Artificial Intelligence (AI) Newsletter by Towards AI #14

Last Updated on November 10, 2021 by Editorial Team

Author(s): Towards AI Team

The Artificial Intelligence (AI) Newsletter by Towards AI

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Hey everyone, I hope you are well. In this issue, we dive into the definitive guide to starting in machine learning, how realistic it is to automate an end-to-end AI pipeline, is Codex really going to replace programmers, what about modelitis, is it coming to an end, and last but not least why AI will never replace managers.

This issue is brought to you thanks to expert.ai:

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You have probably noticed that we have changed the format of the newsletter a bit. We would love to obtain your feedback on whether you like this new format or not, and any feedback you have. So please feel free to drop us a note in any case. We’d love to hear from you.

Machine Learning Guide: If you are starting out in machine learning, the technicalities, math, and other nuances may seem overwhelming. Please know that it is normal to feel that way. I’ve had exactly the same feelings when I started reading about it a few years ago. In case you are in the starting boat, we recommend you to check out this extensive guide by our Head of Community, Louis Bouchard, diving into how to start your machine learning journey in 2021. It has been shared all over, including our friends at MIT.

Automating and end-to-end AI pipeline: Can we automate a full pipeline? Not yet, but the results are promising. “The ideal solution is to inject the domain expertise and then automate different parts of this pipeline while also ensuring that the human knowledge and domain expertise are still somehow injected into your system.” ~ Paroma Varma, Ph.D. Learn more about the conversation on automating pipelines on applying weak supervision research.

Is Codex really going to replace programmers? Short answer, No. Long answer, check out this insightful post by Thomas Smith with some spooky results showcasing how Codex plans to empower programmers by making them more proficient, dynamic, and robust.

Is modelitis coming to an end? Everyone has been talking about data-centric AI, from world-renowned experts like Andrew Ng, to industry whales, to prestigious research labs. Researchers and practitioners have realized two things, 1. better results are achieved by genuinely understanding the data, and 2. customized models are challenging to develop, maintain in production, and worse so with oversized models.

Is AI going to replace managers? No, it won’t. Long answer, decision-makers have a unique skill called reframing, which poses the ability to deduct complex problems before solving them — which is one of the most complex and time-consuming parts in management roles. For a more informative answer, check out this post by Harvard Business Review that talks about it further.

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Thank you! Until next time,

Roberto and the team at Towards AI

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Artificial Intelligence (AI) Newsletter by Towards AI #14 was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.

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