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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:

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From the Editor

How is the advent of quantum computing going to influence artificial intelligence(AI). Basic assumption suggest that quantum processors will be able to accelerate the knowledge-building and training of machine learning systems. However, reducing the role of quantum computing technologies in AI systems to those areas seems very limiting. A more interesting idea is to explore whether quantum computing can enable AI systems that understand complex physical or biological systems that conventional computers are not able to.

The idea of quantum neural networks(QNN) has been around since the 1990s but its just recently that has become a more viable area of research. Just this week, Google published two research papers exploring different capabilities of QNNs for tasks such as classification and training. QNN applications are still on very early stages but the rapid evolution of quantum computing technology will definitely be a catalyzer for the space.

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

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Research

Google and Princeton University have partnered to advance AI research. Their joined efforts have already produced two research papers in large scale optimization and reinforcement learning.

>Read the summary of both papers in this blog post from the Google AI Research team

Google published two research papers exploring the role of quantum computing in deep learning models

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

Researchers from the University of Melbourne published a great summary of different papers about interpretability and AI presented at the Workshop of Interaction Design for Explainable AI

>You can find the summary paper here

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Cool Tech Releases

Facebook open sourced DeepFocus, a new framework for analyzing virtual reality images.

>Read more in this blog post from the Facebook engineering team

Staying with Facebook, the social media giant also open sourced wav2letter++, a high performance speech recognition framework.

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

IBM announced the NeuNetS a new services that can synthesize neural network models allowing non-experts to build sophisticated deep learning systems.

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

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AI in the Real World

In a recent interview, AI legend Kai-fu Lee thinks Europe is falling behind the US and China in terms of AI research

>Read the entire interview in this coverage at Sifted

IBM unveils their vision for AI

>Read more about it in this coverage from Inc Magazine

The Verge provided a comprehensive coverage of the future of AI in 2019

>Read more in this article of The Verge

Written by

CEO of IntoTheBlock, Chief Scientist at Invector Labs, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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