Amazon, every mention
43 scenes (2025), the whole family · ← back to Amazon
tap a year for its mentions
every year 2025 anyone Matt Turck 122Benedict Evans 33Bob Muglia 25Spencer Kimball 18Prat Moghe 18Evan Kaplan 16Justin Borgman 15Tristan Handy 14Nate Stewart 13Aaron Katz 13
Verbatim, from the transcripts: the passages where Amazon comes up
AI That Ends Busy Work — Hebbia CEO on “Agent Employees”
- ▶ 12:02 George Sivulka Amazon is a perfect example of how this happened, how org design shaped what they built.
- ▶ 12:08 George Sivulka If you look at AWS's offerings, every single offering in that big menu is a different startup altogether with its own GM.
- ▶ 31:48 George Sivulka Yeah, we, we, we've got partnerships with OpenAI, but also Anthropic, and also, you know, Amazon, so we're, we're playing the field.
AI Eats the World: Benedict Evans on What Really Matters Now
- ▶ 5:01 Benedict Evans Or, you know, it's just an AWS wrapper.
- ▶ 29:10 Benedict Evans Um, the, the, the analogy that's been floating around, I think, is, is to, is to compare this with AWS, in the sense that AWS was a sort of an order of magnitude change in how easy you could get a startup out of the door.
- ▶ 30:44 Benedict Evans So, you know, there's make it a commodity, which is Amazon and Meta strategy. 2 times in the scene
- ▶ 40:35 Benedict Evans And it's interesting, you look at or listen to the conference calls, you know, and I'm sure you've done the chart, you've missed the chart of the CapEx, where like, Google, Meta, um, AWS, not Amazon overall, AWS only, and, um, and, and, um, 3 times in the scene
- ▶ 40:35 Benedict Evans And it's interesting, you look at or listen to the conference calls, you know, and I'm sure you've done the chart, you've missed the chart of the CapEx, where like, Google, Meta, um, AWS, not Amazon overall, AWS only, and, um, and, and, um, 7 times in the scene
- ▶ 42:41 Matt Turck So we, we, uh, in our little, uh, tour, so we talked about, um, Apple, we talked about Google, we talked about AWS, we, we touched upon Meta, uh, a few minutes ago.
- ▶ 54:05 Benedict Evans You could say, well, there's, there's, there's, there's, there's, there's half a dozen different interest graphs because Google and Meta and Amazon and maybe OpenAI have interest graphs around you of different, of different kinds. 2 times in the scene
- ▶ 1:00:44 Benedict Evans At Amazon is like, it has six hundred million SKUs, and it's, or whatever the number is, a number, a number, the number is effectively infinite, and if you, you can, you know, you can do a tour of their fulfillment centers. 6 times in the scene
- ▶ 1:08:09 Benedict Evans There was like a trap with Siri and Alexa, which was that natural language processing worked, so you thought it was AI, and it wasn't.
Jeremy Howard on Building 5,000 AI Products with 14 People (Answer AI Deep-Dive)
- ▶ 29:09 Jeremy Howard It's kind of a bit AWS like, you know, it's,
- ▶ 39:55 Jeremy Howard Yeah, I think, I think it'll be like AWS.
Rewriting Success: What InfluxDB 3.0 Teaches About Scaling—and Scrapping—Your Core Tech
- ▶ 0:27 Matt Turck On the deep tech side, we unpack how InfluxDB obliterates high cardinality bottlenecks, streams straight to S-Tree and Parquet, and why F-Dap might become the next LAMP stack.
- ▶ 1:04 Matt Turck And the strange but exciting day AWS moved from competitor to partner.
- ▶ 1:07 Evan Kaplan Amazon could have forked us. 2 times in the scene
- ▶ 12:17 Evan Kaplan And, and then there are the, you know, there are the fabrics of the world, the redshifts, Athenas, and the big queries, which also have those same dynamics.
- ▶ 12:17 Evan Kaplan And, and then there are the, you know, there are the fabrics of the world, the redshifts, Athenas, and the big queries, which also have those same dynamics.
