The future of AI for decision-making.

In their latest blog posts, our experts explain where we are travelling to - and where we are coming from.

The future of AI for decision-making.

In their latest blog posts, our experts explain where we are travelling to - and where we are coming from.

Marginal Likelihood

Training the machines with marginal likelihood

Our NeurIPS paper boosts machine learning performance using a probabilistic approach.

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Scalable Ai

The secret to scalable reinforcement learning

Find out how our NeurIPS 2018 paper solves multiple RL problems, simultaneously.

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Five key papers from NeurIPS 2018

Five key papers from NeurIPS 2018

The NeurIPS 2018 conference accepted eight research papers from PROWLER.io and the world-leading institutions and researchers we regularly collaborate with.

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A Dynamic Summit - Special report

Vishal Chatrath, CEO and Co-founder of PROWLER.io on a ground-breaking two days in Cambridge

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Decision time for Decision-Making - A preview

Vishal Chatrath on why the Decision Summit comes at a crucial time for Artificial Intelligence.

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Computer says you need an umbrella

The day-to-day decisions we make might appear simple, even trivial. James Hensman, Head of Probabilistic Modelling at PROWLER.io, unravels some of the secrets of AI for decision making.

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Society of AIs

Enrique and Sofia discuss how the Multi-Agent Systems team here use Game Theory and Machine Learning to tackle problems like managing taxi fleets.

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Decisions, decisions - how AI solutions can triumph over the human mind

Aleksi and Neil explain how reinforcement learning makes decisions in the real world.

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Debuggable Tensor Flow

A guide to bugs, where to find them and what to do with them

PROWLER.io's Wei Yi makes debugging TensorFlow code less of a chore.

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The agents are multiplying - how AI should (and can) cope

David Mguni shows how Reinforcement Learning and Multi-agent Systems can come together to fix previously insoluble problems.

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