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Reinforcement learning has become a priority for tech companies.
Reinforcement Learning (RL) is one of the most exciting prospects a data scientist can include on their resume today. Many IT companies like Google, Amazon, Microsoft, IBM, Sony and others have established artificial intelligence research centers and laboratories in India over the years, and RL has been at the center of some of the major advances in recent years. Let’s take a look at some of the featured companies that are active in RL.
Amazon’s Recommendation Systems
Research has shown that systems that employ reinforcement learning can continually change recommendations based on user feedback. Deep learning can provide mathematical representations of a product as well as consumer interest and satisfaction. Over time, the reinforcement learning agent can customize the material for each individual. based on your tastes and maximize the long term reward. In recent years, deep reinforcement learning has become increasingly popular for use cases including push notifications, faster video loading by pre-scanning content, and offering product suggestions. in action go to the Amazon Sagemaker notebook on recommendation systems.
Google Brain Researchers and DeepMind Alphabet propose an algorithm to exchange the adaptive behavioral guidelines (ABP), an algorithm that enables adapted experience to share from a group of AI agents and a framework called Universal Value Function Discovery ( UVFA) which at the same time experienced political exploration with the same AI. The device says ABPS ATARI games surpasses a variety of forms, including a reduction of 25% in the variance in the best agents.
Microsoft & RL
Microsoft just announced the Reinforcement Learning (RL) Open Source Fest, a global online program that introduces students to RL’s open source programs and software development while working with the team of researchers, data scientists, and engineers at Real World RL from Microsoft Research NYC. In addition, Microsoft’s research team developed and implemented Vowpal Wabbit (VW), an open source machine learning package.
Amazon’s Energy Smart Grids
In applications such as data center cooling and select smart grid applications, reinforcement learning has overtaken advanced control technologies typically used to optimize performance. In this case, Amazon research uses deep learning to create mathematical representations of difficult thermodynamic equations. The learning agent learns the appropriate behaviors (e.g., which systems to turn on and off) over a period of days, weeks, months, and years in an effort to maximize the reward. Check out the Amazon Sagemaker notebook for energy use cases to get hands-on with practical reinforcement learning applications.
Facebook on RL
Similarly, Facebook’s Reinforcement Learning (RL) researchers are developing artificial intelligence bots that can learn to perform tasks in an unfamiliar environment over time by interacting with it. RL algorithms combining inputs from different sources (e.g., language), RL agents integrating real-world constraints (e.g. fairness, privacy and security), RL agents for human interaction, multi-agent RL and self-monitored RL are investigated on Facebook.
Deep reinforcement learning can be used to teach robots in warehouses and factories to pick up and move goods. Now you can experience RL in a practical way, explore and learn autonomous driving with AWS DeepRacer. In the cloud-based 3D racing simulator, you can get started with the virtual car and the tracks. According to Amazon, the goal is to make it faster to experiment and manage robotic workloads, from insights to controls to optimization, and developing end-to-end solutions without having to rebuild them every time.
In parallel, IBM Research has a list of research papers on RL: IBM Artificial Intelligence for Virtual Home, RL for 5G, and more. Likewise, RL has been successfully implemented in a variety of areas, including AlphaZero, a system that has learned to master the games of chess, go and shogi. Similarly, Salesforce has used reinforcement learning to create a simulation and data-driven solution for tax investigation. RL’s research list is also growing.
As we move forward
Recent developments show how India has helped numerous IT companies in their efforts to build proficiency in cutting edge technologies such as AI and RL. India is preferred for setting up AI laboratories and research centers because of its dynamic ecosystem and rich expertise. In India, there are a growing number of organizations and startups dealing with machine learning and RL. In the RL community, this growth has opened up new avenues of research and revitalized existing ones. So it is true that IT companies are investing more in research on reinforcement learning.