We needmoredataCan wemake itreal-time?Thebusinessneed has…evolvedThe serverissuspiciouslyslow todayWorksperfectlyon mymachineDatasethas 47samples.Total.Someonehoggedall GPUsThe labelsarecompletelywrongWhoannotatedthis?!SSHconnectiondied mid-experimentRestartkernel,run all,prayServercrashedduring thelive demoStakeholderghostedafter week2“Quick 5-min sync”= 45minutesPetphotobombedthe video callFree!A meetingcouldhave beenan emailCUDAout ofmemoryActually,let’s pivotthe entireapproachForgot tokill myprocess…sorry team!Jupyterkernel diedmysteriouslyExtremeclassimbalancestrikes againTest dataleaked intotraining setThisshould besimple,right?Who lefttrainingrunning ALLweekend?Groundtruth isn’tactuallytrueCan weget 99.9%accuracy?Serverrebootedovernight.RIP myresults.Nicepajamatop on thecallOOMkilled atepoch 99of 100Internetdied atdemotimeWhen willthe model beproduction-ready?Thisnotebookis 2000cells longI’lldocumentthis laterForgot toshuffle thedatasetThe datais toonoisy touseAs permy lastemail…Requirementschanged…againWait…which celldid I runlast?Just addONE morefeaturebeforelaunchLoss wentto NaN onstep 1We needmoredataCan wemake itreal-time?Thebusinessneed has…evolvedThe serverissuspiciouslyslow todayWorksperfectlyon mymachineDatasethas 47samples.Total.Someonehoggedall GPUsThe labelsarecompletelywrongWhoannotatedthis?!SSHconnectiondied mid-experimentRestartkernel,run all,prayServercrashedduring thelive demoStakeholderghostedafter week2“Quick 5-min sync”= 45minutesPetphotobombedthe video callFree!A meetingcouldhave beenan emailCUDAout ofmemoryActually,let’s pivotthe entireapproachForgot tokill myprocess…sorry team!Jupyterkernel diedmysteriouslyExtremeclassimbalancestrikes againTest dataleaked intotraining setThisshould besimple,right?Who lefttrainingrunning ALLweekend?Groundtruth isn’tactuallytrueCan weget 99.9%accuracy?Serverrebootedovernight.RIP myresults.Nicepajamatop on thecallOOMkilled atepoch 99of 100Internetdied atdemotimeWhen willthe model beproduction-ready?Thisnotebookis 2000cells longI’lldocumentthis laterForgot toshuffle thedatasetThe datais toonoisy touseAs permy lastemail…Requirementschanged…againWait…which celldid I runlast?Just addONE morefeaturebeforelaunchLoss wentto NaN onstep 1

AI lab 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. We need more data
  2. Can we make it real-time?
  3. The business need has… evolved
  4. The server is suspiciously slow today
  5. Works perfectly on my machine
  6. Dataset has 47 samples. Total.
  7. Someone hogged all GPUs
  8. The labels are completely wrong
  9. Who annotated this?!
  10. SSH connection died mid-experiment
  11. Restart kernel, run all, pray
  12. Server crashed during the live demo
  13. Stakeholder ghosted after week 2
  14. “Quick 5-min sync” = 45 minutes
  15. Pet photobombed the video call
  16. Free!
  17. A meeting could have been an email
  18. CUDA out of memory
  19. Actually, let’s pivot the entire approach
  20. Forgot to kill my process… sorry team!
  21. Jupyter kernel died mysteriously
  22. Extreme class imbalance strikes again
  23. Test data leaked into training set
  24. This should be simple, right?
  25. Who left training running ALL weekend?
  26. Ground truth isn’t actually true
  27. Can we get 99.9% accuracy?
  28. Server rebooted overnight. RIP my results.
  29. Nice pajama top on the call
  30. OOM killed at epoch 99 of 100
  31. Internet died at demo time
  32. When will the model be production-ready?
  33. This notebook is 2000 cells long
  34. I’ll document this later
  35. Forgot to shuffle the dataset
  36. The data is too noisy to use
  37. As per my last email…
  38. Requirements changed… again
  39. Wait… which cell did I run last?
  40. Just add ONE more feature before launch
  41. Loss went to NaN on step 1