Automated Container Resource Checks: Does your container have the required resources?

Automated Container Resource Checks: Does your container have the required resources?

At Private AI, we are building a privacy suite centered around personally identifiable information (PII) detection and remediation in unstructured data, such as text. Users interact with our system via a REST API, but what makes us different is that we distribute our system as a container that our customers themselves run. It’s counterintuitive to send data to … Read more

ML Model Evaluations & Multimodal Learning

In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Dr. Aida Nematzadeh (Staff Research Scientist at DeepMind) to discuss machine learning models and multimodal learning.  Before joining DeepMind, Dr. Nematzadeh was a postdoctoral researcher at UC Berkeley advised by Tom Griffiths and affiliated with the … Read more

How to Autoscale Kubernetes Pods Based on GPU

There are several resources available on the internet on how to scale your Kubernetes pods based on CPU, but when it comes to Kubernetes pods based on GPU, it’s hard to find a concise breakdown that outlines each step and how to test. In this article, we outline the steps to scale Kubernetes pods based … Read more

Language Modelling via Learning to Rank

In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Arvid Frydenlund (PhD candidate at the University of Toronto in the Computer Science Department and Vector Institute) to discuss his latest paper Language Modelling via Learning to Rank, presented at AAAI-2022 and published at the 6th Workshop on Structured Prediction for … Read more

MLOps & Machine Learning Deployment at Scale

In the latest episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sits down to chat about MLOps and Machine Learning Deployment at Scale with Luke de Oliveira from Twilio. Luke de Oliveira is the Director of Machine Learning at Twilio, working at the intersection of technology and product. He is building Twilio Intelligence, a … Read more

Deploying Transformers at Scale

Transformer networks have taken the NLP world by storm, but the sheer size of these networks presents new challenges for deployment, such as how to provide acceptable latency and unit economics.

Rappel

Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.

99.5%+ Accuracy

Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.

Please contact us for a copy of the code used to compute these metrics, try it yourself here, or download our whitepaper.