Usually, every month we write an article about the best and most promising AI research papers from that month. You can check them out here:

In addition to that, we list fifteen AI articles we have found amazing that month. This collection of articles should give you an overview of what happened that month in the AI industry both from technical, business and from an ethical perspective. You can check out previous months here:

Have fun!

Not so long ago, Andrej Karpathy famously tweeted: ‚ÄúGradient descent can write code better than you. I‚Äôm sorry.‚ÄĚ What he was trying to say is that¬†neural networks, which use Gradient descent optimization technique, will soon be able not just to write code, but to¬†write code better than us¬†‚Äď software developers. Stay relevant in the rising AI industry an learn all you need to know about deep learning¬†here!

NASA needs your help teaching its Curiosity rover how to drive on Mars

Curiosity Rover needs your help! NASA recently published a new online tool called AI4Mars. This tool allows anyone to label parts of the terrain in the landscape surrounding Curiosity and help it learn how to drive on Mars. 

Read the complete article here.

Deepfake Detection Challenge Results: An open initiative to advance AI

Facebook teamed up with other companies to create Deepfake Detection Challange. The goal of the challenge was to improve the development of new ways to detect deepfake videos. They created and shared new data set of more than 100,000 videos that were used for the challenge.

Read the complete article here.

AI researchers say scientific publishers help perpetuate racist algorithms

Paper called “A Deep Neural Network Model to Predict Criminality Using Image Processing‚ÄĚ raised a lot of heat. The problem is that algorithm is biased. This caused a coalition of AI researchers to publish an¬†open letter¬†based on leading¬†Black¬†AI¬†scholars, which debunks the scientific basis of the paper and asserts that crime-prediction technologies are racist.¬†

Read the complete article here.

Slightly Unnerving AI Produces Human Faces Out of Totally Pixelated Photos

The very cool algorithm that is able able to create photo-realistic faces from pixilated images. It has many problems because it seems that the authors used biased data, so we are slowly drifting into ethical concerns here as well. Still, we can learn a lot from this. 

Read the complete article here.

NeoML Released as TensorFlow Alternative 

NeoML framework is a cool new alternative if you are developing deep learning models for mobile devices. The publishing company ABBY is describing it as a cross-platform deep learning framework that works 20 times faster than TensorFlow for pre-trained image processing models, regardless of device.

Read the complete article here.

Google Meet takes on Zoom with AI-powered noise cancellation

Zoom dominated 2020 because of the whole Covid situation. Google is trying to get some piece of that cake by extending Google Meet with noise cancellation for video conferencing.

Read the complete article here.

Recommendation systems 2

Machine learning helped demystify a California earthquake swarm

California is hit with four-year-long swarm of tiny earthquakes, because of groundwater. Now, scientists are able not only to predict them but to identify the problem and propose the measures using ML.

Read the complete article here.

Google’s MixIT AI isolates speakers in audio recordings

Digest of a cool paper in which researchers propose mixture invariant training or MixIT. This is an unsupervised approach to separating, isolating, and enhancing the voices of multiple speakers in an audio recording. 

Read the complete article here.

IBM says it is no longer working on face recognition because it’s used for racial profiling

IBM‚Äôs CEO Arvind Krishna said in the open letter to the government that the company opposes any technology used ‚Äúfor mass surveillance, racial profiling, violations of basic human rights and freedoms.‚ÄĚ

Read the complete article here.

Recent Advances in Google Translate

Catch up with the recent NLP advances that ended up in new Google Translate.

Read the complete article here.

TensorTrade: Trade Efficiently with Reinforcement Learning

This is one very cool framework if you are into Reinforcement Learning and Trading. It provides means for building, training, evaluating, and deploying robust trading algorithms.

Read the complete article here.

How Artificial Intelligence Could Help Video Gamers Create the Exact Games They Want to Play

A really interesting article on how AI can help video game makers create new and beautiful worlds. The ideas come from Matthew Guzdial, an AI researcher and assistant professor at the University of Alberta. He and his team are working on software that will be able to build video games from scratch.

Read the complete article here.

Russian Voice Assistant Alice Can Paint Landscapes and Abstract Concepts on Command

A new voice assistant created Yandex РAlice uses two neural networks to figure out what to draw based on what it is told. 

Read the complete article here.

Microsoft researchers say NLP bias studies must consider role of social hierarchies like racism

With everything that is happening in USA, ethical AI is a big topic of the month. While IBM stopped working on facial recognition products, Microsoft focuses on language and on NLP. Even recently published GPT-3 has racial bias.

Read the complete article here.

Grading on a Curve? Why AI Systems Test Brilliantly but Stumble in Real Life

Everyone working in the industry knows that developing and testing a model is one thing and deploying it to production is whole another thing. This article explores the challenges of pushing AI algorithms in production.

Read the complete article here.

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Rubik's Code

Building Smart Apps

Rubik‚Äôs Code¬†is a boutique data science and software service company with more than 10 years of experience in Machine Learning, Artificial Intelligence & Software development. Check out the¬†services¬†we provide. Eager to learn how to build¬†Deep Learning¬†systems using Tensorflow 2 and Python? Get our ‚ÄėDeep Learning for Programmers‚Äė ebook¬†here! Read our blog posts¬†here.
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