"muck" orundifferentiatedheavy liftinganypricedroponewordslidecertificationcounts"elastic"anythingExponentialgrowthchartnewapplicationof AI ininfrastructureacknowledgethe 11/26outagetrottingout an "allin"customerAWSheroesshoutoutbraggingaboutnumber ofregistrationsunintelligibleAWSservice icon"snow"productExabyteshybridcloudWernersays"yeah?"mentionAWSretailmemoriesof VegasEDMbetweenspeakersnew classof EC2instancesunexpectedvirtual"chime-bomb" guestnon-x86processingveiledinsults toOracletrainingdataset"muck" orundifferentiatedheavy liftinganypricedroponewordslidecertificationcounts"elastic"anythingExponentialgrowthchartnewapplicationof AI ininfrastructureacknowledgethe 11/26outagetrottingout an "allin"customerAWSheroesshoutoutbraggingaboutnumber ofregistrationsunintelligibleAWSservice icon"snow"productExabyteshybridcloudWernersays"yeah?"mentionAWSretailmemoriesof VegasEDMbetweenspeakersnew classof EC2instancesunexpectedvirtual"chime-bomb" guestnon-x86processingveiledinsults toOracletrainingdataset

AWS Keynote Bingo - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. "muck" or undifferentiated heavy lifting
  2. any price drop
  3. one word slide
  4. certification counts
  5. "elastic" anything
  6. Exponential growth chart
  7. new application of AI in infrastructure
  8. acknowledge the 11/26 outage
  9. trotting out an "all in" customer
  10. AWS heroes shoutout
  11. bragging about number of registrations
  12. unintelligible AWS service icon
  13. "snow" product
  14. Exabytes
  15. hybrid cloud
  16. Werner says "yeah?"
  17. mention AWS retail
  18. memories of Vegas
  19. EDM between speakers
  20. new class of EC2 instances
  21. unexpected virtual "chime-bomb" guest
  22. non-x86 processing
  23. veiled insults to Oracle
  24. training dataset