AI that caught my eye

Here are three links to AI articles that got my attention this week:

  1. Just how good is AI today and where is it heading? This fascinating piece from the NY Times shows the power of OpenAI's DALL-E 2 application. The sample images produced by DALL-E are stunning and the writer, Kevin Roose, makes an excellent point when he says, "you should be paying closer attention to the real, tangible developments that are fueling" AI. That's precisely why I decided to dive in by reading as much as I can on the topic, following many of the thought leaders and sharing my journey on this website.
  2. AI is already in a lot of places and you just don't realize it. Take, for example, the way Panera Bread is leveraging the technology to improve their drive-thru experience. Note that they're also using AI to help measure coffee volume and temps.
  3. Worried about data bias and privacy? Synthetic data might help address both of those issues. It feels like anonymized data on steroids but as I dug deeper into the topic I learned that one of the drawbacks, at least for now, is that it's unable to fully replicate the complexity of the original data.

Machine Learning for Absolute Beginners, by Oliver Theobald

Machine Learning Abs BegNow that I've read a few books and have taken a trio of AI courses I wanted to share that Machine Learning for Absolute Beginners is a must-read for anyone interested in AI and/or machine learning. The reason why this is such a valuable resource has to do with what I discovered after I read it.

I chose the Kindle edition of this one and I'm glad I did. Now that I've reached the end I realize how many fundamental definitions and descriptions were presented throughout. In fact, as I look through my Kindle highlights I see they read like a Cliffs Notes of important AI/ML concepts.

If you've never looked at a Kindle book this way I encourage you to do so by going to read.amazon.com/notebook and finding an ebook you've highlighted or added notes to. This is a much better view than what you'll find in the Kindle app itself, especially on a larger monitor. The only drawback to viewing highlights and notes in the read.amazon.com/notebook link is that you can't export them; in order to pull them out of the Amazon ecosystem you need to use the export feature in the Kindle app.

Back to the book... As the title suggests, if you don't know anything about AI this is a terrific place to start. That said, even though I didn't discover and read it till further along in my journey I'm confident it will be a frequently accessed, important resource in my library.

Deep learning, symbolic AI and hybrid AI

This article might appear to be rather lengthy but it's worth reading every single word. The author, Gary Marcus, provides a short history and comparison of deep learning, symbolic AI and a hybrid approach. Spoiler alert: One size doesn't fit all, so he recommends the hybrid model.

A few paragraphs into the article I felt deflated, wondering if AI will always be one of those technologies that is stuck in place and constantly described as "a revolution that's just x years away", but x never gets here. The more I read, however, the more optimistic I became and began to appreciate the case he makes for the hybrid approach. In fact, the author has me so convinced that my next step is to go buy his book, Rebooting AI.

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