Privacy-preserving A.I. is the future of A.I.

Facebook open-sources Opacus, a PyTorch library for differential privacy

Facebook recently open-sourced Opacus, a library for training PyTorch models with differential privacy that’s ostensibly more scalable than existing methods. With the release of Opacus,... Details
Privacy-preserving machine learning assuages infosec fears

Privacy-preserving machine learning assuages infosec fears

If you're a regular visitor to this blog, then you know that the use of machine learning and AI technologies rapidly on the rise and... Details
Privacy-preserving A.I. is the future of A.I.

Privacy-preserving A.I. is the future of A.I.

The London “festival of A.I. and emerging technology” that takes place each June. This year, due to Covid-19, the event took place completely online. (For... Details
10 Indoor Security Cameras Tested to Protect Your Privacy

10 Indoor Security Cameras Tested to Protect Your Privacy

The Hook Up puts 10 indoor cameras to the test to figure out which one gives the most features while retaining your privacy. My top... Details
Protecting Sensitive Data using Differential Privacy

Protecting Sensitive Data using Differential Privacy

Using data for machine learning and analytics can potentially expose private data.  How can we leverage data while ensuring that private information remains private? In... Details
Addressing GDPR and CCPA Scenarios with Delta Lake and Apache Spark

Addressing GDPR and CCPA Scenarios with Delta Lake and Apache Spark

Databricks  recently hosted this online tech talk on Delta Lake. The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) both aim... Details
Can open-source machine learning enhance CCTV at train stations?

Can open-source machine learning enhance CCTV at train stations?

Can security surveillance systems and associated analytics work in a station environment without disrupting the rail network? An interesting competition us underway in the UK... Details
Building Differentially Private Machine Learning Models Using TensorFlow Privacy

Building Differentially Private Machine Learning Models Using TensorFlow Privacy

Towards Data Science highlights this talk from the Toronto Machine Learning Summit, which introduces differential privacy and its use cases, discuss the new component of... Details
How our cellphone location data can save us from a COVID-19 recession

Can Our Cellphone Location Data Save Us from a COVID-19 Recession

By now, it’s clear that COVID-19 has become a significant threat to public health globally, prompting many governments to undertake draconian measures to contain or... Details
Yes, You Can Do AI Without Sacrificing Privacy

AI Without Sacrificing Privacy

Generally speaking, the more data you have, the better your machine learning model is going to be. However, stockpiling vast amounts of data also carries... Details