A new AI step in Windmill returns a typed answer: a choice, a score, or a yes/no with a probability. Not a text blob you parse. Your next step branches on it with a regular Branch, so the flow routes on the model's decision.
https://t.co/HZZIHCRTAR
A saved AI agent now has its own page in Windmill. Build one, deploy it, and anyone with access can open it and chat, no flow to wrap it in.
https://t.co/HZZIHCRTAR
We are excited to share that DataCo Technologies has selected our XOR Platform to accelerate the growth of consented, privacy-preserving data analytics among leading brands and their ecosystem partners. Read the press release here https://t.co/sPVDwxznNh
In this 1st part of the joint blog series between @lreninfo and Inpher, we show how hospitals can collaborate with other healthcare providers and develop accurate models to detect Alzheimer's disease early on with privacy-preserving #MachineLearning. https://t.co/PHjetUuQ6U
Building a privacy-preserving decision tree model using MPC was hard until now. Read this blog post to learn how XORBoost addresses this challenge. We illustrate this using a fraud detection example that you can try out yourself today!
https://t.co/HzOpvcaspv
We are thrilled to announce today a strategic investment from @SwisscomStartUp. This will help accelerate Inpher’s growth and partnership for market acceleration in the telecom, finance, and healthcare industry. Read the press release here https://t.co/zxlRsRkx2g
We're hiring a platform software engineer to build the next gen privacy preserving tech @inpher_io. Distributed systems, Scala, and other goodness! Apply here (DMs welcome): https://t.co/uG9g30r7aM
Dimitar Jetchev, CTO of @inpher_io, and Joan Feigenbaum, a @Yale computer science professor & Amazon Scholar, describe methods for privacy-preserving ML to address challenges in XGBoost training and prediction. #AmazonScience https://t.co/jJJOF4ndtq
Join our session tomorrow morning at 8a PT to learn how @BNYMellon is building a novel #frauddetection framework with our Secret Computing technology. https://t.co/wucVJnsUEu
Learn how Inpher is accelerating multiparty computation, a compute-intensive crypto technique to help orgs build privacy-preserving #MachineLearning and #FederatedLearning. Our on-demand technical session goes live on Apr 12, 10a PT [S31441] at @NVIDIAGTC https://t.co/FYYfGtogZi
Find out how @BNYMellon uses our Secret Computing technology to build a novel collaborative #frauddetection framework and better predict fraudulent transactions. Join our featured session on Apr 15, 8a PT [S31598] at @NVIDIAGTC https://t.co/wucVJnKw34
Find out how @BNYMellon and @inpher_io built a novel collaborative #frauddetection framework that resulted in up to 20% better predictions for fraudulent transactions. Join the free session [S31598] at #GTC21: https://t.co/O5TOA5ohIh
We are thrilled to announce today a strategic investment from @amazon's @alexadevs for consumer data protection in AI. This will help Inpher advance privacy-preserving ML in connected devices and IoT services. https://t.co/0AHYznnq5h
#ePrint Manticore: Efficient Framework for Scalable Secure Multiparty Computation Protocols: S Carpov, K Deforth, N Gama, M Georgieva, D Jetchev, J Katz, I Leontiadis, M Mohammadi, A Sae-Tang, M Vuille https://t.co/cs3VZjdNll