About Models and Metrics

In 2023, I wanted to go to graduate school to get a Ph.D. in Deep Learning. However, the launch of GPT-4 made me question that decision, as I realized that the future of artificial intelligence is being written today.

A few decades from now, we will look back at this time the same way we do at other major accomplishments in computing, such as the launch of the iPhone. We’re so early in the field of artificial intelligence that the most valuable textbooks have not even been written yet. We’re living through some of the most iconic moments of technological history, and I did not want to lock myself in a school library while the greatest innovations were still happening.

If you want to master something, teach it.” - Richard Feynman

Through this blog, I aim to learn and then illustrate a new aspect of artificial intelligence each week. Much of what I write comes from countless hours of reading research papers, tinkering with open-source tools, and drawing on my personal experience building enterprise applications with generative AI.

A software engineer by training, I do not intend to write in highly esoteric, philosophical, or theoretical terms but rather to communicate in straightforward language that is practical for engineering teams and business leaders for building great products. In some sense, "Models and Metrics" is my own, open-source dissertation in the art and science of artificial intelligence.

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Qualitative and quantitative insights in Artificial Intelligence for leaders in tech.


I read the latest and greatest research papers on artificial intelligence every week to teach you about the most important concepts without the technical jargon.