in aggregate
US /ɪn ˈægrəgət/
・UK /ɪn ˈægrɪgət/
C1
adv. phr.Considering everything together as a total amount.
The sales, in aggregate, exceeded expectations this quarter.
Video subtitles
But how do AI images and videos actually work? | Guest video by Welch Labs
- Although the direction of our 100th step is chosen randomly, there will be some signal in aggregate for our model to learn from here.
Although the direction of our 100th step is chosen randomly, there will be some signal in aggregate for our model to learn from here.
Code Rush: Netscape Mozilla 紀錄片 1998 - 2000 （中文字幕）
- and it's certainly, in aggregate, the highest-paying field of its size.
and it's certainly, in aggregate, the highest-paying field of its size.
- And it's certainly in aggregate,
And it's certainly in aggregate,
Machine Learning: Google's Vision - Google I/O 2016
- Is any of that going to advertisers in any way, even in aggregate, hey, this is a person who seems to like dogs?
Is any of that going to advertisers in any way, even in aggregate, hey, this is a person who seems to like dogs?
- even in aggregate, hey, this is a person who
even in aggregate, hey, this is a person who
VR at Google - Google I/O 2016
- These developers, in aggregate, produce games that are downloaded six to seven hundred times per second, 1.6 billion times per month.
These developers, in aggregate, produce games that are downloaded six to seven hundred times per second, 1.6 billion times per month.
- These developers in aggregate produce games
These developers in aggregate produce games
How Artists Are Rewriting AI’s Future | Fei-Fei Li, Holly Herndon and Mat Dryhurst
- We were really building things from the ground up, which required questions like, "What's your dataset?" AI models are actually just us in aggregate.
We were really building things from the ground up, which required questions like, "What's your dataset?" AI models are actually just us in aggregate.
- AI models are actually just us in aggregate.
AI models are actually just us in aggregate.
How to Win With AI in 2026
- And so in a service business, it means you take raw talent, you add training and skills, or you put multiple of these skills together that, when those skills taken in aggregate, are worth more than any of the individuals on their own, right?
And so in a service business, it means you take raw talent, you add training and skills, or you put multiple of these skills together that, when those skills taken in aggregate, are worth more than any of the individuals on their own, right?
- And so in a service business, it means you take raw talent, you add training and skills, or you put multiple of these skills together that, when those skills taken in aggregate, are worth more than any of the individuals on their own, right?
And so in a service business, it means you take raw talent, you add training and skills, or you put multiple of these skills together that, when those skills taken in aggregate, are worth more than any of the individuals on their own, right?
「機械学習」って何？ コンピューター科学者が5段階のレベルで説明 | 5 Levels | WIRED Japan
- It's also important to realize that people in aggregate are actually pretty predictable.
It's also important to realize that people in aggregate are actually pretty predictable.
- It's also important to realize that people in aggregate are actually pretty predictable.
It's also important to realize that people in aggregate are actually pretty predictable.
Introducing Dagster+ : Beyond traditional orchestration
- And Dagster Plus Insights allows understanding the results of asset checks in aggregate.
And Dagster Plus Insights allows understanding the results of asset checks in aggregate.
- And Dagster+ Insights allows understanding the results of asset checks in aggregate.
And Dagster+ Insights allows understanding the results of asset checks in aggregate.
What Makes The Perfect Business (5 Things)
- And then the second is the revenue retention piece, which is: if you made $100 from those customers in aggregate in January, how much do you make from that same cohort or group of customers today?
And then the second is the revenue retention piece, which is: if you made $100 from those customers in aggregate in January, how much do you make from that same cohort or group of customers today?