🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🇫🇷 InstaDeep a eu l’honneur de participer au “Rassemblement des plus grands talents Français de l’intelligence artificielle” au Palais de l’Élysée 🏰 avec le Président Emmanuel Macron et juste avant #vivatech  à Paris Avec plus de 150 employés de grand talent 🌟 InstaDeep

A DNA-based large language model, AgroNT, trained on multiple plant genomes, can accurately predict various molecular phenotypes within plant species, including important crops. InstaDeep Javier Mendoza-Revilla Thomas Pierrot Marie Lopez doi.org/10.1038/s42003…

AgroNT, our 1B parameters foundation model for plants 🌱 genomics 🧬, just got published in communication biology ⭐️

Excited to sponsor and participate in the Machine Learning for Computational Biology Conference #MLCB2024, kicking off today in Seattle! Watch Thomas Pierrot explain how InstaDeep is advancing Generative AI for Genomics! 🧬 📽️ Live here: bit.ly/47hkcVb

👋 Hello World! 🌎 Introducing DeepPCB Pro, our AI-powered design tool for industry-grade PCBs! Fast, precise, and compute-scalable with Google Cloud ☁️ Check it out at deeppcb.ai 👀

Nice to see this launch of a Pro version of DeepPCB, an RL-based system for laying out PCB boards, which runs on Google Cloud. Nice work, Karim Beguir and team! 🎉 The use of RL for many kinds of hardware design and layout problems is accelerating. I remember excitedly comparing

Our Kyber supercomputer makes it to the top 20 H100 GPU compute index! 🔥🚀

🎉 Big news! Our Nucleotide Transformer foundation models for genomics were just published in Nature Methods! 🚀 So proud of this incredible team InstaDeep! ⭐Paper: go.nature.com/3OA7dWr 📕Research briefing: go.nature.com/3BbSPQY

On my way to NeurIPS Conference!✈️ Come chat with the InstaDeep team about our latest work on foundation models for biology. Presenting exciting new research! Also keen to connect with folks using the Nucleotide Transformer and anyone interested in ML for science. 🧬 See you there!

Learning the Language of Protein Structure • A novel approach to protein structure modeling: this study introduces a vector-quantized autoencoder (VQ-AE) to transform continuous protein structures into discrete representations, enabling the use of natural language processing

BulkRNABert: Cancer prognosis from bulk RNA-seq based language models 1. BulkRNABert is the first transformer-based language model pre-trained on bulk RNA-seq data, designed for cancer type classification and survival analysis. It leverages self-supervised learning to create

From breakthroughs to product launches and more, it has been a stellar year at InstaDeep! ✨ Wishing you all happy holidays 🎉 AI is the Force, let's steer it to benefit everyone in 2025! 🌍🌟🚀

Recurring question: So what? It can't be used to train Deep NNs, let alone LLMs. That's true. ES doesn't work well in high dimensional spaces. As it maintains a population, memory requirements (if you are using ES to train Deep NNs) are prohibitive and sample efficiency is not

As the #AIActionSummit kicks off in Paris today, our France Lab is excited to announce its first workshop "Foundations and Advances in Generative AI". 📅 When: February 12–13, 2025 📍 Where: Fondation François Sommer, 62 Rue des Archives, 75003 Paris, France Co-hosted by our

Looking forward to it!

🤖 The action at the #AIActionSummit continues tomorrow with "Foundations and Advances in Generative AI" organized by the #ML Department of MBZUAI. 💬 Attendees, don't miss out on Thomas Pierrot's session on Multi-modal Foundation Models for Biology, 13 February at 10:10 AM .

Excited to share our latest work applying Bayesian Flow Networks (BFNs) to proteomics! We show how BFNs can outperform leading autoregressive, discrete diffusion, and BERT models in protein sequence modeling. 🧵

holy shit AI can now decode the human proteome without any reference genome. a new paper published today presents a new model that can read raw mass spec and generate novel peptide sequences from scratch. no database or priors. just biology. 1/

Introducing ChatNT: The first biological sequence-language model, published in Nature Machine Intelligence ! 🧬🎉 Inspired by vision-language models, ChatNT's architecture combines biological and language foundation models, using Nucleotide Transformer (NT) and Llama to answer questions