Every week, Invector Labs publishes a newsletter that covers 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: Machine Learning for Quantum

Quantum computing is likely to be the next big technology revolution and one that its going to change many of the established principles of computer science. Artificial intelligence(AI) is one of the disciplines that its likely to be accelerated by the advent of quantum computing. However, most machine learning models would need to be reimagined to work in quantum architectures and that will require a new generation of frameworks.

This week, Google AI announced the release of TensorFlow Quantum(TFQ), a new framework that enables the creation of machine learning models and datasets that work on quantum architectures. The beauty of TFQ is that it allow developers to leverage the familiar TensorFlow tools and libraries making it easier for data scientists and researchers to jump into this new world. Certainly a project worth following in the next few years.

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

AI Research

Amazon Smart Search Queries

AI researchers from Amazon published a paper proposing a neural network for predicting context of use from customer queries.

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


In a new research paper, Google proposes ELECTRA, a new pre-training technique that enables the implementation of more efficient NLP models.

>Read more in this blog post from Google Research

Facebook RIDE

Facebook AI researchers published a paper describing Rewarding Impact-Driven Exploration (RIDE), an intrinsic reward method that encourages AI-driven agents to take actions, versus just exploring, in an environment.

>Read an explanation of the paper in this coverage from VentureBeat

Cool AI Tech Releases

TensorFlow Quantum

Google open sourced TensorFlow Quantum, an open source framework for prototyping quantum machine learning models.

>Read more in this blog post from Google Research

LinkedIn Data Sentinel

LinkedIn unveiled the details behind their platform for data quality and validation.

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

Cloud AI Platform Pipelines

Google Cloud introduced AI Platform Pipelines, a new platform to simplify machine learning development.

>Read more in this blog post by the Google Cloud team

AI in the Real World

The White House, AI and Coronavirus

US Chief Technology Officer Michael Kratsios previewed a database of coronavirus-related information and urged AI companies to use to find solutions that help fight the pandemic.

>Read more in this coverage on The Next Web

Kaggle Coronavirus Challenge

A new Kaggle challenge is looking to predict the spread of coronavirus.

>See the details about the data challenge here

IBM Adds Project Debater to Watson

IBM is going to leverage Project Debater as part of Watson’s sentiment analysis, summarization, and clustering topics found in language.

>Read more in this coverage from VentureBeat

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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