Cambridge-based startup PROWLER.io has secured £1.5 million in seed investment to fund development of its sophisticated decision-making AI engine designed to revolutionise autonomous system design.
PROWLER.io’s researchers and engineers are developing revolutionary next-generation machine learning algorithms that will massively improve the quality and development speed of AI decision making systems. This £1.5 million investment will enable PROWLER.io to build a prototype version of its platform with select partners.
Initially the company will target games developers, with numerous other sectors to follow. Starting in the gaming industry, PROWLER.io’s technology will enable superior decision-making and much more natural in-game behaviour from non-player characters (NPCs) through AI, revolutionising current games industry techniques and thinking.
NPC behaviour is currently still controlled by hand-crafted decision rules, often leading to unnatural and repetitive gameplay. Using machine learning instead enables improved testing and an enhanced gameplay experience, as well as speeding development and making it far less cumbersome.
In addition to gaming, PROWLER.io is looking towards autonomous vehicles (cars, drones, etc.), smart city simulations and robotics as additional fields which can benefit from the application of bots which are autonomous, tunable and self-learning. The development path for those sectors is similar to that required by gaming and therefore the research is easily transferable to many other use cases and commercial opportunities. Analysts predict that these industries will reach a combined total value of more than $1 trillion by 2025.
PROWLER.io’s bots use “reinforcement learning,” a speciality of machine learning which enables long chains of complex decisions to be made autonomously. The technology powers highly artificially intelligent bots which learn and adapt to changing environments – making NPCs act much more naturally in an environment being destroyed in a video game gun battle, or enabling an autonomous vehicle to deal intelligently with the constantly changing road and traffic conditions around it.
Vishal Chatrath, CEO of PROWLER.io, comments: “Gaming is a 100-billion-dollar industry which is still reliant on hugely complex, inflexible and expensive hand-made decision rules. As well as being extremely labour-intensive to build, they also deliver a substandard experience for gamers: NPCs don’t evolve as the game environment changes, for example. With so many games now relying on extended playing time to generate revenue, it’s more important than ever for developers that games don’t become boring or repetitive. Sophisticated AI and machine learning is the best way to create and deliver that experience, and can reduce cost at the same time. It’s a win-win.”
Chatrath continues: “Looking at other applications and industries, the use of next-generation machine learning algorithms greatly reduces the cost and difficulty of developing highly intelligent AI bots, improving safety and utility in all sorts of applications and saving billions of dollars in development costs in the process.”
Eileen Burbidge, partner at Passion Capital, comments: “We invested in PROWLER.io because we see near limitless use cases for next-generation machine and reinforcement learning to revolutionise industries. From smart city infrastructure to agriculture to drones, in the very near future powerful artificial intelligence is going to change the world we live in for the better. The huge potential of the technology combined with the calibre of the PROWLER.io team make this a very exciting proposition.”
“Clearly there are very compelling investment opportunities around reinforcement learning, which is one of the most active research areas in AI and machine learning,” said Hermann Hauser, co-founder and partner at Amadeus Capital. “As a research-led start-up, PROWLER.io is at the very forefront of this emerging technology and is leading the charge to apply reinforcement learning to many current and future challenges. This state-of-the-art technology will continue to develop in the coming years and there are certain to be important applications that we haven’t yet considered.”
Zach Tan, director at Infocomm Investments’ London office, comments: “We believe that the gaming environment and AI research exist symbiotically: by applying them together, the gaming environment becomes more realistic and that in turn becomes a fantastic platform for furthering research into artificial intelligence. Smart city simulations are comparable to a gaming environment and this symbiosis is pushing the technology frontier further and further forward. There’s a huge market opportunity in Asia for these types of technologies, for example, in applications for Singapore’s Smart Nation programme.”
PROWLER.io’s advisory board is made up of some of the world’s foremost experts in machine learning and includes Professor Carl Rasmussen, Professor of Information Engineering, Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge; Professor Kee-Eung Kim, Associate Professor, Department of Computer Science, Korea Advanced Institute of Science and Technology; and Dr. Marc Deisenroth, Lecturer in Statistical Machine Learning at the Department of Computing, Imperial College London.
Meet the PROWLER.io team
PROWLER.io CEO and co-founder Vishal Chatrath was the first employee and management team member of VocalIQ, a speech-related AI company which was acquired by Apple in 2015. Prior to VocalIQ he founded Chleon Automotive, an auto telematics company and also led Nokia’s automotive team which developed MirrorLink, an open technology standard for connecting smartphones and cars.
CTO and co-founder Dr. Dongho Kim is an expert in reinforcement learning, POMDP and statistical dialog systems. Kim first teamed up with Chatrath at VocalIQ, where he formed the core of the machine learning team. Dongho is a former post-doctoral research associate in Cambridge University’s Engineering Department. He obtained his PhD in AI at KAIST in 2011.
The third co-founder is Aleksi Tukiainen, a former master’s student at the University of Cambridge’s Department of Engineering where he was studying machine learning methods and control systems. Tukiainen has been designing and managing engineering projects for a number of years, working on collaboration platforms, solar vehicle design as well as self-learning robots.