News

• 03 Feb 2020

When G-Research was founded in 2001, the tools to perform large-scale data science were few and far between.  Fewer still were the number of open-source tools available to perform large-scale data science. At the time, it made perfect sense for G-Research to turn to the available 3rd-party technologies and in-house development to fill the gap. […]

• 30 Jan 2020

Charity and community have always been key pillars of G-Research. We’re proud to provide opportunities for our team to volunteer at a wide range of organisations, from STEMettes to Action Tutoring, and we have long supported our staff’s fundraising endeavours by doubling any donations they receive. We are an organisation, however, that never rests on […]

• 21 Jan 2020

Andrew S – Quantitative Researcher Random deep neural networks are biased towards simple functions Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd Deep neural networks often have more parameters than datapoints in their training set, so one might naively expect them to be very overfit, and have poor generalisation properties.  They are fully capable of learning randomly-labelled […]

• 16 Jan 2020

Data is at the core of everything we do at G-Research, and metrics are no different. We’ve been running a reasonably sized OpenTSDB installation for 4 years now, and are putting metrics from applications, systems and processes in it at a fair rate (currently about 11 billion points a day). We’ve scaled our cluster over […]

• 14 Jan 2020

Tackling maths problems in creative ways. Do you think you have the solution?

• 07 Jan 2020

An oft-repeated maxim in programming is "if you think it's a compiler bug, it's not a compiler bug".

• 18 Dec 2019

Tackling maths problems in creative ways. Do you think you have the solution?

• 03 Dec 2019

We were building a service that receives market data and caches it for multiple clients to access.

• 28 Nov 2019

The latest blog in our series from G-Research's CTO, Chris Goddard.