Valence Labs’ Post

Amid rapid advances at the intersection of artificial intelligence and the life sciences, NTI | bio and leading experts took important steps toward creating a roadmap for safeguarding AI-enabled tools for engineering living systems from misuse. Learn more about this meeting of the Biosecurity Innovation and Risk Reduction Initiative.👇

Exciting news! Our team has presented a paper at KDD establishing the world's first baseline for the medical Large Language Model. Check out the link for more information. https://lnkd.in/gCzbuHaW #KDD #MedicalAI #LanguageModel

New IEEE Transactions on Molecular, Biological and Multi-Scale Communications article Our article Synchronized Relaying in Molecular Communication: An AI-based Approach using a Mobile Testbed Setup has been accepted for publication in IEEE Transactions on Molecular, Biological and Multi-Scale Communications. In this paper, we propose using a reinforcement learning (RL)- based synchronizer to continually adapt a decoding threshold and detect transmitted synchronization frames in a dynamic molecular communication environment. Link to article: https://lnkd.in/dijxwtUk

🔬 Exciting News for the Biomedical and NLP Community! 🧬 I'm thrilled to share my latest Medium article: "BioGPT: The Innovative Generative Pre-trained Transformer (GPT) for Biomedical Text Understanding and Generation." Discover how BioGPT, powered by Microsoft Research and trained on 15 Million PubMed abstracts, is transforming the way we comprehend and generate biomedical text. Join the conversation and unravel the language of life! Read the article: https://lnkd.in/dsddNepZ #AI #BiomedicalText #Innovation #Research #Medicine #Bioinformatics

I've developed a UNet model for semantic segmentation of nuclei in biomedical images. This project leverages deep learning to accurately identify and segment nuclei cells, aiding in medical research and diagnostics. Check out the project on GitHub: https://lnkd.in/d5k2fW8k #DeepLearning #MachineLearning #BiomedicalEngineering #UNet #DataScience #AI #OpenSource #GitHub

If you've mastered the basics of the perceptron algorithm and would like to take the next step in your exploration, Pan Cretan offers an accessible primer on Adaline (adaptive linear neuron classifier).

What can be determined from a single cell image? Our Human Foundation Model generates 115 unique morphology dimensions from each cell image taken on REM-I. Using self-supervised deep learning that was trained on millions of REM-I generated images, the HFM detects differences In cell morphology without labeled training data. This enables real-time cell characterization & classification of a sample. Learn more here 👉 https://ow.ly/Y83950PGt4k

In addition to the "mainline" force fields (you'll know them because they are named after herbs), researchers in the Open Force Field Initiative are advancing many different directions in force field science, including machine learning potentials.