Evidence receipt / recommendation
Published · transcript-backedLiva Ralaivola: recommendation
9 May 2026 The Cognitive Revolution Milliseconds to Match: Criteo's AdTech AI & the Future of Commerce w/ Diarmuid Gill & Liva Ralaivola
“We have more scientific papers because we have researchers doing AI science and publishing in conferences and everything ties up together. And if you want to know more, if you want to dig deeper, if you want to know the sizes of the models, how we train them, what are the losses that we use, we have a bunch of articles online that you can totally download and read to have more information.”
Source trail
Everything needed to verify it.
- Speaker
- Liva Ralaivola
- Attribution
- Verified speaker
- Claim type
- recommendation
- Recorded
- 9 May 2026
- Publisher
- The Cognitive Revolution
Transcript context
…To be accurate, to be fast, and then also to do it billions of times a day, right? At huge levels of stability and reliability. And then the other thing that's a great challenge within our system is when you have the Black Friday, Cyber Monday, the busiest period of the year, So imagine any world in where your piece of technology, you are able to run it at like 300% of what you normally run. Imagine taking your car and running it for one week at 300 miles an hour and then back to normal for the rest of the year. And it's the same car, same machinery, and it has to perform exactly the same way. That sounds like a challenge. It's fun. Great challenge. And the engineers behind it, my hat goes off to them. It's the work they do. One thing for the people listening and for you is that one thing that is important for us is also to share how we are machine learning. You can access blogs that explain the deep KNN methodology and that explain a relevancy for the written media business, and we want to go even deeper. We have more scientific papers because we have researchers doing AI science and publishing in conferences and everything ties up together. And if you want to know more, if you want to dig deeper, if you want to know the sizes of the models, how we train them, what are the losses that we use, we have a bunch of articles online that you can totally download and read to have more information. Yeah, I was, of course, reading some of that ahead of this call, and it's super cool to see how you guys have made that both public, but also pretty easy to understand for, you know, I'm not a true technical person, and it was totally easy to follow. AvePoint is building the control layer for AI agents so you can securely govern, audit, and recover every action at scale. Design trusted agentic outcomes from day one at https://avpt.co/tcr…
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