MachineLearning

“We have very little time to get people ready for it, businesses ready for it…” — Kristalina Georgieva, head of the International Monetary Fund A few days back, OpenAI unvelied GPT-4o, Google unvelied Gemini Pro 1.5. I’m at a loss of words for how fast GenAI is progressing. It feels like just yesterday we were marveling at how tools like ChatGPT made learning, coding, and even creative writing a breeze, and now we have GPT-4o and Gemini 1....

Concerns about Transparency and Bias Lately, there’s been a growing skepticism about the ethics behind AI, and it’s easy to see why. For one, transparency is a significant issue. Many AI systems, especially the more advanced ones, operate like black boxes. It’s difficult to understand how they make decisions, which raises questions about accountability and trust. Bias in AI is another major concern. These systems learn from data, and if that data is biased, the AI will be too....

I recently completed the Self-Driving Cars Specialization by the University of Toronto. While the course provided a comprehensive overview of autonomous vehicle technology, I wanted to delve deeper into the computer vision aspect. To gain hands-on experience, I developed a lane line detection program. This project involved: Image Processing: Applying filters and transformations to isolate lane markings from the surrounding environment. Edge Detection: Utilizing algorithms to identify the boundaries of the lane lines....