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How I Keep Up with the Latest Innovations in AI and ML

Breaking down my reading list of what’s new in the AI world

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The field of Machine Learning and Artificial Intelligence is changing rapidly. Five years ago, classical Machine Learning was the hottest trend; now it’s just like an iPhone 6S — outdated. Deep Learning dominates the market these days, and if you’ll come back to this post in 2025, there’s a good chance we’ve moved way past beyond this (self-note: I bet on Deep Reinforcement Learning).

Being a data scientist requires you to keep up with the latest innovations and discoveries, but there’s so much information coming in from so many directions, it’s easy to get lost in the stream. So what should you focus on? Well, it depends on you — but to get you going, here’s my reading list of AI sources that allows me to keep up to date with the latest innovative ideas. You can give it a shot by going over one or two sources whenever you got a few minutes to kill. It’s far more valuable to you than 9Gag 🙂 (another self-note).

Leading companies’ AI Blogs

These companies are usually the ones that pop to your mind whenever you think of who actually use AI in the real world. While many more interesting and AI-leading companies exist, these four are usually my go-to blogs.

Google: There’s probably no reason for me to explain why I open my list with Google. These guys come up with new stuff like French boulangeries baking baguettes — on a daily basis. The Google AI Blog is an excellent source to keep up with latest innovation by the tech-giant, and they tend to explain their ideas in a very professional way. Another source for academic papers specifically is the Google Research Publication Database, narrowed down to AI topics.DeepMind: While technically a part of Google, DeepMind tend to be a somewhat of an autonomy within the corporation, which is said to sometimes rival with Google internal AI department. Being the ones behind some of the greatest breakthroughs of AI in the last few years, such as AlphaGo, AlphaGo Zero and AlphaFold, their Research Blog and publications is certainly a great source for keeping up to date with AI.Facebook AI: Another company you’ve probably already thought of, Facebook publishes many AI related papers, which can be found on their publications page. You can also checkout their blog, though I find it to be more like reading Wired articles, compared to Google AI’s blog.Microsoft Research: Yes, Microsoft. The company that once ruled us all and then faded away, has made a massive leap forward in all aspects — and their AI research and capabilities are no different. They too own an impressive amount of AI publications of the highest level. They also have two similar and relevant blogs, their AI Blog and Research Blog, yet both bear the same Wired feeling I mentioned before.

Academic blogs

While some of the sharpest minds work at the industry, they all started at the academia. Some of them are still there — and some do both — which is why following the latest AI news coming from leading AI labs and institutes are some of the best sources to keep up to date with this field.

BAIR: If we’ve ever spoke face-to-face about AI, there’s a very good chance you’ve heard me mentioning the Berkeley AI Research (BAIR) blog, as it is my number-one, all-time-favorite AI blog out there — and for two reasons: one, their main focus is Deep Reinforcement Learning, which I personally find the most interesting and most promising field in AI research. Second, and far more important, their ability to explain in simple words, using intuition and common logic, their fascinating and not-so-trivial concepts and ideas. I can only recommend you to follow them too.SAIL: Stanford University doesn’t need an introduction. Being the academic home of figures as Andrew Ng and Yoav Shoham, Stanford AI Lab (SAIL) blog is certainly a great source to be checked frequently.MIT: Another academic institute which you’ve probably already heard about, MIT News on Artificial Intelligence and MIT Technology Review on Artificial Intelligence both feel like an AI-dedicated branch of TechCrunch, and are recommended and a contradicting reading-genre than the other two mentioned above.

Leading AI conferences

Each respected AI conference has a list of accepted papers, which are presented as it goes along. While each is being updated only once a year, they each accept quite a bunch of papers, which will keep you busy reading for quite some time. Here are some of these:

NeurIPS: accepted papersRecSys: 2020 list of accepted papersKDD: 2020 list of accepted papersICLR: 2020 list of accepted papers

Latest on arXiv

Obviously, a lot of innovative companies and leading institutes are not on these lists. One of my favorite methods to find the latest papers, regardless of authors, is to use arXiv’s Advanced Search and limit it to the period of time I’m interested in (for example, last month). To get only AI related papers, filter only results of these subcategories: cs.LG and cs.AI.

That wraps up my reading list. Got any other source you think is worth checking? Let me know in the comments!

How I Keep Up with the Latest Innovations in AI and ML was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

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