Okay, I’ll admit it I just needed an excuse to finally buy a Mac Mini (been wanting one for way too long).

The serious answer though: some workflows really do benefit from a device like this especially when you’re trying to avoid website rate limits or need to integrate with actual macOS apps. It’s not quite the same comparison as a Raspberry Pi for that reason.

Bonus: I’m running local inference for the tool directly on the Mac Mini using LM Studio. For compute per dollar, that’s honestly some of the best value out there.

Reflections from a week of extremely human conversations about AI:

There are a lot of reasons why I believe AI will not replace humans but one of the main ones is that it doesn’t matter how much you have in common with any one person; human interaction almost always leads to non-linear thinking. And that’s largely because while we all have humanity in common we all have a unique set of experiences.

To put it in more machine learning centric geeky terms:
Humans have all the same underlying “statistical model” but we all have uniquely different “training data” and that is what leads to a world where each of our own’s training data leads to us uniquely different “optimization functions”.

Quite frankly that’s what makes startups unique, cities dynamic and things fun.

Looking forward to exploring even more training data in upcoming conversations.

Happy Pi Day! For those who celebrate 🤓!

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I will attend and present at #BSidesOrlando for the first time in just one week. As you know, I'm passionate about data, analytics, privacy, and security; my goal for this presentation is to shed new light on Machine Learning Security and try to encourage more people to look at this problem space. Here are the key takeaways you should expect to get from this presentation:

- The traditional software supply chain is fairly challenging, but for ML, there are even more elements and complexities: Models and Modeling, Data and Runtime / Serving of those models.
- While you will hear otherwise, many of the ML Security Problems are not too far from traditional Secure Software / Application Development and IT Operations; there are just a few extra moving pieces to be mindful of.
- ML Security poses unique challenges and requires not just security people but machine learning engineers to solve them. We need more people thinking about and solving these problems as technology rapidly adapts.

If you are attending BSidesOrlando, I hope we get the opportunity to meet there and hope you can attend this talk; if you are not and the above is something you are interested in, care about, or have strong opinions about, I'm looking forward to catching up with you to make sure I get your perspective in this presentation. Because who doesn't like editing slides 10 minutes before the talk 😁.

#Cybersecurity #MachineLearning #AI #Data