Tech Talk with Toni

  I can eat sushi with chopsticks! (sometimes) Today's post is inspired by a combination of my experience at a restaurant last night and the latest Bloomberg Technology podcast I listened to. Ordering Sushi x AI Agents! AI is going to remain a hot topic in 2025. But what’s especially exciting is how AI agents are evolving. These are highly autonomous tools capable of making complex decisions without constant human oversight. Think of AI agents as digital assistants who don’t just answer questions but take action on your behalf. They can place online orders, book hotels, send emails, and even manage schedules. For example, you could ask an AI agent to plan a weekend trip. It could find the best flight deals, reserve your hotel, and book dinner at your favorite sushi spot—all without you needing to check multiple websites yourself. But here’s the catch: this all depends on whether the agent understands your instructions correctly. It's easy to mess up orders. Just last night, I...

Wave (noun) - 2nd meaning: a sudden occurrence of or increase in a phenomenon, feeling, or emotion. Homo Technologicus —a term explored in Mustafa Suleyman’s The Coming Wave —captures the essence of humanity’s deep entanglement with technology. Suleyman observes a striking reality: “Our phones are the first thing we see in the morning and the last at night.” Our devices have evolved beyond tools; they are now extensions of our minds and identities.  Consider the device in your hand—it doesn’t just connect you to others but serves as your map, encyclopedia, personal assistant, and entertainment hub.  However, this symbiosis with technology goes far beyond smartphones. Suleyman warns that humanity is at the cusp of a technological wave unlike any before, driven by two core innovations: artificial intelligence (AI) and synthetic biology . Together, they promise godlike powers of creation but pose existential risks if not managed wisely. Artificial Intelligence (AI) AI syste...

Text, image and audio If humans communicated in numbers like computers do, collecting data would be effortless. Imagine : no misinterpretations, no nuances, no contextual layers—just a clean stream of zeros and ones. But, of course, humans are far more complex than binary code. Our communication styles are diverse, emotional, and full of context. We don’t just speak words; we rely on tone, body language, and even cultural cues to convey meaning.  When someone says, “Don’t beat around the bush,” there’s no shrubbery involved—it’s just a colorful way of saying, “Get to the point.” This complexity is both the beauty and the challenge of qualitative data collection. In a world where data is the new oil, having datasets that genuinely reflect how people feel, think, and act is like striking a rich vein of insight.  I once watched a video that jokingly predicted the future of AI.  One of the stages involved “Downloading Human Consciousness.” (see link below) While it was mea...

You can clearly see which one stands out   Today's post is inspired by a question one of my colleagues had around outliers: Are there different types? And to that question, the simple answer is yes! As data professionals, we often encounter data points that stand out like a sore thumb during analysis, leaving us wondering what to do with them. In most cases, deletion seems like the obvious choice.  However, I believe we need to pause and take a closer look at these points before removing them. You see, during Exploratory Data Analysis (EDA for short), asking the right questions about the dataset is crucial to uncovering its full story.  Deleting an outlier just because it stands out can create a narrow, myopic view of the data, limiting the depth and value of the insights you can gain. Rather than rushing to remove outliers, consider what they might reveal. Could they signal an emerging trend, an unusual but important event, or even a data collection issue?  With t...

Pronounced 'seek-will' short for Structured Query Language Like it or not, SQL has been the backbone of data management for decades with 70% of companies use SQL as their primary tool for accessing and analyzing data  (Stack Overflow Developer Survey 2023). My first encounter with SQL was back in 2020, during the pandemic, in a virtual Enterprise Database Systems class. We were writing simple queries, such as SELECT * FROM students WHERE grade = 'A'.  At the time, I thought, “That’s all there is to it? How hard can this be?” By the middle of 2022, I was working with massive, real-world datasets that demanded writing complex queries spanning hundreds of lines of code. Suddenly, SQL wasn’t so simple anymore.  The depth required in professional settings can be overwhelming, but it’s also rewarding. Let me be honest: SQL isn’t my favorite language. But as I’ve learned, you don’t have to love something to be good at it.  (I once disliked Physics, but I still managed to ...

Money grows on trees—the tree is a metaphor for your mind. Defining a problem is the first step to solving it, but have you ever considered the value your solution will create? Before jumping into problem-solving, it's crucial to ask: Is this the right problem to tackle, and is solving it worth the cost? As professionals—especially in tech—it’s easy to fall into the habit of building solutions without pausing to assess whether the effort aligns with the value it delivers. For example, imagine spending weeks building an automated self-watering system for a cactus. Sure, it’s a cool project, but was it really worth the time and resources? After all, a cactus only needs watering once a week, and it would take less than a minute to do it yourself. Sometimes, solving the problem manually is the most effective and resource-efficient option. Your salary is directly linked to the value you bring to a company, and time and energy are finite resources. How we choose to allocate them signif...