Gone are the days of optimizing content solely for search engines. For modern SEO, your content needs to please both robots and humans. But how do you know that what you're writing can check the boxes for both man and machine? In today's Whiteboard Friday, Ruth Burr Reedy focuses on part of her recent MozCon 2019 talk and teaches us all about how Google uses NLP (natural language processing) to truly understand content, plus how you can harness that knowledge to better optimize what you write for people and bots alike. Click on the whiteboard image above to open a high resolution version in a new tab! I'm Ruth Burr Reedy, and I am the Vice President of Strategy at UpBuild, a boutique technical marketing agency specializing in technical SEO and advanced web analytics. I recently spoke at MozCon on a basic framework for SEO and approaching changes to our industry that thinks about SEO in the light of we are humans who are marketing to humans, but we are using a machine as the intermediary. Those videos will be available online at some point.

Coming up with the ultimate cookie recipe can take even a seasoned baker hours of trial and error, all the more so if her target audience has specialized needs -- say, a diet that's vegan or gluten-free. Complicating matters is the fact that most cooks bring with them into the kitchen a set of biases as to what spices and flavor combinations will best work their magic. When Jeanette Harris was developing a chocolate chip cookie recipe for her Gluten Free Goat Bakery in Garfield, for example, the thought of adding cardamom -- a pungent spice used mostly in Indian cooking -- never crossed her mind. She certainly never thought about using technology to fine-tune her list of ingredients and baking methods, despite having been a guest cook with Google Pittsburgh chef John Karbowski at Kitchen Sync, the company's teaching kitchen for Google employees. Using artificial intelligence technology developed by software engineers at the Bakery Square office (and tested by Mr. Karbowski), researchers were able to determine that two teaspoons of the spice was exactly the right amount needed to create a killer cookie.

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.

Google has turned to an unusual source to train its high-tech AI: chocolate chip cookie recipes. Tasking programmers with helping an AI learn from data through trial-and-error is tedious and time-consuming, so the company has employed a neural network called Vizier to help another neural networks learn via a type of training automation called hyperparameter tuning. To teach Vizier, Google tasked it with formatting the perfect chocolate chip cookie recipe, considering taste-tester feedback until it for the recipe just right. Google has turned to an unusual source to train its high-tech AI: chocolate chip cookie recipes. The company gave chefs recipes to bake for taste-testers, who then provided feedback via a survey.