Hernan de Lahitte's blog

MIT’s AI Risk Repository reveals over 700 identified AI vulnerabilities, with many cybersecurity threats still flying under the radar. From data poisoning to adversarial attacks, these risks expose glaring gaps in our current safety measures. Are we prepared to defend against these evolving AI threats?
Explore the full findings here:

This project aims to develop a noise cancellation system using a Generative Adversarial Network (GAN). The goal is to take a noisy audio file as input, generate the inverse waveform, and combine the two signals to achieve noise cancellation (i.e., producing silence). The project is implemented in Python, using libraries like PyTorch, Librosa, and Matplotlib, and includes the option for API integration (e.g., OpenAI or Google AI) for advanced audio processing.

Check out this AI-generated version of "me" leaping over mountains like a parkour pro! 😂

P.S. My real trail runs involve a lot more huffing, puffing, and just a bit fewer cliffs. Safety first! 🏃‍♂️🏔️

After many frustrating technical interviews that overlooked my extensive experience and my current context, I share my insights on why we must modernize our hiring practices. It's time to leave the abacus behind and embrace the future of hiring!

If you already played with new Semantic Logging Application Block which I strongly recommend if you are using the new typed events in NET 4.5, perhaps you have noticed the wide extensibility provided in both in-process and out-of-process scenarios. 

So you were reading some good tutorials on how to write your first typed event class but for some reason it may not work as expected? (Or many other issues as well)

Finally the latest version of Enterprise Library 6.0 (and almost a decade of evolution from the first block).

 Finally the Semantic Logging CTP from Enterprise Library 6.0 is out.