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Preview all research reports and prototypes

Our research focuses on emerging data and machine learning-enabled trends. Accompanying the reports are working prototypes that exhibit the capabilities of the algorithm and offer detailed technical advice on its practical application.

Multi-Task Learning

In our latest report, we focus on multi-task learning, a new approach to machine learning that allows algorithms to master tasks in parallel.

Semantic recommendations

In this report, we show how using the semantic content of items can help solve common recommendation pitfalls such as the cold start problem, and open up new product possibilities.


In this report, we show how to make models interpretable without sacrificing their capabilities or accuracy.

Probabilistic programming

Here, we show how to use probabilistic programming and Bayesian inference to easily build tools that make better predictions for more effective decision making.


Learn how to use deep learning and embeddings to make text computable for a variety of business applications and products.

Deep learning: Image analysis

This report explores the history and current state of deep learning, explains how to apply it, and predicts future developments.

Probabilistic methods for realtime streams

Here, we explore probabilistic methods that offer highly efficient models for extracting value from streams of data as they are generated.

Natural language generation

In this report, we look at how machine systems can turn highly structured data into human language narrative.

Read the Fast Forward Labs blog


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