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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: Fairness in AI

One of the greatest benefits of artificial intelligence(AI) is that it can produce results that are pragmatic and not vulnerable to the subjectivity and biases of humans. However, that statement of only partially true. While AI systems don’t make decisions based on feelings or emotions, they do inherit a lot of human biases via the training datasets. Bias is relevant because it leads to unfairness. Defining a notion of fairness is one of the most important challenges of the next decade of AI.

Building more fairer AI systems seems like an obvious goal but how to we exactly define fairness. Conceptually, fairness can be define as a relationship between a sensitive input attribute such as race or gender and the output of the model. However, that’s just part of the equation. AI Fairness is directly related to the biases in the data generation model. This week, DeepMind published some clever work about how to build more fairer machine learning systems using a very old statistical model. DeepMind’s work is an example of the importance of the role that fairness will play in the next generation of AI systems.

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

AI Research

AI and Quantum Computing

Google AI researchers published a new paper that proposes a framework for optimizing quantum computation models using machine learning

>Read more in this blog post from Google AI

An Old Statistical Model to Improve AI Fairness

DeepMind published a new research paper discussing how causal Bayesian networks can improve the fairness of machine learning models.

>Read more in this blog post from the DeepMind team

High Quality Speech Synthesis

IBM Research published a new paper that proposes a better text-to-speech method for high quality speech synthesis.

>Read more in this blog post from IBM Research

Cool AI Tech Releases

TensorFlow 2.0

TensorFlow 2.0 has launched with a lot of new cool features

>Read more in this blog post from the TensorFlow community

Streamlit launches a new machine learning framework

Streamlit, a startup founded by a lot of AI industry veterans launched a new machine learning development framework accompanied by a $6 million series A.

>Read more in this coverage from TechCrunch

New AutoML Capabilities

Google released new upgrades to AutoML Vision Edge and AutoML Video.

>Read more in this coverage from VentureBeat

AI in the Real World

Tesla Adds AI Talent

Tesla quietly acquired DeepScale, a machine learning startup to improve its autopilot system.

>Read more in this coverage from Fortune

AI for Designing Drugs

Novartis and Microsoft partner to develop drugs using AI

>Read more in this coverage from The Financial Times

AI News Commentator

Microsoft built a bot that can comment on news

>Read more in this coverage from Vice

Written by

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

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