MapReduce, every mention
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tap a year for its mentions
every year anyone Christopher Nguyen 8Vijay Pande 3Ion Stoica 3Steven Sinofsky 2Mike Matchett 1
Verbatim, from the transcripts: the passages where MapReduce comes up
Beyond Leaderboards: LMArena’s Mission to Make AI Reliable
- ▶ 43:21 Ion Stoica MapReduce, Google file systems, all of that happening at Google.
a16z Podcast | A New Lab Rises
- ▶ 11:09 Ion Stoica If you think about the MapReduce and Google File System, which really started as a big data movement. 2 times in the scene
a16z Podcast | The Strategies and Tactics of Big
- ▶ 17:09 Steven Sinofsky If Google wants to replace MapReduce with some new thing, or if they are going to roll out, like, a new way of doing machine learning internally, they'll work on that for the same amount of time that Apple works on a phone.
a16z Podcast | The Storage Renaissance
- ▶ 13:28 Mike Matchett When you had Hadoop and MapReduce, they could partition certain categories of problems and run them in parallel, but not really a lot of machine learning algorithms.
a16z Podcast | A Conversation With the Inventor of Spark
- ▶ 0:57 unnamed speaker Before Spark, the most widely used system was probably MapReduce, which was, uh, uh, invented at Google and popularized through the, the open source Hadoop project. 7 times in the scene
a16z Podcast | The Cool Stuff Only Happens at Scale
- ▶ 1:41 Vijay Pande But you can't do MapReduce with everything. 2 times in the scene
- ▶ 6:21 Vijay Pande I think I've gotten people thinking about this, and MapReduce and things like that, those abstractions have played a huge role.
a16z Podcast | Making Sense of Big Data, Machine Learning, and Deep Learning
- ▶ 11:41 Christopher Nguyen Uh, so big compute is the first example of the compute you can think of is MapReduce. 8 times in the scene
a16z Podcast | Why the Datacenter Needs an Operating System
- ▶ 0:23 Steven Sinofsky There are things like Kafka and Spark and MapReduce and Cassandra, and it's super, super