Aropha’s Post

Skip the in-lab testing with ArophaAI. Our machine learning program will accurately predict the biodegradability of your product without costly traditional lab testing. We have both a free and a paid version to best suit your needs. Learn more: https://hubs.li/Q02yRBFc0

To really understand what is happening in large waste containers, Sensorita uses machine learning algorithms trained on immense amounts of data. Check out our explainer below to see how that works.

Join this TransPack session at the #ISTAForum, led by Amin Joodaky & Khadijeh Shirzad of Michigan State University, to learn how machine learning is transforming the field of packaging dynamics. For more information on the upcoming Forum, visit https://bit.ly/48nCSCa.

Vector embeddings give you a way to represent information that isn't typically easy to represent by using a series of numbers produced from a machine learning model. Watch this quick video to learn more from Dev Advocate Yujian Tang! #MachineLearning #vectors #Zilliz

Our NEW preprint using machine learning to predict the net flow of programmable catalytic reactions in loops is now online: https://lnkd.in/gg6azBdq

Huang, Geitner, Croy and Gräfe use Δ-machine learning to identify optimal ligands for C-H activation by Ru complexes, in our latest featured #DigitalDiscovery article. Read the paper here: https://lnkd.in/e-Ecb3pp #openaccess

📢 Excited to share our latest blog post on "Improving Label Error Detection and Elimination with Uncertainty Quantification"! Identifying and handling label errors is crucial for enhancing the accuracy of supervised machine learning models. Our paper presents novel, model-agnostic algorithms for Uncertainty Quantification-Based Label Error Detection (UQ-LED), surpassing state-of-the-art confident learning in identifying label errors. Find out more about our groundbreaking approach and its impact on dataset cleaning and model accuracy here: https://bit.ly/44SK34U #MachineLearning #DataScience #UncertaintyQuantification

I am excited to share my latest research paper on "Real-Time Adaptive Control Systems for Turbocharged Engines Using Machine Learning Algorithms." Check it out on ResearchGate to dive into how machine learning is revolutionizing engine control systems: #ResearchPaper #MachineLearning #EngineControlSystems #TurbochargedEngines #AdaptiveControl

🚀 2024 will be wild as LLMs push into automation of time intensive tasks and unlock latent resources in life science organizations which are tied up in manual, repetitive and tedious work. With our Causaly AI Copilot release being imminent, we will deliver the first fully production grade scientific Copilot that combines scientific data from Knowledge Graphs and unstructured documents in a visual easy to use interface for scientists. Expect some developments in 2024 that will be game changing for R&D productivity. More to come soon...

We are seeing some amazing business projects coming to life with our customers who are leveraging retrieval augmented generation alongside Elastic. Need to learn more? Check out this video and then let me know if I can introduce you to Steve at Elasticon in New York next month! #RAG #GenAI #vectordatabase