This year’s submissions reflect the depth and breadth of InstaDeep’s research efforts, ranging from groundbreaking developments in Decision-Making AI to breakthroughs in Machine Learning for Biology.
Articles
Scalable Reinforcement Learning on Cloud TPU
Instadeep used reinforcement learning on Cloud TPUs to improve DeepPCB, its AI-driven Printed Circuit Board (PCB) design product. Authors: Armand Picard, Software Engineer Donal Byrne, Senior Research Engineer Alexandre Laterre, Research Lead Vaibhav Singh, Product Manager, Google Cloud TPU The long-term goal of Artificial Intelligence (AI) is to solve complex real-life problems. On the path… Read more »
InstaDeep open-sources the Nucleotide Transformers, its collection of genomics Language Models, to HuggingFace
InstaDeep Research is pleased to announce the open-sourcing of its Nucleotide Transformer on the HuggingFace platform. The Nucleotide Transformer project introduces a collection of four DNA large language models, with parameter counts ranging between 500M and 2.5B, which were developed in collaboration with NVIDIA and the Technical University of Munich. As part of this work,… Read more »
InstaDeep Research team continues success at ICLR with record four publications, hosts exclusive preview screening of new AI documentary
InstaDeep’s research team is off to a great start in 2023 with a new record of four confirmed papers: two papers on the main track, including a spotlight; and two workshop papers, including an oral presentation. ICLR, the globally respected International Conference on Learning Representations, is being held at the Kigali Convention Centre in Rwanda… Read more »
New research from InstaDeep, NVIDIA and the Technical University of Munich beats expectations, provides new insights into genomics research
InstaDeep is pleased to announce a new collaboration with the Technical University of Munich and NVIDIA, using the UK-based Cambridge-1 supercomputer to train large language models (LLMs) on diverse genomic datasets to examine the impact of model scale and data diversity on downstream task performance. As part of the work, multiple foundation models for genomics… Read more »
InstaDeep and Google Cloud are developing the next generation of Genomics Language Models for sustainable agriculture
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 »
InstaDeep and Imperial College present three joint papers on Quality-Diversity at GECCO
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, Imperial College London and Sorbonne joint research accepted for ICLR 2022 workshop
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 launches dedicated Quantum Machine Learning team, as first QML research paper is published in Nature Machine Intelligence
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 »
InstaDeep and Oxford University Research Collaboration Accepted to ICLR
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 »