Weekly ML drop #5

I’ve become more and more interested in machine learning during last year. This is my way of collecting and sharing interesting reads on the topic I stumble upon. Those posts are published each Friday, they are divided into few categories and the format is constantly evolving.

This week I gathered a lot of articles on the topic of AI for self-driving cars and this will be a theme for this edition.

In this part, I share interesting news from machine learning and artificial intelligence world. Those are mostly not very scientific articles about interesting applications,  predictions and controversies that AI causes.

Artificial Intelligence will enable jobs too
Usually, in the context of AI, you can hear predictions of people losing jobs. In this story about IBM “new collar” jobs, we can read that company is aiming at hiring people uneducated in cyber security who have necessary set of natural skills, and augment them with technology to fill lackings in professional skills.

Intel forms new AI division
Intel’s been behind Nvidia in developments of processing units that power AI revolution. Recent acquisitions mentioned last week and forming new group shows that they’re not gonna give up easily. In a similar move, YCombinator is gonna run experimental vertical group focused on AI in next batch of founded startups.

Andrew Ng leaves Baidu
He’ll now focus on “shepherding this important societal change”. He also wants to support ML community around the world. I love the quote from his blog.

Just as electricity transformed many industries roughly 100 years ago, AI will also now change nearly every major industry — healthcare, transportation, entertainment, manufacturing — enriching the lives of countless people. I am more excited than ever about where AI can take us. — Andrew Ng

Agents in OpenAI research develop their own language
In this blog post, OpenAi discusses some results from the research that aimed at teaching AIs developing a new language of communication “by dropping them into a set of simple words, giving them the ability to communicate, and then giving them goals that can be best achieved by communicating with other agents”.

Learning materials
Here I’m sharing material for learning ML that I found useful – online courses, blogs, books etc. This is usually rather technical stuff.

Algorithmia’s not very heavy intro to Deep Learning
This is not very heavy article explaining on a high level what Deep Learning is.

Convolutional Neural Networks
Recently in my learnings, I was exploring the topic of CNNs. This is a type of neural networks that are very good at image recognition tasks. This series of articles going through interesting papers on the field and this papers were especially interesting. I highly recommend them if you’re interested in the topic.

This is it for today, thanks for reading. If you liked the post, let me know and please check other parts of the series.

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