The optimizer did its job. Then engineering reality hit.

Unlocking the full value of parallel compute through batch sampling

Secondmind Active Learning explained

Is your AI an engineering partner - or just more friction?

The power of unification: simplifying combinatorial design in automotive engineering

Three-cylinder engine: Designing for robustness from day one

Engineering AI for the physical world

When advanced machine learning meets set-based design

On our minds: Women in engineering

Less simulating, more solving: AI-powered design

A new era for design space exploration

Tackling e-powertrain calibration complexity with advanced machine learning

Unlocking more efficient design with Secondmind open source tools

Applying generative AI to solve complex automotive engineering problems

Introducing compiler optimizations for memory-safe & democratized modelling

Mixture-model likelihoods for outlier detection

Achieving sustainability through machine learning

GPflux: A Library for Deep Gaussian Processes

Trieste: our first open-source toolbox

What is Stochastic Network Control?

What is a Gaussian process?

Sparse GPs: approximate the posterior, not the model

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

Cloud-based ML: the catalyst transforming automotive product development