- ▶ 16:08 Matt Turck So the idea is to live on top of S-III, is that, is that the right? 4 times in the scene
- ▶ 17:42 Evan Kaplan Those are the standards that the lake houses are built on and things like Redshift and, and BigQuery.
- ▶ 25:06 Evan Kaplan Amazon uses it.
- ▶ 29:34 Evan Kaplan I'm already in Amazon. 7 times in the scene
- ▶ 29:35 Evan Kaplan I can use Timestream. 3 times in the scene
Dashboards Are Dead: Sigma’s BI Revolution for Trillion-Row Data
- ▶ 11:28 Mike Palmer So for example, uh, in our world, we needed a Snowflake, a Databricks, a BigQuery, a Redshift,
- ▶ 16:43 Mike Palmer One of the things that I knew before, I was working in infrastructure, and one of the things I knew before joining Sigma was that the price per terabyte of storing data in AWS for five years in a row was -65%.
- ▶ 32:45 Mike Palmer So, I mean, I, I don't think that happens in AWS because AWS has never been good at, uh, end user products.
Box’s Big AI Leap: Aaron Levie on Agents & the Future of Work
- ▶ 24:30 Aaron Levie Um, and Amazon web services didn't launch until like 2 times in the scene
- ▶ 47:08 Aaron Levie Meta and Amazon and those guys.
Snowflake CEO on Winning the AI Arms Race
- ▶ 19:57 Sridhar Ramaswamy It's an Apache project with a set of contributors that come from many places, from Netflix, from Snowflake, from Databricks, from AWS, but it is vendor neutral.
- ▶ 23:40 Sridhar Ramaswamy Snowflake essentially runs in what we call deployments, which you can think as a point of presence in every major data center that AWS and Azure and GCP have.
- ▶ 1:18:34 Sridhar Ramaswamy At the end of the day, we are a smallish public company compared to the likes of Google and AWS and Microsoft, or even OpenAI in terms of how much money we are able to put for things like model training.
From Selfie to Studio: Captions CEO on AI Video for 10M Creators
- ▶ 20:46 Gaurav Misra Siri and Alexa existed at that time.
Trino, Iceberg and the Battle for the Lakehouse | Justin Borgman, CEO, Starburst
- ▶ 17:37 Matt Turck Uh, but in the cloud data warehouses, obviously you have, uh, Snowflake, uh, Redshift, uh, Google BigQuery, uh, in the world of DataLex, uh, who, originally Hadoop, at some point, early Databricks.
- ▶ 29:25 Justin Borgman It is connecting to your storage, uh, so it's your own S three buckets, your own, you know, RDS, your own MySQL database, uh, but the compute and the control plane is managed by us, and so we're able to offer a very seamless, easy to use,…
- ▶ 32:53 Justin Borgman So even if you're just accessing S three and you're going to be querying iceberg tables, 2 times in the scene
- ▶ 49:27 Matt Turck I mean, on there, you, you know, this, uh, you know, uh, certainly better than me, but on there, like a bunch of like iceberg, uh, uh, contributors, like AWS.
Understanding Data Engineering in 2025 | Ben Rogojan, Seattle Data Guy
- ▶ 21:29 Ben Rogojan (Seattle Data Guy) Um, also getting familiar with interacting with cloud, or the cloud, however you want to call it, you know, AWS. 2 times in the scene
- ▶ 39:26 Ben Rogojan (Seattle Data Guy) Like AWS is trying to do their own version.
- ▶ 39:46 Ben Rogojan (Seattle Data Guy) I mean, I think the big thing is that it sets a standard for, for how you're going to end up storing data and interacting with it, which just, you know, instead of, uh, you know, Databricks stores their data in Delta, um, Snowflake stores…
- ▶ 43:14 Ben Rogojan (Seattle Data Guy) Um, not a big Redshift fan. 4 times in the scene
- ▶ 48:48 Matt Turck So not an Azure fan, not a Redshift fan.
- ▶ 50:48 Ben Rogojan (Seattle Data Guy) Um, so I think in those places, you're going to see people pick other tools, or maybe somehow have five different instances of, uh, iceberg, uh, or, you know, maybe they've, one's using Databricks, one's using Snowflake, one's using AWS,…