why aren't all 23 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Assertion Not checkable as stated
Ghodsi: Early Big Tech achieved AI breakthroughs using 1970s algorithms with massive data
“What they were doing is they were taking those algorithms from the seventies that do not work, but they were applying orders of magnitude, more data to it. So a lot of data on modern hardware, and they were getting superhuman results.”
Assertion Supported
Uber dropped Google Maps for Foursquare to power venue search
“If you use Uber and you say, like, I, you know, please pick me up at the, you know, Regency Cinema in Tribeca and take me to the Starbucks on 27th street, rather than typing addresses, That's all powered by Foursquare's global data set and they moved off Googl…”
Opinion
Ehrenberg: Early marketplace startups like Uber and Airbnb are not super tech-intensive
“Those businesses themselves are not super tech intensive, right? They're just leveraging very basic building blocks”
Opinion
Horowitz: Uber had a 'very compelling culture' under Travis Kalanick
“Uber had a very compelling culture under Travis with a very bad issue.”
Assertion Supported
Golde: Uber drivers average 0.6 to 0.8 empty miles per passenger mile
“We look at some of our competitors, specifically Uber, there's a paper published again, either late last year or earlier this year, showing how many miles they ride empty on average for every single passenger mile that they do, and it's about between . Six and…”
Assertion Not checkable as stated
Uber deployed trip similarity algorithms to fight incentive fraud in China
“Uber used to run this incentive program in China, and, ah, people are trying to game it, so they used to always have, like, similar trips simulated From their, ah, various different devices. So what we did was actually, like, try to find an algorithm where we …”
Assertion Contradicted
Liu: Uber and Instabase use LlamaIndex for enterprise data applications
“We've seen people build these workflows at different settings from, for instance, like hacks on projects at startups building, for instance, like track GPT, like, plugin over, like, your Slack or your Notion all the way to kind of, like, bigger companies, for …”
Opinion
Sarah Guo considers Uber a machine learning company
“I'd argue Uber is an ML company because they use it for demand management and pricing and everything else.”
Assertion Not checkable as stated
Tech giants like Google and Uber rely on home-rolled ML infrastructure
“Most of the tooling is kind of home rolled. Best practices haven't emerged yet. We're seeing a lot of, especially large companies, roll their entire own stacks. So Facebook has FB Learner, Google has TFX. Uber has Michelangelo. Airbnb has Big Head.”
Insight
Bhardwaj: Great platform businesses succeed by expanding total market supply
“If you look at any good platform, Like Uber or Airbnb, it's not that they made life convenient, but they also increased the supply of things. Like with Airbnb, the supply of hotels or supply of basically places you can find significantly increases, or with Ube…”
Assertion Supported
Foursquare location technology powers Apple Maps, Uber, Bing, and 100,000 others
“We power a lot of the location inside Bing. We power a lot of Apple Maps around the world. If you search in Uber or Tencent, Pinterest, and Snapchat, Samsung, Twitter, Garmin, these are among the 100,000 companies that now are using this technology set.”
Assertion Not checkable as stated
Murugesan: Uber practically had no data infrastructure when he joined in 2014
“We practically did not have an infrastructure is what the honest reality is.”
Insight
Schemaless JSON fails as companies scale beyond 50 employees
“It works well, like, if you're, like, a ten-person company, or, like, even to a fifty-person company, when you're, like, scaling to, like, thousands of people, like, you actually need a proper negotiation in between.”
Assertion Supported
ClickHouse counts Spotify, Netflix, Disney, and Uber as customers
“We are taking this very powerful analytical database that's used by companies like Spotify and Netflix and Disney and Uber and eBay and Cloudflare, and we're building a managed service in the cloud that we're calling ClickHouse Cloud.”
Assertion Supported
Katz: Uber adopted ClickHouse for logging infrastructure to lower costs
“They were evaluating a variety of technologies for their logging infrastructure for their logging platform, which is being used by hundreds of developers every day for a variety of analytical workloads. And the current technology presented a bit of a cost. Con…”
Assertion Not checkable as stated
Murugesan: City operations personnel constitute most of Uber's data consumers
“Most of Uber's data consumers are actually these operations people.”
Assertion Not checkable as stated
Uber transitioned from ETL into Vertica to EL into Hadoop
“We went from an ETL model, where we scraped from, like, the original source, transformed the data and loaded to Vertica, to, like, just an EL model, where we just, like, just copy the data as soon as possible into, like, Hadoop, and all the transformation can …”
Assertion Not checkable as stated
Uber consolidated all log and business data into an HDFS data lake
“What we really created was, like, using HDFS, like, a data lake, where we basically copied the whole data sets from, like whatever we get from, like, analytical logs or, like, all our business data sources, too, into HDFS.”
Assertion Not checkable as stated
Uber engineers frequently crashed Kafka clusters with unthrottled Spark executor writes
“Kafka was, in general, like, a nice way where people used to pipe the results of, like, their Spark jobs. But often cases, what they do is, like, they hit Kafka hard and bring Kafka down because they're trying to, like, actually send data from, like, hundred e…”
Disclosure
Uber uses cost accounting chargebacks to track data storage costs by unit
“We have something called cost accounting chargebacks is what we call it. So we actually try to, we have a lineage model where we try to figure out who's storing the data. And, ah, we actually kind of can go get a dollar amount of what we are storing.”
Assertion Not checkable as stated
Streamific powers all data ingestion and aggregation at Uber
“There's a system called Streamific, which powers all of the data ingestion aggregation at this point.”
Assertion Supported
Narkhede: Apache Kafka is used by thousands of companies worldwide
“Since we open sourced it, you know, roughly five years ago, Kafka is used in thousands of companies worldwide, from Uber, and LinkedIn, and Netflix, all the way to traditional enterprises like eBay, and PayPal, and Cisco, and Goldman Sachs.”
Assertion Supported
Tan: Sift Science has 25 employees and 175 customers including Twitter and Uber
“We have 25 people out in San Francisco just closed our Series B recently, and we have about a 175 customers around the world, including Twitter, Square, Match.com, OpenTable, Uber, Airbnb, Kickstarter and others.”