Kabir's Tech Dives
I'm always fascinated by new technology, especially AI. One of my biggest regrets is not taking AI electives during my undergraduate years. Now, with consumer-grade AI everywhere, I’m constantly discovering compelling use cases far beyond typical ChatGPT sessions.
As a tech founder for over 22 years, focused on niche markets, and the author of several books on web programming, Linux security, and performance, I’ve experienced the good, bad, and ugly of technology from Silicon Valley to Asia.
In this podcast, I share what excites me about the future of tech, from everyday automation to product and service development, helping to make life more efficient and productive.
Please give it a listen!
Kabir's Tech Dives
⚠️ Synthetic Data: Limitations and Implications for AI
Synthetic data is useful for AI training but has limitations. Over-reliance on it can lead to model collapse, bias amplification, and a failure to capture real-world complexities. This can erode trust in AI systems and stifle innovation. The article suggests a balanced approach, combining synthetic and human-sourced data, along with tools for data provenance and AI-powered filters. Partnering with trusted data providers and promoting digital literacy are also crucial for responsible AI development.
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