what’s the latest?

news blog events research
  • Vishal @ Zebra Project

    Video: our CEO speaks to business leaders at Taylor Vinters' Zebra Project about the need for transparency in Machine Learning.

    read more
  • Mixture Density Networks in GPflow – A Tutorial

    Vincent shares a demonstration tutorial that uses GPFlow, a powerful, flexible framework for probabilistic modelling.

    read more
  • We’re Business Weekly Startup of the Year!

    PROWLER.io tops the hottest list of life science and technology fledglings the Awards has ever witnessed.

    read more

under the hood

The burgeoning AI industry is still focused on perception – recognising images, understanding speech, helping robots touch. But far greater benefits will come when AIs can make good, principled decisions based on those perceptions.


PROWLER.io’s Decision Making systems:
  • are autonomous
  • learn from experience
  • use Probabilistic models that are flexible enough to generalise to novel situations
  • adapt to changing environments by refining their strategies in data-driven ways
  • continually update their environmental models in light of data collected while operating.
  • use Reinforcement Learning (RL) algorithms that can help estimate, account for and even reduce uncertainty
  • can cope with the uncertainties of finite – even small – amounts of data
  • can favour decisions that loop back fresh information to models
  • use Game Theory to operate in multi-agent settings
  • can cooperate – and compete – by inferring what humans and other AIs are trying to do.

our core strategies

  • probabilistic modelling
  • reinforcement learning
  • multi-agent systems

how can our technology be used?

  • games
  • smart cities
  • finance
  • autonomous vehicles
  • drones & robots