If your name is John Smith, and you prompt Gemini to act as a robust OSINT tool, you will experience the vicissitudes of Chaps firsthand as the tool normalizations of vector space yields an answer that will not only never get close to identifying you because it has lumped several John Smiths together like asking a dog to fetch your shoes and it comes back with a Footlocker in its mouth.
No, not really. That's pretty basic stuff. You would do well in reading up on the shared responsibility model. Customers are responsible for setting up their own infrastructure, and platform/service providers are only responsible for the services they manage. Even then, stuff like persisted data is still recoverable by design.
But you are absolutely responsible for the service you put together. This is a basic principle for around two decades. Infrastructure as code tools are pervasive and ubiquitous for over a decade.
Correct me if I’m wrong, but from my experience in this space in order for a model to exercise judgment it must force itself to operate in a strict chain of thought mode. Since all LLMs are predictive creatures, I started to care a lot more about my judgment settings, the transparency of them, and the presence of a judgment loop in either the development or functionality of an application built these days.
Not exactly sure where I’m going with this, but my work with creating penetesting tools for LLMs, the way that I use judgment is critical to the core functionality of the application. I agree with your concern and I will just say that the more time I spent concerned with chain of though where now I will make multiple versions of the same app using a different judge set a different “temperaments” and I found it to be incredibly enlightening as to the diversity of applications and approaches that it creates.
Even using BMAD or superpowers, I can make five versions of an app without judges involved and I feel like I’m just making the same app five times because the API begins to coalesce around the business problem you want to solve. The vicissitudes of prediction tools always want to take the safest bet for the greater good, but with the judge involved we can make the agent force itself to actually be hostile about what exactly we’re trying to do, which has produced interesting and fun results.
Not notepad++!
(Opens WhatsApp)
OpenClawd express my discontent across all my channels and draft an email to send to IT tomorrow morning. Also turn off the lights off and go to bed.
(Somewhere in china, all the lights go out)
There is capital “A” Active Listening, which is in a family of behavior modification techniques in which the interviewer can follow the aforementioned scripts to increase engagement…
And lowercase active listening, IMHO is genuinely being interested in the experiences of the person talking that your line of questioning disarms the subject into sharing stories that add personal, “cultural” context to their choices which could be considered taboo.
Beautifully said. I believe wholeheartedly that in real life, disagreements between two people hinge on an ability to disarm each other through charm and disposition. The less you know someone, and the more they appear to earnestly try to understand you - becoming heated and firing phasers just feels unbecoming; why would I perpetuate personal loneliness or ennui in a moment that is genuinely devoid of it?
