Artificial IntelliTools

  image by ChatGpt. lol I Just Tried Google’s New “AI Mode” — My Take on the Future (and Possible Death) of Search An email popped up in my inbox just a couple of hours ago. Google. Subject: Something about AI Mode and Search Labs. Honestly, I barely remember signing up for whatever beta or experiment this was, but there it was. The email pitched “a new search experiment where you can get AI-powered responses, ask follow-up questions, and explore more on the web.” My immediate reaction? “Wait, isn’t that… just the definition of AI?” It sounded less like a revolutionary feature and more like Google finally catching up to describe what AI does . Still, curiosity got the better of me. What exactly is this AI Mode, and what does it tell us about where search is headed? Let’s dive into what I found. First Impressions: It’s Google Search, But With an AI Assistant Glued On Firing up this new AI Mode felt… oddly familiar, yet different. At its core, it’s the Google Search w...

New York City’s Noise Landscape. Apodcast? E.K.O Legend · Data Speaks: Understanding NYC's Noise Landscape So, I’m sure you’ve heard of Google’s Notebook LM. If you haven’t, listen to the podcast above then come back. Seriously, I’ll wait. OK, Just press play and listen as you scroll through. Alright, now that you’re back, let me give you a brief background on why and how this started. For months, my teammates Andrea Lacche , Pradeep, and I have been working on analyzing New York City’s noise landscape as part of a class project( 311 Noise complaints data ). The goal was to analyze noise complaints across New York City to better understand the urban noise landscape. We wanted to identify key hotspots and trends, ultimately providing insights into how noise pollution affects different neighborhoods and what measures might be effective in addressing these issues. We uncovered some pretty interesting insights, such as the Bronx having the highest number of noise complaints, particul...

  Understanding Survival in the ICU: How Logistic Regression Reveals Key Insights Imagine you're in charge of an Intensive Care Unit (ICU). Every day, critically ill patients are admitted, each presenting unique health challenges. Your team’s goal is straightforward yet monumental: ensure the best possible outcomes for every patient. But how do you objectively understand which factors most impact survival rates? Enter logistic regression—an accessible yet powerful statistical tool that can help you make sense of complex medical data. Photo by Anna Shvets:  What Exactly is Logistic Regression? At its core, logistic regression is a statistical method used when the outcome you're interested in has two possible categories: such as survived versus not survived, or disease versus no disease. Instead of predicting exact values, logistic regression estimates the probability that an event will happen. For example, it can predict the likelihood that a patient admitted to the ICU will...

  Beauty in the Classroom: What Really Drives Professor Evaluations? ( A data-driven exploration ) A data-driven exploration of how appearance, gender, and other factors influence teaching evaluations Photo by Max Fischer We’ve all been there at the end of a semester: faced with those standardized evaluation forms asking us to rate our professors. Most universities consider these evaluations essential for tenure decisions, promotion, and even annual performance reviews. But what factors are truly being measured in these evaluations? Are they valid indicators of teaching effectiveness, or are they influenced by factors entirely unrelated to a professor’s teaching abilities? In this article, I’ll dive into an analysis of real evaluation data from the University of Texas at Austin to uncover what’s actually driving student ratings. The results may surprise you ,and make you think differently about those evaluation forms. The Dataset: Beauty and the Professor The data comes f...

  Decoding the Numbers: How Linear Regression Reveals Hidden Relationships image by Artem Podrez Have you ever wondered if taller people really do have broader shoulders? Whether consuming more calories at Starbucks means consuming more carbs? Or if more attractive professors actually get better teaching evaluations? These are more than just idle questions. They touch on fundamental patterns in nutrition, human physiology, and even unconscious bias in education. Beneath these questions lies a powerful statistical tool that can help us uncover meaningful relationships in data: linear regression. In this article, we’ll explore how linear regression works, when to use it, and what it can tell us about the world around us. Using three real-world examples, we’ll see how this technique allows us to predict one variable from another and quantify just how strong these relationships really are. What Is Linear Regression, Really? At its heart, linear regression is a way to describe how ...