Applied NLP, Challenges in RL, State-of-the-art Research, and more!

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How do we attract and keep the best and the brightest? This post by Divyansh Kaushik and Caleb Watney dives into a fundamental problem. How to support international students and entrepreneurs in our economy to continue to have the US as an innovation powerhouse and keep attracting highly skilled immigrants.

If you are into the realms of the fascinating weak supervision and programmatic labeling approaches, we recommend you to check out “How to Use Snorkel to Build AI Applications,” where Head of Technology and Co-founder of Snorkel AI, Braden Hancock, dives into the history and state-of-the-art methods that drove Snorkel to become the giant that they are now—starting within the OSS realm and moving toward serving some of the world’s most prominent Fortune 500 enterprises.

Now, let’s face it. AI systems are often opaque, strange, and challenging to use. In the field of machine learning, this is particularly true. So if we want to make intelligent systems that people can understand and interact with — more efficiently, a crucial part of the solution is a community where people can come together, share ideas and learn from each other. That is why we created our AI community on Discord — to connect and learn with other data experts and enthusiasts.

Minecraft poses a unique environment, and the folks at MineRL have been working hard in beating Minecraft using state-of-the-art machine learning. If you haven’t yet, check out their work and how to get involved — most of their work is OSS.

One of the coolest things launched recently is Habitat by Facebook AI, aiming at helping researchers and practitioners tackle the next frontier in embodied AI by enabling agents to be trained in interactive environments at much faster speeds than their predecessors.

Also, Github recently launched Copilot, an AI application powered by OpenAI that translates natural language into code, and Codex, a natural language power source, will integrate with the app by the end of the Summer through an API. With Copilot, developers can get code suggestions for whole lines and sometimes entire functions right within the editor as you go, and while it may present biases, it’s going to be very useful for non-bias-based applications. For a more straightforward yet robust proof-of-concept similar to Copilot, check out the OSS CoderX by Carnegie Mellon Professor Graham Neubig.

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Now onto the monthly picks! We pick these articles based on readers, fans, and views a specific piece gets. We hope you enjoy reading them as much as we did. Also, we started doing something new! We will pick our top-performing articles, and our editors will choose a couple of essays that didn’t have outstanding performance, but due to their quality — they made the cut for the month.

📚 Editor’s choice featured articles of the month ↓ 📚

Reinforcement learning(RL) has been at the center of some of the most impressive achievements in artificial intelligence(AI) in the last decade. From DeepMind’s famous AlphaGo to milestones in StarCraft II, Dota 2, or Minecraft, RL remains one of the fastest-growing areas in the deep learning space. However, despite all its success, Facebook AI Research(FAIR) believes that RL needs to be pushed to new levels, and, for that, they are turning their attention to a new game: NetHack.


Trending AI/ML Article Identified & Digested via Granola by Ramsey Elbasheer; a Machine-Driven RSS Bot

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