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Private AI Secures $3.15 Million Seed Round to Streamline Privacy Compliance for Enterprises
Limina Updates
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September 15, 2021

Private AI Secures $3.15 Million Seed Round to Streamline Privacy Compliance for Enterprises

TORONTO, ONT., Sept. 15, 2021— Private AI, a developer of privacy-preserving machine learning and natural language processing tools, is pleased to announce that it has secured $3.15 million in seed funding to improve their product offering, expand the team, and accelerate their acquisition of domestic and international customers.

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Anonymized Data is Useless: Fact or Fiction
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August 20, 2021

Anonymized Data is Useless: Fact or Fiction

“When is anonymization useful?” is a tricky question, because the answer is highly data-type- and task-dependent.

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Data Anonymization: Perspectives from a Former Skeptic
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June 4, 2021

Data Anonymization: Perspectives from a Former Skeptic

On the misleading ways journalists and industry use the term "anonymization."

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Demystifying De-identification
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April 6, 2021

Demystifying De-identification

Understanding key tech for data protection regulation compliance

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What It Really Takes to Build An AI System: It’s more complicated than many think
Artificial Intelligence
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February 17, 2021

What It Really Takes to Build An AI System: It’s more complicated than many think

Building an AI system sounds straightforward until it isn't. From sourcing quality training data to handling real-world edge cases, productionizing models, and maintaining them over time, the true cost of building your own is far greater than most teams anticipate. Here's an honest breakdown of what it actually takes.

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Natural Language v. Regex: The Context wars
Artificial Intelligence
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February 3, 2021

Natural Language v. Regex: The Context wars

Regexes are highly effective in the perfect world of computer data, but unfortunately the real world is much more complicated.

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Customers Are Demanding Privacy
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November 5, 2020

Customers Are Demanding Privacy

In the past three years there has been a massive wake-up in customer awareness about privacy. Many customers are now refactoring how they buy, taking their business elsewhere if they don’t trust a company’s data practices.

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Privacy Enhancing Technologies Decision Tree
Privacy
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October 18, 2020

Privacy Enhancing Technologies Decision Tree

Privacy Enhancing Technologies Decision Tree: for developers, managers, and founders looking to integrate privacy into their software pipelines and products.

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Liability & AI Malfunction: An AI System Developer’s Perspective
Artificial Intelligence
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September 1, 2020

Liability & AI Malfunction: An AI System Developer’s Perspective

AI is rapidly being deployed around the world with few to follow. Along with the complexity of creating the technology, there remain many unanswered legal questions.

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Developer Guides
Privacy
Accelerating Tensorflow Lite with XNNPACK
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June 12, 2020

Accelerating Tensorflow Lite with XNNPACK

The new Tensorflow Lite XNNPACK delegate enables best in-class performance on x86 and ARM CPUs — over 10x faster than the default Tensorflow Lite backend in some cases.

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NVIDIA DALI: Speeding up PyTorch
Developer Guides
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January 21, 2020

NVIDIA DALI: Speeding up PyTorch

Some techniques to improve DALI resource usage & create a completely CPU-based pipeline.

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Artificial Intelligence
Part 2: Homomorphic Encryption for Beginners
Developer Guides
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September 3, 2019

Part 2: Homomorphic Encryption for Beginners

We discuss a practical application of homomorphic encryption to privacy-preserving signal processing, particularly focusing on the Fourier transform.

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Privacy
Part 1: Homomorphic Encryption for Beginners
Developer Guides
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December 26, 2018

Part 1: Homomorphic Encryption for Beginners

We cover the basics of homomorphic encryption, followed by a brief overview of open source HE libraries and a tutorial on how to use one of those libraries (namely, PALISADE).

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Privacy
The Definitive Guide to Privacy-Preserving Natural Language Processing: Why It Is Essential for the Modern Enterprise
Privacy
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June 26, 2018

The Definitive Guide to Privacy-Preserving Natural Language Processing: Why It Is Essential for the Modern Enterprise

Natural language processing is now central to how enterprises operate, but the data powering these systems is often deeply sensitive. This guide explains why privacy-preserving NLP is no longer optional, how de-identification differs from encryption, and what organizations need to do today to build AI that is secure, compliant, and trusted.

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A Brief Overview of Privacy-Preserving Technology Methods
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March 22, 2018

A Brief Overview of Privacy-Preserving Technology Methods

A very brief overview of privacy-preserving technologies follows for anyone who’s interested in starting out in this area. I cover symmetric encryption, asymmetric encryption, homomorphic encryption, differential privacy, and secure multi-party computation.

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