Reinforcement learning (RL) is one of the most exciting prospects that a data scientist may add to their resume today. Many IT companies, such as Google, Amazon, Microsoft, IBM, Sony, and others, have established research centres and AI labs in India throughout the years. RL has been at the heart of some of the most significant breakthroughs in recent years. Let’s take a look at some of the prominent companies that are active in RL.
Amazon’s Recommendation Systems
According to research, systems that apply reinforcement learning can change recommendations based on user feedback continuously. Deep learning may provide mathematical representations of a product, as well as consumer interest and satisfaction. Over time, the reinforcement learning agent can adapt the material for each individual based on their tastes, maximising the reward in the long run. In recent years, deep reinforcement learning has become more popular for use cases, including push alerts, faster video loading by pre-fetching content, and offering product suggestions. To understand more about reinforcement learning in action, go to the Amazon Sagemaker notebook on recommendation systems.
The researchers at Google Brain and Alphabet’s DeepMind propose Adaptive Behavior Policy Sharing (ABPS), an algorithm that allows the sharing of experience adaptively selected from a pool of AI agents, and a framework called Universal Value Function Approximators (UVFA) that simultaneously learns directed exploration policies with the same AI. The teams say that ABPS outperforms Atari games in a variety of ways, including a 25% reduction in variance on top agents.
Microsoft & RL
The Reinforcement Learning (RL) Open Source Fest was just announced by Microsoft. It’s a global online programme that introduces students to open source RL programmes and software development while working alongside Microsoft Research NYC’s Real World RL team of researchers, data scientists, and engineers. Further, the Microsoft Research team developed and introduced Vowpal Wabbit (VW), an open-source machine learning package.
Amazon’s Energy Smart Grids
For applications like data centre cooling and select smart grid applications, reinforcement learning has outperformed advanced control technologies normally employed for energy optimisation. In Amazon research, deep learning is being utilised to create mathematical representations of difficult thermodynamic equations in this case. Here, the reinforcement learning agent learns the proper behaviours to take (such as which systems to turn on and off) over the period of days, weeks, months, and years by pursuing reward maximisation. 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 create AI bots that can learn to accomplish tasks in an unknown 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-supervised RL are all being studied at Facebook.
Deep reinforcement learning may be used to teach robots in warehouses and factories how to pick up and move goods. You can now get hands-on with RL, explore, and learn through autonomous driving with AWS DeepRacer. In the cloud-based 3D racing simulator, you can get started with the virtual car and tracks. As per Amazon, the goal is to make it faster to experiment with and manage robotic workloads, from perception to controls to optimisation, and to construct end-to-end solutions without having to recreate them each time.
In parallel, IBM Research has a list of RL-related research contributions – IBM’s artificial intelligence for the virtual home, RL for 5G, and more. Likewise, RL has been successfully implemented in a variety of fields, including AlphaZero, a system that learned to master the games of chess, Go, and Shogi. Identically, Salesforce has employed reinforcement learning to create a simulation and data-driven solution for tax research. Similarly, the RL research list is growing.
As we move forward
The recent advances indicate how India has benefitted numerous IT companies in their efforts to establish competence in cutting-edge technology such as AI and RL. India is preferred for creating AI laboratories and research centres due to its vibrant ecosystem and a big pool of expertise. In India, there is a rising number of organisations and startups working on the subject of machine learning and RL. In the RL community, this growth has sparked new research avenues and reignited existing ones. So, yes, it is true that IT businesses are investing more in reinforcement learning research.