At Arena, we believe that the next leap forward in applied AI lies in active learning systems and techniques like reinforcement learning. These systems are ‘curious’ – they continuously try new things in the world, making them better at adapting to and operating in a fast-changing, complex world. Most AI today is passive. It learns by looking at billions of examples of labeled data, like tagged faces. Active learning systems improve through interactions with their environment – think Neo from The Matrix learning Kung Fu by fighting Morpheus over and over in a virtual dojo. Arena builds simulations and active learning agents that can safely and quickly learn new tasks by exploring a real or simulated environment. Similar techniques have been used in research labs to beat humans in games, from Go to StarCraft to Dota. We’re excited to bring this game-playing AI out of the lab and into the real world by creating simulations and writing software to let AI explore and interact with real environments.
Today, we are focused on pricing. We use active learning agents (e.g., Gaussian Processes, RL) to find the optimal products and discounts that a company should offer to a particular customer at a given time. Over the past year we have raced our agents against people and existing software, outperforming both, resulting in sizeable increases in revenue for our customers. We are now building a product to enable big and small consumer companies to deploy better product assortment & pricing strategies, automatically. Pricing is just the start. Our long-term mission is to create active learning agents that can learn to operate effectively and safely in any new, real-world environment.
We were inspired by Theodore Roosevelt’s Man in the arena speech, which honors the value of committing oneself to the pursuit of a bold and exciting mission. At our core, we value:
Real world > Lab. Despite the many degrees on our team, we focus on solving real world problems instead of over-applying theory. We show measurable results, and we get paid when we truly move the needle.
Speed > Perfection. We value getting something from 0 to 1 fast, and then iterating on it. We believe that the more we ship, the faster we learn. And if there’s room for improvement, we’re transparent about it.
Trust > Procedure. If you join us, we will trust you and ask that you trust us. Our expectations will be high, but you can also expect a lot from us in return. Micro-management and hierarchies are not our way.
Form + Function. We strive to build products that move us on both a rational and an emotional level and truly understand the user.
Pride – Ego. We started Arena with the best people we know and we want it to reflect the best work each of us has ever done. That’s why we shed our egos and approach problems from first principles. True competence is quiet and humble.
Kindness > Niceness. We are motivated by understanding and supporting others, not by maintaining a facade. We know that ‘being in the arena’ can be hard, and authentic support is critical to growth.
Harvard, Cornell Tech, McKinsey, SAB Miller, SecurityScorecard, Bloomberg
We founded Arena in March 2019, and are looking to add machine learning scientists and engineers to our team in New York City. Our customers are global, and we travel to many countries to spend time with our users. As a young company, our culture is evolving and we’re excited for you to shape it with us. We prioritize diverse thoughts and backgrounds, so if our mission speaks to you, and the core values sound like you, we’d love for you to join us in the arena.