InstaDeep is pleased to reaffirm its support for AI Expo Africa for the third consecutive year, as Silver sponsors of the event. The continent-wide, virtual Expo is taking place on 7-9 September, and is the largest business-focused AI, Robotic Process Automation (RPA) and Fourth Industrial Revolution (4IR) trade event in the region. Over 5,000 delegates… Read more »
InstaDeep is delighted to announce it is a Gold sponsor of the 2021 Biologics UK conference happening in London on 6-8 September 2021. The event, billed as “Europe’s Premier Meeting for Biologics R&D”, is dedicated to protein and antibody engineering and development strategies, advancing bispecifics to the clinic and therapeutic use, bioanalysis, and vaccine development. … Read more »
InstaDeep is pleased to announce its Gold sponsorship of the forthcoming École Polytechnique Fédérale de Lausanne’s (EPFL) Applied Machine Learning Days (AMLD), taking place between 2-4 September 2021. The online event is the first time EPFL have hosted an event in Africa, and will include three days of talks, tutorials and workshops on Machine Learning… Read more »
InstaDeep’s Nicolás Lopez Carranza and Marcin J. Skwark recently presented the DeepChain protein design platform at the highly prestigious ISMB/ECCP 2021 conference. Speaking to a large virtual audience of expert bioinformaticians and computational biologists, Nicolás (DeepChain Lead) and Marcin (Bioinformatics Lead) explained how DeepChain helps life science researchers design and optimize protein-protein interactions, and how… Read more »
InstaDeep co-founder Zohra Slim has been profiled in a new article about leading female founders by the NVIDIA Inception programme. Zohra, a self-taught software, web and design expert, has always championed women in tech and AI, leading the way for other women to work in traditionally under-represented, male-dominated areas and roles. She co-founded InstaDeep in… Read more »
This July, DeepChain lead, Nicolás Lopez Carranza, was invited to speak at this year’s IA Congreso (AI Congress) – the premier event for AI in Latin America. Representing InstaDeep, Nicolás presented on the topic of “AI-first Protein Design”, as part of a top line up of experienced AI professionals from the region and beyond. The… Read more »
Today, InstaDeep introduces Mava: a research framework specifically designed for building scalable, high-quality Multi-Agent Reinforcement Learning (MARL) systems. Mava provides useful components, abstractions, utilities, and tools for MARL and allows for easy scaling with multi-process system training and execution while providing a high level of flexibility and composability. To support the field of single-agent reinforcement… Read more »
TUNIS, TUNISIA, 22.06.2021: InstaDeep and iCompass announced Tuesday that the two AI companies would make TunBERT, their world-first Natural Language Processing (NLP) model for the underrepresented Tunisian dialect, available free and open-source to help spur innovation in Tunisia’s already rapidly growing AI and tech ecosystem. Tunisia’s tech ecosystem has emerged as an economic and technological… Read more »
For Africa Day 2021, The Africa I Know (TAIK) announced its inaugural list of Africa’s most inspirational leaders from across the STEM industries, “The TAIK 54 Most Inspiring Africans.” To InstaDeep’s great honour, CEO and Co-Founder Karim Beguir featured on the prominent list. TAIK compiled the list as part of its mission to positively change… Read more »
Residual networks (ResNets) have displayed impressive results in pattern recognition and, recently, have motivated the neural ordinary differential equations (neural ODE) architecture which garnered a lot of interest in the Machine Learning community. A widely established claim is that the Neural ODE is the limit of ResNets as the number of layers increases. A collaboration effort between InstaDeep and the University of Oxford challenges this claim by investigating the properties of weights trained by stochastic gradient descent and their scaling with network depth through detailed numerical experiments.
