Artificial IntelliTools

  Can artificial intelligence predict what will go viral? I built three neural networks to find out—and discovered something surprising about the limits of machine learning. The Challenge: Finding the Next Viral Hit Imagine you're an editor at a major online publication. You publish 50 articles today. Some will get 500 shares. A few might explode to 50,000. Most will land somewhere in between. The million-dollar question: Can you predict which articles will go viral before you invest your marketing budget? This isn't just an intellectual exercise. For publishers like Mashable, BuzzFeed, or Medium, getting this right means: Promoting the right content at the right time Maximizing return on advertising spend Understanding what resonates with audiences I set out to answer this question using neural networks and real data from 39,644 Mashable articles. What I discovered challenges everything you might assume about AI and prediction. The Data: 39,644 Articles, 60 Feat...

My first academic conference shattered a myth, and I finally understood why representation isn’t just a buzzword.  The Wake-Up Call I recently attended the IEEE/ACM CHASE 2025 conference on connected health. As someone from Africa, I used to imagine presenters at these events as superhuman geniuses – aliens operating on a level I could never reach. Their papers seemed like cryptic manuscripts; their presence felt untouchable. But after three days immersed in this world, my naivety was peeled away like old paint. The Revelation The room was filled with brilliant minds – 80% Asian, 20% White, and a scattering of others. Including me, there were nine Black attendees among 140 participants. As I listened to presentations, something struck me:  Their work was identical to what I’d done in my graduate classes.  The same formula: Pick a topic  (like we do for projects). Find a dataset  (hello, Kaggle!). Identify a problem  (standard research 101). Propose a soluti...

  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...

  How Humans Have Tried to Explain, formalize, and understand the World Around Them Over Time. "For much of human history, we were like the LLMs, figuring things out by matching patterns in our minds." - Stephen Wolfram Humans have been trying to understand the world around them for centuries. We have used a variety of models to explain the natural world, including structural models, mathematical models, computational models, and multicomputational models. All these, in my view, contribute to what we can collectively call Intelligence and kind of paint an interesting picture of human intelligence, how it has evolved over time, why it's different from other forms we see in the world, and why our attempt to model out intelligence is going to be an interesting journey to watch. Antiquity Structural models - It's all about what things are made of. They were developed in antiquity and are based on geometric elements. These models do not consider time explicitly and are ba...