Every week, my team at Invector Labs publishes a newsletter to track the most recent developments in AI research and technology. You can find this week’s issue below. You can sign up for it below. Please do so, our guys worked really hard on this:

From the Editor: Facebook is Making Deepfakes to Fight Deepfakes

Deepfakes are one of the existential challenges of digital information distribution. Recent advancements in machine learning make possible to manipulate images and videos to create fake content that is indistinguishable from the real one. In order to get more efficient at detecting deepfakes, organizations need to create machine learning models that are as advanced as those generating the fake content. Can we fight fire with fire?

This week, Facebook announced that it will generating a new dataset of deepfakes in order to help artificial intelligence(AI) researchers train detection models. The social media giant will dedicate $10 million for funding the detection technology through grants and challenge prizes and was able to involve other technology powerhouses like Microsoft as well as top universities. Just like with the antivirus revolutions, to stop deepfakes we might need to get really good at creating them.

Now let’s take a look at the core developments in AI research and technology this week:

AI Research

DeepMind published a research paper introducing R2D3, an AI agent that makes efficient use of demonstrations to solve hard exploration problems in partially observable environments.

>Read more in this blog post from DeepMind

Facebook AI researchers published a paper introducing a natural language strategy game to help AI agents make complex decisions.

>Read more in this blog post from Facebook AI Research

Facebook, Microsoft and several prestigious academic institutions launched a challenge to create a dataset and models to fight deepfakes.

>Read more in this blog post from Facebook AI Research team

Cool AI Tech Releases

Google open sourced Neural Structured Learning, an TensorFlow extension to train neural networks using graphical structured datasets.

>Read more in this blog post from the TensorFlow contributor team

SingularityNET announced the new Beta version of its Decentralized AI marketplace.

>Read more in this blog post from the SingularityNET team

Google released two datasets to improve the training of natural language models.

>Read more in this blog post from the Google Research team

Microsoft and Qualcomm announced the release of a new developer kit to accelerate vision analysis capabilities for internet of things(IOT) applications.

>Read more in the announcement from the Azure IOT team

AI in the Real World

Huawei launched a new app that let’s visually impaired users read text with their phone’s camera.

>Read more in this coverage from VentureBeat

AI could enable the near impeccable lie detectors, but is it ethical?

>The Guardian published a very detailed article about this controversial subject

Amazon is testing a new AI system that allow people to pay by using their hand.

>Read more in this article from MIT Technology Review

CEO of IntoTheBlock, Chief Scientist at Invector Labs, I write The Sequence Newsletter, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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