learning agents that respect safety constraints while training.


What Is Constrained Reinforcement Learning And How Can One Build Systems Around It

#artificialintelligence

One of the most important innovations in the present era for the development of highly-advanced AI systems has been the introduction of Reinforcement Learning (RL). It has the potential to solve complex decision-making problems. It generally follows a "trial and error" method to learn optimal policies of a given problem. It has been used to achieve superhuman performance in competitive strategy games, including Go, Starcraft, Dota, among others. Despite the promise shown by reinforcement algorithms in many decision-making problems, there are few glitches and challenges, which still need to be addressed.


DeepMind gets good at games (and choosing them) – plus more bits and bytes from the world of machine learning

#artificialintelligence

Roundup If you can't get enough of machine learning news then here's a roundup of extra tidbits to keep your addiction ticking away. Read on to learn more about how DeepMind is helping Google's Play Store, and a new virtual environment to train agents safely from OpenAI. An AI recommendation system for the Google Play Store: Deepmind are helping Android users find new apps in the Google Play Store with the help of machine learning. "We started collaborating with the Play store to help develop and improve systems that determine the relevance of an app with respect to the user," the London-based lab said this week. Engineers built a model known as a candidate generator.


OpenAI releases Safety Gym for reinforcement learning

#artificialintelligence

While much work in data science to date has focused on algorithmic scale and sophistication, safety -- that is, safeguards against harm -- is a domain no less worth pursuing. This is particularly true in applications like self-driving vehicles, where a machine learning system's poor judgement might contribute to an accident. That's why firms like Intel's Mobileye and Nvidia have proposed frameworks to guarantee safe and logical decision-making, and it's why OpenAI -- the San Francisco-based research firm cofounded by CTO Greg Brockman, chief scientist Ilya Sutskever, and others -- today released Safety Gym. OpenAI describes it as a suite of tools for developing AI that respects safety constraints while training, and for comparing the "safety" of algorithms and the extent to which those algorithms avoid mistakes while learning. Safety Gym is designed for reinforcement learning agents, or AI that's progressively spurred toward goals via rewards (or punishments).