A first look at two major AI releases — Here comes an AI unboxing video! These shiny new tools were released just over a week ago, so they’re fresh out of the oven. In the video, you’ll see me running my first ever Bard + GPT-4 side-by-side prompts. Below that, you’ll find something that started as the video transcript…

Let’s take a look at the hottest AI tech released in the past week — Wow, what a week for the AI industry! Over the last few days, we saw some massive AI announcements, including two cutting edge large language model (LLM) releases that rocked social media: Mar 14, 2023: GPT-4 Mar 21, 2023: Bard How do they relate to one another? I feel your…

(Besides the fact that you don’t need technical skills to do it) — One week ago, on Mar 14, OpenAI released GPT-4. I’ll admit to being one of the users who rushed to pay my $20/month to play with it by getting a ChatGPT Plus subscription and I’m impressed. Let me take this opportunity to congratulate OpenAI on a tremendous achievement in democratizing…

Motivation and career insights I wish I hadn’t had to work out for myself — Most of my articles are about data science and decision-making, but occasionally I write articles about other topics because they were helpful in getting me where I am today. Here’s a compilation, so you don’t have to learn it all the hard way. While some of these articles were written…

The industry-wide neglect of data design and data quality (and what you can do about it) — My favorite way of explaining the difference between data science and data engineering is this: If data science is “making data useful,” then data engineering is “making data usable.” These disciplines are so exciting that it’s easy to get ahead of ourselves and forget that before we can make data…

The bias-variance tradeoff, part 1 of 3 — Should you read this article? If you understand all the words in the next section, then no. If you don’t care to understand them, then also no. If you want the bolded bits explained, then yes. The bias-variance tradeoff “The bias-variance tradeoff” is a popular phrase you’ll hear in the context of ML/AI…

The bias-variance tradeoff, part 2 of 3 — In Part 1, we covered much of the basic terminology as well as a few key insights about the bias-variance formula (MSE = Bias² + Variance), including this paraphrase from Anna Karenina: All perfect models are alike, but each unhappy model can be unhappy in its own way. To make…

The bias-variance tradeoff, part 3 of 3 — We covered a lot of ground in Part 1 and Part 2 of this series. Part 1 was the appetizer, where we covered some basics you’d need to know on your journey to understanding the bias-variance tradeoff. Part 2 was our hearty main course, where we devoured concepts like overfitting…

Let’s take a Midjourney around the world — Welcome! This isn’t so much a blog post as an exhibition made with Midjourney, showcasing the beauty and bias of AI art. …