How Experts Use Decades of Knowledge: Content, Context, Consequence

A discussion with Octave’s Prashant Darisi and Vick Vaishnavi

Speaking with experts who love their jobs usually makes you aware of two things simultaneously: 1) how much you don’t know, and 2) how much you’d like to know. My conversations with Prashant Darisi and Vick Vaishnavi were no exception. I walked away with an appreciation for the decades of expertise, knowledge, and experience behind Octave’s key players, and a more solid understanding of how these elements have developed a human-centered AI platform that doesn’t replace human potential so much as magnify it.

This, in a world where many big companies are tempted to prioritize monetary gain as they skim over the details, is not only a point of principle but a distinct advantage in terms of quality.

How? For one thing, there’s no shortage of people providing the data and context to keep AI in check (ask Vaishnavi), and for another, the tasks involved are inherently more connected and supported by a wide range of professionals and operational use standards than ever (ask Darisi).

I began with general questions.

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Comments

cool advert

It really feels a type of way when someone is selling you something by pretending to empathise with the world you live in, while betraying that they've never lived there themselves. The anecdotes all exude a cargo cult understanding of quality management.

"There are many people who can quantify risk on a scale of zero to 10."

"And then I have a QMS that tells me, oh, your quality’s up, down, etc."

"You may do a root cause and realize, hey, it’s how we built it and assembled it that was a problem, the way we were doing it to specs. And then the build guys will say, geez, we only did what you told us. It was functions as design. [sic] So you know what? It’s really a design problem. So to navigate this little loop, if you will, between the design, build, operate, protect, you really want it to be a continuous improvement cycle."