You are what you eat. We’ve all been told this, but the truth is what we eat is often more complex than we are – genetically at least. Take a grain of rice. The plant that produces rice has 40,000 to 50,000 genes, double that of humans, yet we know far more about the composition… Read more »
Each year, the Genetic and Evolutionary Computation Conference (GECCO) gathers the leading global experts in the domain of genetic and evolutionary computing. This year, InstaDeep’s research team presented two main conference papers and one workshop paper at the event, which took place in Boston, MA between 9-13 July. The three works result from a close… Read more »
InstaDeep proudly announces that a co-authored research paper on Diversity Policy Gradient for Sample Efficient Quality-Diversity Optimization has been accepted by ICLR and will be presented at a workshop during the week-long event. This latest acceptance – on the tenth anniversary of ICLR – continues InstaDeep’s track record of producing high quality research in collaboration… Read more »
InstaDeep is pleased to announce the formation of a new Quantum Machine Learning (QML) team within the company’s well-established research department. The announcement coincides with the publication of the “Autoregressive neural-network wavefunctions for ab initio quantum chemistry” research paper in the leading science journal, Nature Machine Intelligence. Publication in Nature Machine Intelligence The paper was… Read more »
This research was authored by Scott Cameron at the University of Oxford and InstaDeep, in collaboration with Prof Stephen Roberts, Dr Arnu Pretorius of InstaDeep and Tyron Cameron of Discovery Insure South Africa. It is Cameron’s first publication from his PhD, which is funded by InstaDeep. Stochastic differential equations (SDEs) have been consistently used across… Read more »
Early Warning System combines Spike protein structural modeling with artificial intelligence (AI) to detect and monitor high-risk SARS-CoV-2 variants, identifying >90% of WHO-designated variants on average two months prior to officially receiving the designation Study introduces a new method of combining publicly available SARS-CoV-2 sequence information with predictive analytics to effectively detect and monitor potential… Read more »
Our collaboration with Google AI, “On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa”, describes an early detection system for desert locust outbreaks across the African continent. This research will be presented at two NeurIPS 2021 machine learning conference workshops: Artificial Intelligence for Humanitarian Assistance and Disaster Response (AI+HADR) and Machine… Read more »
