Understand & Where to use AI & Machine Learning 101

on YouTube ↗54m

" summary

Oracle claims its autonomous database uses ML to tune, patch and secure itself and offers a free cloud trial to spin up instances in minutes; AutoML produces working Python notebooks in minutes where it used to take days; Apex is already powering about 2 million apps at ~3,000/day and now generates SQL from English; Oracle pairs Co:here LLMs with a new vector database and uses retrieval-augmented generation to boost answer accuracy toward ~96%.

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" chapters (85)

1. 0:00intro
2. 1:43preamble
3. 2:10where to use ai & ml 101
4. 2:44about viscosity
5. 3:40agenda
6. 4:47the economic potential of genai
7. 5:13symbiotic coming relationship; you & robots
8. 5:53the brain center at whipple's & chatgpt
9. 6:23robotics / automation impact to jobs
10. 6:50leverage - db, gps & robotics
11. 7:22autonomous database - replacing the dba?
12. 7:44biju thomas - emerging jobs (devloper/dba)
13. 8:11characteristics of big data - the five v's
14. 8:38converged database
15. 9:49a robot may not look like one!
16. 10:10autonomous db : future dba & robot db
17. 10:56oracle machine learning: brief highlights only
18. 11:17ml process (supervised learning)
19. 12:34business understanding
20. 13:18oaa model build and real-time sql apply
21. 14:29dbms_data_mining oracle algorithms
22. 14:43ml learning in adw/atp
23. 16:10a game of pool
24. 16:49oracle ml algorithms and analytics in oracle db
25. 17:12decision tree algorithm (ml classifier)
26. 17:47oml (oaa) oracle data mining sql sample (partial)
27. 18:25random forest (ml classifier)
28. 18:50neural network
29. 20:29one-class svm (ml anomaly detection)
30. 21:15hierarchical k-means (ml cluster)
31. 21:52seasonal, irregular & missing data: time series algorithm
32. 22:28linear model (regression)
33. 22:52generalized linear model (glm)
34. 23:21principal component analysis (attribute importance)
35. 24:26living doll
36. 24:43apriori / market based (association rules)
37. 25:20singular value decomposition (feature extraction)
38. 25:31principal component analysis (feature extraction)
39. 25:47in his image
40. 26:11number 12 looks like you (2020)
41. 26:22sql analytics (windows / patterns / aggregates)
42. 26:56statistical functions in oracle (partial list)
43. 27:06ml ffunctions - oracle docs
44. 27:48autml is here for autonomous db
45. 28:15time enough at last for ml with automl
46. 28:55ml & ai - oracle's built-in algorithms
47. 29:05biju thomas at odtug
48. 29:55applications - ai powered; analytics & ml
49. 30:16oracle genai
50. 30:32sql generation from natural language using llm
51. 31:10think of it as an assistant (60-70%)
52. 32:03apex development speed- genai
53. 33:25genai writes the sql
54. 33:41what's next: a worldwide race to build ai
55. 34:26healthcare driving oracle to better ai products
56. 34:40oracle driving first responders with tesla
57. 34:50openai - ten years later... the baby talks!
58. 35:21generative ai - things to know...
59. 36:20chat gpt
60. 36:45google's bard
61. 37:20transformers - google, 2017
62. 38:04generative ai: gpt & chatgpt
63. 38:35chatgpt-4
64. 38:51oracle vector db
65. 39:25from juan loaiza interview
66. 40:23vecotr search
67. 40:49create table with vector data type & blob
68. 42:36retrieval augmented generation
69. 43:03answer detailed questions / supply manuals
70. 43:29ask question & reference document ai searches
71. 44:06from stanford paper
72. 44:54robots we grew up with... movie robots... closer to the future... today's robots
73. 45:38genai inside apex, sensors, robots... etc.
74. 45:53use oracle va with robots
75. 46:03db, ai & vr
76. 46:25a world of difference (getting closer)
77. 47:05the after hours (future sentience issues ahead)
78. 47:36the digital transformation ahead
79. 48:11digital - how did we go from magical to toxic?
80. 48:59gartner 2020 hype cycle
81. 49:49quantum computing makes ml fast enough!
82. 50:143 types of ai
83. 50:42final thoughts
84. 51:26summary
85. 53:12thank you!

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