If the pandemic had never happened, Ali Z. might never have joined TikTok. But by the time the short, dark January days arrived, she was getting restless. Nearly a year into quarantine, her go-to hobbies--cooking, baking, and playing video games--felt lonely. In particular, she missed cooking for friends and family. "It's not quite as fun if you're just doing it on your own," Ali told me in a recent phone call. In the midst of this reflection, Ali realized her favorite video games involved aspects of cooking.

Some image recognition programs would not recognize this image as a bride. But not all brides wear white. Bias and discrimination are often used interchangeably. But they are not the same. Bias is a point of view or a preference for one thing over another.

Jeanette Harris would have never put two teaspoons of cardamom in a recipe for a dozen cookies. The spice is strong, polarising and typically associated with India and Asian cooking, not gluten-free chocolate chip cookies. "Humans have internal biases about these sorts things, especially cooks and bakers, we have these ideas that these are the tried and true ways," Harris said while she combined ingredients for her cookies during a cooking demo Monday at her bakery in Garfield. Two teaspoons of cardamom is not one of those tried and true ways. But when an artificial intelligence designed to optimise parts for airplanes and spaceships told her two teaspoons of cardamom was the right amount, she listened.

Several weeks ago I wrote a post on Bayesian statistics. I was very interested in the implementation of Bayesian statistics, especially for complex problems which are more easily solved with simulation rather than mathematical manipulation. I wrote the article with a specific audience in mind: namely those that knew the basics of Bayesian statistics, but had no idea how to implement it. As an astute commenter pointed out, in my excitement to implement my Bayesian program, I skimmed over several key points of Bayesian statistics and woefully mis-represented others. Let's fix that now, shall we! Let's talk about the basics of Bayesian statistics, and then move up to simulating them.

Little known secret about me, I love to bake. It doesn't matter if it's cakes, cookies, or bread, you name it and I've probably at least attempted to make it. So when I found out the Google Home added recipes to its repertoire, I knew I had to try it out for myself. But, you've also been able to cook with Google's competitor, the Amazon Echo, for a while now. How was I supposed to know which one was more helpful in the kitchen?

The good: Recognizes certain foods, Easy to use, Cooks food automatically The bad: Expensive, only identifies limited selection of foods Who should buy: Those with cash to spare who don't have much time to cook and have limited kitchen experience I'm not the best home chef around, yet my first attempt at baking lemon garlic salmon turned out perfectly. But I wasn't following a special technique: I just opened the oven door, slid in a tray of seasoned filets, and pressed a button. My oven took care of the rest. That's what it's like to use the June Intelligent Oven, which relies on a combination of internal cameras, artificial intelligence to identify and cook certain foods. The company behind the oven says it'll start shipping units to customers who pre-ordered its $1,495 oven in December; it'll start fulfilling new orders in January.