If you’ve spent any time on social media recently, you’ve probably seen the trend: people uploading selfies to AI services that render them as retro action figures sealed in plastic blister packs. The results are undeniably creative—quirky accessories, heroic stances, vintage fonts. It’s nostalgia wrapped in AI-powered novelty. But beneath the fun lies a growing […]
Artificial Intelligence has become synonymous with Generative AI in recent years. Whenever AI is discussed in public forums, mainstream media, or boardroom meetings, the focus is almost exclusively on chatbots, image generation, and large language models like ChatGPT. While these technologies are indeed impressive, they represent only a fraction of the vast AI landscape. AI
Not All AI is ChatGPT! Read More »
The world of investing has always been a numbers game, but in the age of AI, those numbers are being processed at an unprecedented scale and speed. Financial markets generate vast amounts of data every second—price movements, trading volumes, earnings reports, economic indicators, and news sentiment. AI is transforming how investors analyze this information, identify
How AI Powers Smart Investing Read More »
The phrase “data is the new oil” has become a common metaphor in the digital economy, emphasizing data’s immense value as a driver of business and technological innovation. However, like crude oil, raw data in its unprocessed form is not inherently useful. Just as oil must undergo refining before it can power industries, data must
Data is the New Oil, but Not All Oil is Refined Read More »
In today’s digital world, real-time data streaming is no longer a luxury—it’s a necessity. Businesses and AI-driven applications thrive on instant insights, requiring robust data pipelines that can process and react to events as they happen. Apache Kafka and Apache Flink form the backbone of modern real-time data processing, enabling seamless data flow, low-latency analytics,
As we have explored in the previous parts of this series, high-quality and real-time data are essential for AI and ML applications. Now, let’s take a deeper look into how to implement real-time data products effectively using Apache Kafka and Apache Flink. This part focuses on two crucial features of Flink that enable reliable and
Implementing Real-Time Data Products with Apache Kafka and Apache Flink (Part 3) Read More »
Building and maintaining data products for AI and ML is not just about collecting data—it is about ensuring data quality, scalability, and accessibility. Without addressing these challenges, AI models will produce unreliable results, and organizations will struggle to use data effectively. Two of the biggest challenges in this area are data quality and scalability. Ensuring
Challenges in Building and Maintaining Data Products for AI and ML (Part 2) Read More »
I still remember the days in the early 2010s, when the term „big data“ was widely discussed in the tech industry. Companies were encouraged to collect as much data as possible, seeing it as a key resource (or the new oil as we called it those days) for the digital economy. However, focusing only on
What Are Data Products and Why Do They Matter for AI and ML? (Part 1) Read More »
The AI landscape is undergoing a seismic shift, and at the epicenter is DeepSeek—a $6M Chinese AI startup that has achieved what Silicon Valley deemed impossible. In doing so, it has wiped $2 trillion off the market capitalization of U.S. tech stocks, with NVIDIA alone losing over $500 billion. This is not just a story
The $6M AI Startup or how to erase $2 Trillion worth of Market Cap Read More »
Generative AI (GenAI) tools, such as ChatGPT or other large language models (LLMs), are hailed as groundbreaking innovations for generating human-like responses to diverse prompts. They excel at mimicking natural language, summarizing information, and even assisting with creative tasks. However, their technical foundation raises significant concerns about their suitability as reliable tools for learning and