Earley AI Podcast - Episode 93: AI Translation, Brand Voice, and Global Content with Olga Beregovaya

Thanks so much for having me.

So

we start off, I like to talk about what people don't understand, the misconceptions and about AI and specifically your space.

When you talk to executives and technology leaders about AI translation, what do they most consistently get wrong? Okay.

The first thing that's gotten wrong most consistently is looking at the price sheet for commercial provider tokens and just saying, hey, why can I just not pay, whatever, let's say $7 per million tokens and call it a day, plug it into my ecosystem? So I guess a lot of people just get mesmerized by the price and do not realize the complexities behind.

And that's actually one of the most frequent conversations that we're having with executives and say C-suite executives, senior leadership executives.

Like guys, yes, you can totally consume your million tokens at a super low price point, but what exactly are you buying for this money? So I guess the simplicity and accessibility and like everything is available right now and I could just do it myself within a day.

That's probably the biggest one.

And how do you really illustrate that? How does that manifest itself? And one of the things that we talk about is the need for information architecture when it comes to artificial intelligence.

But there are instances where you don't need it, right? You can drop 400 PDFs into a SharePoint repository.

You can run...

You can run Copilot against it and you can get some answers.

And of course, there are use cases like that, right? And my answer to that is, well, what would have worked without that any curation or any information architecture for Copilot would work with full-text search because it's curated content.

It's not messy content.

It's usually a well-maintained application.

This happened to be about standard operating procedures.

So you have to concede that argument that sometimes it's okay to not have IA for your AI.

When is it okay to do the simple way? What are the use cases where that argument is reasonable?

My message, and that's what I usually share, is just separate branded content from versus not branded content.

In other words, if it's a content that represents your brand, and if it's outbound content that represents your brand, and you're super sensitive to your brand tone and voice in the market, then co-pilot is not a good idea.

And I'll actually use a specific example.

So if it can carry any kind of potential brand damage or If it can carry any liabilities with it, and a great example would be, for instance, CROs or any kind of documents in regulated industries like life sciences, like pharma, right? You can do it, but why would you if it can potentially bring about a lawsuit? And that's the last thing you want.

So that's the no, that's the no.

So the converse of that to say when it does work is when you have more pedestrian content that doesn't impact the brand.

It's not branded content.

Thanks so much for having me.

So

we start off, I like to talk about what people don't understand, the misconceptions and about AI and specifically your space.

When you talk to executives and technology leaders about AI translation, what do they most consistently get wrong? Okay.

The first thing that's gotten wrong most consistently is looking at the price sheet for commercial provider tokens and just saying, hey, why can I just not pay, whatever, let's say $7 per million tokens and call it a day, plug it into my ecosystem? So I guess a lot of people just get mesmerized by the price and do not realize the complexities behind.

And that's actually one of the most frequent conversations that we're having with executives and say C-suite executives, senior leadership executives.

Like guys, yes, you can totally consume your million tokens at a super low price point, but what exactly are you buying for this money? So I guess the simplicity and accessibility and like everything is available right now and I could just do it myself within a day.

That's probably the biggest one.

And how do you really illustrate that? How does that manifest itself? And one of the things that we talk about is the need for information architecture when it comes to artificial intelligence.

But there are instances where you don't need it, right? You can drop 400 PDFs into a SharePoint repository.

You can run...

You can run Copilot against it and you can get some answers.

And of course, there are use cases like that, right? And my answer to that is, well, what would have worked without that any curation or any information architecture for Copilot would work with full-text search because it's curated content.

It's not messy content.

It's usually a well-maintained application.

This happened to be about standard operating procedures.

So you have to concede that argument that sometimes it's okay to not have IA for your AI.

When is it okay to do the simple way? What are the use cases where that argument is reasonable?

My message, and that's what I usually share, is just separate branded content from versus not branded content.

In other words, if it's a content that represents your brand, and if it's outbound content that represents your brand, and you're super sensitive to your brand tone and voice in the market, then co-pilot is not a good idea.

And I'll actually use a specific example.

So if it can carry any kind of potential brand damage or If it can carry any liabilities with it, and a great example would be, for instance, CROs or any kind of documents in regulated industries like life sciences, like pharma, right? You can do it, but why would you if it can potentially bring about a lawsuit? And that's the last thing you want.

So that's the no, that's the no.

So the converse of that to say when it does work is when you have more pedestrian content that doesn't impact the brand.

It's not branded content.