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How Facebook fights fake news with machine learning and human insights

The Parallax

To combat fake (or “false”) news, McNally says, Facebook now employs a wide range of tools ranging from manual flagging to machine learning. Facebook now works with a global network of fact-checking organizations to verify that content posted on Facebook Groups and pages is authentic, not designed to drive misinformation or hate.

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When voice deepfakes come calling

CIO

And if they werent, multi-factor authentication (MFA), answers to security questions, and verbal passwords would solve the issue. Navigating IVR According to an analysis of call center deepfake attacks, a primary method favored by fraudsters is using voice deepfakes to successfully move through IVR-based authentication.

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What’s holding back CIO’s AI strategies? Their own AI learning curve for one

CIO

But it’s important to understand that AI is an extremely broad field and to expect non-experts to be able to assist in machine learning, computer vision, and ethical considerations simultaneously is just ridiculous.” “A certain level of understanding when it comes to AI is required, especially amongst the executive teams,” he says.

Strategy 199
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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning. Choose a different stack name for each application.

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Scaling AI talent: An AI apprenticeship model that works

CIO

The hunch was that there were a lot of Singaporeans out there learning about data science, AI, machine learning and Python on their own. Because a lot of Singaporeans and locals have been learning AI, machine learning, and Python on their own. I needed the ratio to be the other way around! And why that role?

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Machine Learning at scale: first impressions of Kubeflow

OpenCredo

Machine learning has great potential for many businesses, but the path from a Data Scientist creating an amazing algorithm on their laptop, to that code running and adding value in production, can be arduous. Here are two typical machine learning workflows. Monitoring. Does it only do so at weekends, or near Christmas?

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. That’s up to the machine learning model to discover and avoid such false-positive incidents. Are you interested in solving challenging problems at the intersection of machine learning and security ?