The Didi & Lital Show

Should You Care About the Cranes?

There is a fear that Chinese-manufactured cranes could be controlled by the Chinese and used to stop or slow U.S. production. Didi and Lital talk about whether this and similar concerns are legit or overblown.

Deepfake and Security

Deepfake is a real threat. So why aren't we taking typical measures of security to stop fraud?

Securing Your Smart Home

Didi and Lital are moving into a new home, and a "smart" one at that. What are their plans for security?

The Constant Fear of Data Loss

How can companies avoid data loss? Didi and Lital discuss the various concerns and solutions.

The Importance of Subtleties

Didi and Lital explain that hyperbole is doing us all a disservice, and that a generation may not have any sense of subtleties.

The Specter of Low-Code/No-Code Software

Low-code, no-code software development: you don't need to know legit coding to be able to build software. When is it appropriate to use these tools? Are they helpful? Are there risks in using them -- and how should people starting startups today think about it?

If You Tolerate This, Your Children Are Next

Didi and Lital - with special guest Leia - discuss the major flaws in the Newton, MA school system and how important it is to stand up to institutions.

Stop Using Security as an Excuse

Didi, Lital and special guest Leia say that people need to stop using security concerns as an excuse to avoid moving forward.

Gen Z’s Take on Cybersecurity & Social Media

Didi and Lital are joined by a special guest - their daughter Leia - to discuss the way Gen Z deals with security issues connected to social media. Leia knows what malware is -- but do her peers?

Explaining Algorithmic Biases

As life in an AI world becomes more driven by algorithms, or "statistical inferences," the way those algorithms are being built and trained and the data that is being fed into them will influence the results. Didi and Lital talk about the concern that some of those algorithms, or potentially all of them, will have biases. We all have biases. So at the end of the day, outcomes may have biases.